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aquavm/benches/PERFORMANCE.txt

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chore(bench): add bench results (#467) add bench results for current Marine
2023-02-14 09:59:49 +02:00
Machine 05b76e53f793eceba4cb1e947eecaedf581b236317d6c24d5fba40ce9350735f:
Platform: Linux-5.10.136-x86_64-AMD_Ryzen_9_5950X_16-Core_Processor-with-glibc2.36
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
Timestamp: 2023-02-14 07:53:57.703442+00:00
chore(bench): add bench results (#467) add bench results for current Marine
2023-02-14 09:59:49 +02:00
AquaVM version: 0.35.1
Benches:
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
big_values_data (7.05ms): Loading a trace with huge values
air::runner::execute_air: 7.05ms
farewell_step::outcome::from_success_result: 2.77ms
populate_outcome_from_contexts: 2.74ms
to_vec(call_results): 9.00µs
to_vec(data): 2.21ms
preparation_step::preparation::prepare: 4.21ms
air::preparation_step::preparation::make_exec_ctx: 12.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 4.14ms
air_parser::parser::air_parser::parse: 15.00µs
runner::execute: 6.00µs
dashboard (45.83ms): big dashboard test
air::runner::execute_air: 45.83ms
farewell_step::outcome::from_success_result: 224.00µs
populate_outcome_from_contexts: 200.00µs
chore(bench): add bench results (#467) add bench results for current Marine
2023-02-14 09:59:49 +02:00
to_vec(call_results): 13.00µs
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
to_vec(data): 102.00µs
preparation_step::preparation::prepare: 448.00µs
air::preparation_step::preparation::make_exec_ctx: 19.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 275.00µs
air_parser::parser::air_parser::parse: 95.00µs
runner::execute: 45.09ms
execute: 40.68ms
execute: 4.10ms
instructions::call::resolved_call::prepare_request_params: 337.00µs
instructions::call::resolved_call::serde_json::to_string(tetraplets): 14.00µs
resolver::resolve::resolve_ast_variable: 216.00µs
resolve_variable: 70.00µs
resolver::resolve::resolve_ast_variable: 572.00µs
resolve_variable: 184.00µs
new: 26.91ms
resolve_ast_scalar: 20.17ms
resolve_ast_variable: 12.53ms
resolve_variable: 4.08ms
long_data (2.05ms): Long data trace
air::runner::execute_air: 2.05ms
farewell_step::outcome::from_success_result: 597.00µs
populate_outcome_from_contexts: 573.00µs
to_vec(call_results): 9.00µs
to_vec(data): 300.00µs
preparation_step::preparation::prepare: 1.39ms
air::preparation_step::preparation::make_exec_ctx: 22.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 1.30ms
air_parser::parser::air_parser::parse: 14.00µs
runner::execute: 6.00µs
network_explore (3.52ms): 5 peers of network are discovered
air::runner::execute_air: 3.52ms
farewell_step::outcome::from_success_result: 100.00µs
populate_outcome_from_contexts: 79.00µs
to_vec(call_results): 8.00µs
chore(bench): add bench results (#467) add bench results for current Marine
2023-02-14 09:59:49 +02:00
to_vec(data): 25.00µs
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
preparation_step::preparation::prepare: 191.00µs
air::preparation_step::preparation::make_exec_ctx: 14.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 70.00µs
air_parser::parser::air_parser::parse: 52.00µs
runner::execute: 3.17ms
execute: 2.83ms
execute: 470.00µs
resolve_ast_variable: 189.00µs
resolve_variable: 61.00µs
new: 1.69ms
resolve_ast_scalar: 1.25ms
resolve_ast_variable: 780.00µs
resolve_variable: 258.00µs
parser_10000_100 (17.82ms): Running very long AIR script with lot of variables and assignments
air::runner::execute_air: 17.82ms
farewell_step::outcome::from_success_result: 77.00µs
populate_outcome_from_contexts: 58.00µs
to_vec(call_results): 8.00µs
to_vec(data): 14.00µs
preparation_step::preparation::prepare: 16.93ms
air::preparation_step::preparation::make_exec_ctx: 12.00µs
air_parser::parser::air_parser::parse: 16.87ms
runner::execute: 95.00µs
execute: 65.00µs
execute: 11.00µs
new: 13.00µs
chore(benches): update benchmark data to new format (#559) * feat(aquavm-air-cli): `run` fails if AquaVM fails Unless `run --no-fail` is provided. It will make benchmarks fail on errors, unless you provide `--no-fail` to specific benchmark. * Fix dashboard and network_explore benches * Convert benchmark data to new format * `performance_metering`: use dirs only Ordinary files like README.md are not considered to be a benchmark. * Update `benches/performance_metering/README.md` * Fix performance report Looks like performance reports was merged in wrong order: data is not sorted by machine ID. The sorting is needed for stable diffs. * Run benchmarks on Macbook Air M1
2023-04-11 02:27:32 +07:00
Machine 0dfa4f098d7a6ef0d77a7bbc028ccf65fd6dc8d37be8a466ab3933a1a4a8e113:
Platform: macOS-11.7.3-x86_64-i386-64bit
Timestamp: 2023-02-14 04:31:01.303450+00:00
AquaVM version: 0.35.1
Benches:
big_values_data (14.17ms): Loading a trace with huge values
air::runner::execute_air: 14.17ms
farewell_step::outcome::from_success_result: 6.08ms
populate_outcome_from_contexts: 6.00ms
to_vec(call_results): 17.00µs
to_vec(data): 4.95ms
preparation_step::preparation::prepare: 7.87ms
air::preparation_step::preparation::make_exec_ctx: 40.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 7.61ms
air_parser::parser::air_parser::parse: 66.00µs
runner::execute: 18.00µs
dashboard (89.32ms): big dashboard test
air::runner::execute_air: 89.32ms
farewell_step::outcome::from_success_result: 469.00µs
populate_outcome_from_contexts: 415.00µs
to_vec(call_results): 33.00µs
to_vec(data): 215.00µs
preparation_step::preparation::prepare: 1.06ms
air::preparation_step::preparation::make_exec_ctx: 56.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 589.00µs
air_parser::parser::air_parser::parse: 233.00µs
runner::execute: 87.58ms
execute: 78.38ms
execute: 7.91ms
instructions::call::resolved_call::prepare_request_params: 678.00µs
instructions::call::resolved_call::serde_json::to_string(tetraplets): 36.00µs
resolver::resolve::resolve_ast_variable: 416.00µs
resolve_variable: 131.00µs
resolver::resolve::resolve_ast_variable: 1.09ms
resolve_variable: 362.00µs
new: 50.99ms
resolve_ast_scalar: 37.72ms
resolve_ast_variable: 23.15ms
resolve_variable: 7.40ms
long_data (4.44ms): Long data trace
air::runner::execute_air: 4.44ms
farewell_step::outcome::from_success_result: 1.32ms
populate_outcome_from_contexts: 1.24ms
to_vec(call_results): 23.00µs
to_vec(data): 672.00µs
preparation_step::preparation::prepare: 2.88ms
air::preparation_step::preparation::make_exec_ctx: 64.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 2.59ms
air_parser::parser::air_parser::parse: 63.00µs
runner::execute: 22.00µs
network_explore (8.09ms): 5 peers of network are discovered
air::runner::execute_air: 8.09ms
farewell_step::outcome::from_success_result: 256.00µs
populate_outcome_from_contexts: 198.00µs
to_vec(call_results): 21.00µs
to_vec(data): 62.00µs
preparation_step::preparation::prepare: 661.00µs
air::preparation_step::preparation::make_exec_ctx: 60.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 244.00µs
air_parser::parser::air_parser::parse: 174.00µs
runner::execute: 6.94ms
execute: 6.12ms
execute: 1.02ms
resolve_ast_variable: 393.00µs
resolve_variable: 124.00µs
new: 3.57ms
resolve_ast_scalar: 2.61ms
resolve_ast_variable: 1.60ms
resolve_variable: 517.00µs
parser_10000_100 (32.25ms): Running very long AIR script with lot of variables and assignments
air::runner::execute_air: 32.25ms
farewell_step::outcome::from_success_result: 202.00µs
populate_outcome_from_contexts: 152.00µs
to_vec(call_results): 17.00µs
to_vec(data): 45.00µs
preparation_step::preparation::prepare: 29.95ms
air::preparation_step::preparation::make_exec_ctx: 49.00µs
air_parser::parser::air_parser::parse: 29.74ms
runner::execute: 264.00µs
execute: 169.00µs
execute: 29.00µs
new: 40.00µs
chore(bench): add bench results (#465) bench results
2023-02-13 15:57:13 +03:00
Machine 5fce753d17dde8b439ef04cdbce135789eb44646c753548ad79a37b88cf17f0a:
Platform: macOS-12.3.1-arm64-arm-64bit
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
Timestamp: 2023-02-13 16:59:20.507375+00:00
chore(bench): add bench results (#465) bench results
2023-02-13 15:57:13 +03:00
AquaVM version: 0.35.1
Benches:
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
big_values_data (31.97ms): Loading a trace with huge values
air::runner::execute_air: 31.97ms
farewell_step::outcome::from_success_result: 10.56ms
populate_outcome_from_contexts: 8.69ms
to_vec(call_results): 108.00µs
to_vec(data): 5.66ms
preparation_step::preparation::prepare: 17.47ms
air::preparation_step::preparation::make_exec_ctx: 1.40ms
air_interpreter_data::interpreter_data::serde_json::from_slice: 10.68ms
air_parser::parser::air_parser::parse: 1.86ms
runner::execute: 126.00µs
dashboard (103.60ms): big dashboard test
air::runner::execute_air: 103.60ms
farewell_step::outcome::from_success_result: 4.71ms
populate_outcome_from_contexts: 3.70ms
to_vec(call_results): 162.00µs
to_vec(data): 1.87ms
preparation_step::preparation::prepare: 16.17ms
air::preparation_step::preparation::make_exec_ctx: 1.61ms
air_interpreter_data::interpreter_data::serde_json::from_slice: 5.50ms
air_parser::parser::air_parser::parse: 6.11ms
runner::execute: 78.68ms
execute: 66.40ms
execute: 9.37ms
instructions::call::resolved_call::prepare_request_params: 1.43ms
instructions::call::resolved_call::serde_json::to_string(tetraplets): 398.00µs
resolver::resolve::resolve_ast_variable: 335.00µs
resolve_variable: 105.00µs
resolver::resolve::resolve_ast_variable: 946.00µs
resolve_variable: 277.00µs
new: 40.53ms
resolve_ast_scalar: 29.73ms
resolve_ast_variable: 18.24ms
resolve_variable: 5.84ms
long_data (24.35ms): Long data trace
air::runner::execute_air: 24.35ms
farewell_step::outcome::from_success_result: 6.79ms
populate_outcome_from_contexts: 5.07ms
to_vec(call_results): 108.00µs
to_vec(data): 2.23ms
preparation_step::preparation::prepare: 13.54ms
air::preparation_step::preparation::make_exec_ctx: 1.75ms
air_interpreter_data::interpreter_data::serde_json::from_slice: 6.77ms
air_parser::parser::air_parser::parse: 1.84ms
runner::execute: 130.00µs
network_explore (46.01ms): 5 peers of network are discovered
air::runner::execute_air: 46.01ms
farewell_step::outcome::from_success_result: 5.48ms
populate_outcome_from_contexts: 4.50ms
to_vec(call_results): 105.00µs
to_vec(data): 2.25ms
preparation_step::preparation::prepare: 18.74ms
air::preparation_step::preparation::make_exec_ctx: 1.98ms
air_interpreter_data::interpreter_data::serde_json::from_slice: 7.05ms
air_parser::parser::air_parser::parse: 6.74ms
runner::execute: 17.86ms
execute: 9.97ms
execute: 3.17ms
resolve_ast_variable: 339.00µs
resolve_variable: 94.00µs
new: 4.10ms
resolve_ast_scalar: 2.65ms
resolve_ast_variable: 1.67ms
resolve_variable: 547.00µs
parser_10000_100 (48.47ms): Running very long AIR script with lot of variables and assignments
air::runner::execute_air: 48.47ms
farewell_step::outcome::from_success_result: 4.70ms
populate_outcome_from_contexts: 3.48ms
to_vec(call_results): 105.00µs
to_vec(data): 1.60ms
preparation_step::preparation::prepare: 34.34ms
air::preparation_step::preparation::make_exec_ctx: 1.41ms
air_parser::parser::air_parser::parse: 29.66ms
runner::execute: 4.39ms
execute: 2.00ms
execute: 483.00µs
new: 471.00µs
chore(bench): add bench results (#469) add bench results for current Marine
2023-02-14 12:45:43 +03:00
Machine 62dabcde478dc58760ebbe71ef6047299144a5f63990c6c3d826ebf30175adfc:
Platform: Linux-5.15.0-60-generic-x86_64-with-glibc2.35
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
Timestamp: 2023-02-14 10:33:54.321822+00:00
chore(bench): add bench results (#469) add bench results for current Marine
2023-02-14 12:45:43 +03:00
AquaVM version: 0.35.1
Benches:
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
big_values_data (12.75ms): Loading a trace with huge values
air::runner::execute_air: 12.75ms
farewell_step::outcome::from_success_result: 5.85ms
populate_outcome_from_contexts: 5.78ms
to_vec(call_results): 18.00µs
to_vec(data): 4.51ms
preparation_step::preparation::prepare: 6.78ms
air::preparation_step::preparation::make_exec_ctx: 29.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 6.62ms
air_parser::parser::air_parser::parse: 22.00µs
runner::execute: 11.00µs
dashboard (146.20ms): big dashboard test
air::runner::execute_air: 146.20ms
farewell_step::outcome::from_success_result: 522.00µs
populate_outcome_from_contexts: 441.00µs
to_vec(call_results): 39.00µs
to_vec(data): 212.00µs
preparation_step::preparation::prepare: 697.00µs
chore(bench): add bench results (#469) add bench results for current Marine
2023-02-14 12:45:43 +03:00
air::preparation_step::preparation::make_exec_ctx: 27.00µs
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
air_interpreter_data::interpreter_data::serde_json::from_slice: 402.00µs
air_parser::parser::air_parser::parse: 121.00µs
runner::execute: 145.10ms
execute: 131.22ms
execute: 13.68ms
instructions::call::resolved_call::prepare_request_params: 959.00µs
instructions::call::resolved_call::serde_json::to_string(tetraplets): 41.00µs
resolver::resolve::resolve_ast_variable: 610.00µs
resolve_variable: 199.00µs
resolver::resolve::resolve_ast_variable: 1.75ms
resolve_variable: 555.00µs
new: 83.94ms
resolve_ast_scalar: 60.95ms
resolve_ast_variable: 36.93ms
resolve_variable: 11.76ms
long_data (3.41ms): Long data trace
air::runner::execute_air: 3.41ms
farewell_step::outcome::from_success_result: 1.07ms
populate_outcome_from_contexts: 1.00ms
to_vec(call_results): 20.00µs
to_vec(data): 540.00µs
preparation_step::preparation::prepare: 2.21ms
air::preparation_step::preparation::make_exec_ctx: 50.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 2.03ms
air_parser::parser::air_parser::parse: 21.00µs
runner::execute: 10.00µs
network_explore (11.17ms): 5 peers of network are discovered
air::runner::execute_air: 11.17ms
farewell_step::outcome::from_success_result: 306.00µs
populate_outcome_from_contexts: 228.00µs
to_vec(call_results): 32.00µs
to_vec(data): 62.00µs
preparation_step::preparation::prepare: 345.00µs
air::preparation_step::preparation::make_exec_ctx: 22.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 102.00µs
air_parser::parser::air_parser::parse: 74.00µs
runner::execute: 10.35ms
execute: 9.32ms
execute: 1.55ms
resolve_ast_variable: 592.00µs
resolve_variable: 189.00µs
new: 5.43ms
resolve_ast_scalar: 3.93ms
resolve_ast_variable: 2.38ms
resolve_variable: 766.00µs
parser_10000_100 (26.83ms): Running very long AIR script with lot of variables and assignments
air::runner::execute_air: 26.83ms
farewell_step::outcome::from_success_result: 205.00µs
populate_outcome_from_contexts: 149.00µs
chore(bench): add bench results (#469) add bench results for current Marine
2023-02-14 12:45:43 +03:00
to_vec(call_results): 28.00µs
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
to_vec(data): 33.00µs
preparation_step::preparation::prepare: 24.70ms
air::preparation_step::preparation::make_exec_ctx: 26.00µs
air_parser::parser::air_parser::parse: 24.55ms
runner::execute: 270.00µs
execute: 197.00µs
execute: 42.00µs
new: 42.00µs
chore(benchmarking): data generators for a set of map-related benchmarks [fixes VM-345] (#735)
2023-11-08 16:22:17 +03:00
Machine 88756ca30bfb93b0da6a64252adc98fc3e97e142c3b4970af3d2948fd66107b4:
Platform: Linux-6.5.9-arch2-1-x86_64-with-glibc2.35
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
Timestamp: 2024-01-15 11:32:08.545924+00:00
AquaVM version: 0.58.0
chore(benchmarking): data generators for a set of map-related benchmarks [fixes VM-345] (#735)
2023-11-08 16:22:17 +03:00
Benches:
Features:
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
big-values-data (5.02ms; 56.250 MiB, 56.250 MiB): Loading a trace with huge values
air::runner::execute_air: 5.02ms
preparation_step::preparation::parse_data: 1.07ms
serialize: 16.00µs
try_from_slice: 968.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
preparation_step::preparation::prepare: 184.00µs
air::preparation_step::preparation::make_exec_ctx: 44.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 18.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
runner::execute: 9.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
runner::farewell: 927.00µs
from_success_result: 906.00µs
populate_outcome_from_contexts: 871.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 200.00µs
air_interpreter_data::interpreter_data::serialize: 483.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
signing_step::sign_produced_cids: 102.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
verification_step::verify: 2.61ms
verify: 2.21ms
call-requests500 (24.40ms; 57.375 MiB, 57.375 MiB): multiple call requests
air::runner::execute_air: 24.40ms
preparation_step::preparation::parse_data: 149.00µs
serialize: 15.00µs
try_from_slice: 51.00µs
preparation_step::preparation::prepare: 220.00µs
air::preparation_step::preparation::make_exec_ctx: 44.00µs
CallResultsRepr.deserialize: 14.00µs
air_parser::parser::air_parser::parse: 49.00µs
runner::execute: 22.20ms
runner::farewell: 1.49ms
from_success_result: 1.46ms
populate_outcome_from_contexts: 1.34ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 1.07ms
air::farewell_step::outcome::InterpreterDataEnv::serialize: 23.00µs
air_interpreter_data::interpreter_data::serialize: 68.00µs
signing_step::sign_produced_cids: 103.00µs
verification_step::verify: 96.00µs
verify: 10.00µs
call-result-100mb (530.00ms; 580.375 MiB, 580.375 MiB): benchmarking
air::runner::execute_air: 530.00ms
preparation_step::preparation::parse_data: 49.20ms
serialize: 16.00µs
try_from_slice: 49.13ms
preparation_step::preparation::prepare: 195.00µs
air::preparation_step::preparation::make_exec_ctx: 40.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
CallResultsRepr.deserialize: 10.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
air_parser::parser::air_parser::parse: 35.00µs
runner::execute: 205.00ms
runner::farewell: 50.00ms
from_success_result: 50.00ms
populate_outcome_from_contexts: 50.00ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 16.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 14.40ms
air_interpreter_data::interpreter_data::serialize: 35.30ms
signing_step::sign_produced_cids: 109.00µs
verification_step::verify: 225.00ms
verify: 225.00ms
call-results500 (26.30ms; 54.438 MiB, 54.438 MiB): multiple call results
air::runner::execute_air: 26.30ms
preparation_step::preparation::parse_data: 232.00µs
serialize: 14.00µs
try_from_slice: 127.00µs
preparation_step::preparation::prepare: 421.00µs
air::preparation_step::preparation::make_exec_ctx: 229.00µs
CallResultsRepr.deserialize: 194.00µs
air_parser::parser::air_parser::parse: 50.00µs
runner::execute: 22.90ms
runner::farewell: 1.92ms
from_success_result: 1.89ms
populate_outcome_from_contexts: 1.42ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 120.00µs
air_interpreter_data::interpreter_data::serialize: 652.00µs
signing_step::sign_produced_cids: 548.00µs
verification_step::verify: 122.00µs
verify: 13.00µs
canon-map-100mb (1.11s; 1.305 GiB, 1.305 GiB): benchmarking
air::runner::execute_air: 1.11s
preparation_step::preparation::parse_data: 49.60ms
serialize: 16.00µs
try_from_slice: 49.43ms
preparation_step::preparation::prepare: 209.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 46.00µs
runner::execute: 706.00ms
runner::farewell: 127.00ms
from_success_result: 127.00ms
populate_outcome_from_contexts: 127.00ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 37.40ms
air_interpreter_data::interpreter_data::serialize: 89.00ms
signing_step::sign_produced_cids: 112.00µs
verification_step::verify: 224.00ms
verify: 224.00ms
canon-map-key-by-lens (12.80ms; 55.312 MiB, 55.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 12.80ms
preparation_step::preparation::parse_data: 2.46ms
serialize: 15.00µs
try_from_slice: 2.35ms
preparation_step::preparation::prepare: 533.00µs
air::preparation_step::preparation::make_exec_ctx: 351.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 55.00µs
runner::execute: 3.13ms
runner::farewell: 1.78ms
from_success_result: 1.75ms
populate_outcome_from_contexts: 1.42ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 120.00µs
air_interpreter_data::interpreter_data::serialize: 895.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
signing_step::sign_produced_cids: 101.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
verification_step::verify: 4.63ms
verify: 4.26ms
canon-map-key-element-by-lens (13.10ms; 55.312 MiB, 55.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 13.10ms
preparation_step::preparation::parse_data: 2.49ms
serialize: 16.00µs
try_from_slice: 2.39ms
preparation_step::preparation::prepare: 541.00µs
air::preparation_step::preparation::make_exec_ctx: 357.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 54.00µs
runner::execute: 3.35ms
runner::farewell: 1.79ms
from_success_result: 1.77ms
populate_outcome_from_contexts: 1.43ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 121.00µs
air_interpreter_data::interpreter_data::serialize: 891.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
signing_step::sign_produced_cids: 103.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
verification_step::verify: 4.69ms
verify: 4.33ms
canon-map-multiple-keys (13.00ms; 54.562 MiB, 54.562 MiB): benchmarking a map insert operation
air::runner::execute_air: 13.00ms
preparation_step::preparation::parse_data: 227.00µs
serialize: 18.00µs
try_from_slice: 117.00µs
preparation_step::preparation::prepare: 225.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
air::preparation_step::preparation::make_exec_ctx: 42.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 50.00µs
runner::execute: 10.10ms
runner::farewell: 1.78ms
from_success_result: 1.75ms
populate_outcome_from_contexts: 1.39ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 96.00µs
air_interpreter_data::interpreter_data::serialize: 893.00µs
signing_step::sign_produced_cids: 112.00µs
verification_step::verify: 424.00µs
verify: 27.00µs
canon-map-scalar-multiple-keys (4.92ms; 53.125 MiB, 53.125 MiB): benchmarking a map insert operation
air::runner::execute_air: 4.92ms
preparation_step::preparation::parse_data: 210.00µs
serialize: 16.00µs
try_from_slice: 110.00µs
preparation_step::preparation::prepare: 214.00µs
air::preparation_step::preparation::make_exec_ctx: 42.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 46.00µs
runner::execute: 3.44ms
runner::farewell: 432.00µs
from_success_result: 408.00µs
populate_outcome_from_contexts: 367.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 21.00µs
air_interpreter_data::interpreter_data::serialize: 55.00µs
signing_step::sign_produced_cids: 104.00µs
verification_step::verify: 391.00µs
verify: 27.00µs
canon-map-scalar-single-key (3.86ms; 53.062 MiB, 53.062 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.86ms
preparation_step::preparation::parse_data: 202.00µs
serialize: 16.00µs
try_from_slice: 101.00µs
preparation_step::preparation::prepare: 206.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
CallResultsRepr.deserialize: 11.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
air_parser::parser::air_parser::parse: 42.00µs
runner::execute: 2.39ms
runner::farewell: 426.00µs
from_success_result: 404.00µs
populate_outcome_from_contexts: 352.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 21.00µs
air_interpreter_data::interpreter_data::serialize: 66.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
signing_step::sign_produced_cids: 102.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
verification_step::verify: 402.00µs
verify: 40.00µs
canon-map-single-key (10.30ms; 54.438 MiB, 54.438 MiB): benchmarking a map insert operation
air::runner::execute_air: 10.30ms
preparation_step::preparation::parse_data: 192.00µs
serialize: 16.00µs
try_from_slice: 96.00µs
preparation_step::preparation::prepare: 199.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 40.00µs
runner::execute: 7.57ms
runner::farewell: 1.66ms
from_success_result: 1.64ms
populate_outcome_from_contexts: 1.35ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 107.00µs
air_interpreter_data::interpreter_data::serialize: 903.00µs
signing_step::sign_produced_cids: 102.00µs
verification_step::verify: 399.00µs
verify: 40.00µs
dashboard (6.15ms; 52.688 MiB, 52.688 MiB): big dashboard test
air::runner::execute_air: 6.15ms
preparation_step::preparation::parse_data: 519.00µs
try_from_slice: 435.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
preparation_step::preparation::prepare: 330.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
air::preparation_step::preparation::make_exec_ctx: 64.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 134.00µs
runner::execute: 1.17ms
runner::farewell: 488.00µs
from_success_result: 465.00µs
populate_outcome_from_contexts: 418.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 23.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 40.00µs
air_interpreter_data::interpreter_data::serialize: 119.00µs
signing_step::sign_produced_cids: 107.00µs
verification_step::verify: 3.40ms
verify: 204.00µs
lense-100mb (1.09s; 1.207 GiB, 1.207 GiB): benchmarking
air::runner::execute_air: 1.09s
preparation_step::preparation::parse_data: 49.00ms
serialize: 16.00µs
try_from_slice: 48.93ms
preparation_step::preparation::prepare: 220.00µs
air::preparation_step::preparation::make_exec_ctx: 44.00µs
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 48.00µs
runner::execute: 686.00ms
runner::farewell: 125.00ms
from_success_result: 125.00ms
populate_outcome_from_contexts: 125.00ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 37.10ms
air_interpreter_data::interpreter_data::serialize: 88.10ms
signing_step::sign_produced_cids: 111.00µs
verification_step::verify: 226.00ms
verify: 225.00ms
long-data (3.73ms; 53.125 MiB, 53.125 MiB): Long data trace
air::runner::execute_air: 3.73ms
preparation_step::preparation::parse_data: 969.00µs
serialize: 15.00µs
try_from_slice: 865.00µs
preparation_step::preparation::prepare: 205.00µs
air::preparation_step::preparation::make_exec_ctx: 66.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 17.00µs
runner::execute: 9.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
runner::farewell: 416.00µs
from_success_result: 395.00µs
populate_outcome_from_contexts: 360.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 27.00µs
air_interpreter_data::interpreter_data::serialize: 97.00µs
signing_step::sign_produced_cids: 98.00µs
verification_step::verify: 1.92ms
verify: 490.00µs
map-100mb (1.12s; 1.305 GiB, 1.305 GiB): benchmarking
air::runner::execute_air: 1.12s
preparation_step::preparation::parse_data: 50.40ms
serialize: 16.00µs
try_from_slice: 50.23ms
preparation_step::preparation::prepare: 209.00µs
air::preparation_step::preparation::make_exec_ctx: 38.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 44.00µs
runner::execute: 712.00ms
runner::farewell: 130.00ms
from_success_result: 130.00ms
populate_outcome_from_contexts: 130.00ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 16.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 38.30ms
air_interpreter_data::interpreter_data::serialize: 91.70ms
signing_step::sign_produced_cids: 111.00µs
verification_step::verify: 224.00ms
verify: 224.00ms
multiple-cids10 (2.89ms; 52.500 MiB, 52.500 MiB): verifying multiple CIDs for single peer
air::runner::execute_air: 2.89ms
preparation_step::preparation::parse_data: 325.00µs
try_from_slice: 243.00µs
preparation_step::preparation::prepare: 226.00µs
air::preparation_step::preparation::make_exec_ctx: 56.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 44.00µs
runner::execute: 561.00µs
runner::farewell: 451.00µs
from_success_result: 425.00µs
populate_outcome_from_contexts: 354.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 17.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 32.00µs
air_interpreter_data::interpreter_data::serialize: 103.00µs
signing_step::sign_produced_cids: 103.00µs
verification_step::verify: 1.09ms
verify: 262.00µs
multiple-peers8 (11.10ms; 53.438 MiB, 53.438 MiB): verifying many CIDs for many peers
air::runner::execute_air: 11.10ms
preparation_step::preparation::parse_data: 1.12ms
try_from_slice: 1.04ms
preparation_step::preparation::prepare: 302.00µs
air::preparation_step::preparation::make_exec_ctx: 126.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 51.00µs
runner::execute: 3.76ms
runner::farewell: 924.00µs
from_success_result: 900.00µs
populate_outcome_from_contexts: 777.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 60.00µs
air_interpreter_data::interpreter_data::serialize: 428.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
signing_step::sign_produced_cids: 101.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
verification_step::verify: 4.79ms
verify: 1.24ms
multiple-sigs30 (23.10ms; 55.812 MiB, 55.812 MiB): signing multiple CIDs
air::runner::execute_air: 23.10ms
preparation_step::preparation::parse_data: 3.67ms
try_from_slice: 3.58ms
preparation_step::preparation::prepare: 445.00µs
air::preparation_step::preparation::make_exec_ctx: 272.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
CallResultsRepr.deserialize: 11.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
air_parser::parser::air_parser::parse: 47.00µs
runner::execute: 10.80ms
runner::farewell: 2.78ms
from_success_result: 2.75ms
populate_outcome_from_contexts: 2.59ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 208.00µs
air_interpreter_data::interpreter_data::serialize: 1.28ms
signing_step::sign_produced_cids: 675.00µs
verification_step::verify: 4.51ms
verify: 2.11ms
network-explore (3.09ms; 52.375 MiB, 52.375 MiB): 5 peers of network are discovered
air::runner::execute_air: 3.09ms
preparation_step::preparation::parse_data: 219.00µs
try_from_slice: 137.00µs
preparation_step::preparation::prepare: 238.00µs
air::preparation_step::preparation::make_exec_ctx: 47.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 68.00µs
runner::execute: 173.00µs
runner::farewell: 310.00µs
from_success_result: 287.00µs
populate_outcome_from_contexts: 245.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 18.00µs
air_interpreter_data::interpreter_data::serialize: 38.00µs
signing_step::sign_produced_cids: 102.00µs
verification_step::verify: 1.93ms
verify: 63.00µs
null (988.00µs; 52.375 MiB, 52.375 MiB): Empty data and null script
air::runner::execute_air: 988.00µs
preparation_step::preparation::parse_data: 176.00µs
serialize: 33.00µs
try_from_slice: 38.00µs
preparation_step::preparation::prepare: 207.00µs
air::preparation_step::preparation::make_exec_ctx: 47.00µs
CallResultsRepr.deserialize: 14.00µs
air_parser::parser::air_parser::parse: 22.00µs
runner::execute: 12.00µs
runner::farewell: 306.00µs
from_success_result: 277.00µs
populate_outcome_from_contexts: 234.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 16.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 22.00µs
air_interpreter_data::interpreter_data::serialize: 22.00µs
signing_step::sign_produced_cids: 104.00µs
verification_step::verify: 41.00µs
verify: 12.00µs
parser-10000-100 (31.20ms; 54.625 MiB, 54.625 MiB): long air script with lot of variable assignments
air::runner::execute_air: 31.20ms
preparation_step::preparation::parse_data: 140.00µs
serialize: 27.00µs
try_from_slice: 30.00µs
preparation_step::preparation::prepare: 29.80ms
air::preparation_step::preparation::make_exec_ctx: 42.00µs
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 29.60ms
runner::execute: 24.00µs
runner::farewell: 272.00µs
from_success_result: 247.00µs
populate_outcome_from_contexts: 213.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 18.00µs
air_interpreter_data::interpreter_data::serialize: 21.00µs
signing_step::sign_produced_cids: 99.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
verification_step::verify: 34.00µs
verify: 10.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
parser-air-100mb (676.00ms; 110.500 MiB, 110.500 MiB): multiple calls parser benchmark
air::runner::execute_air: 676.00ms
preparation_step::preparation::parse_data: 141.00µs
serialize: 27.00µs
try_from_slice: 35.00µs
preparation_step::preparation::prepare: 651.00ms
air::preparation_step::preparation::make_exec_ctx: 42.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 651.00ms
runner::execute: 27.00µs
runner::farewell: 264.00µs
from_success_result: 243.00µs
populate_outcome_from_contexts: 208.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 17.00µs
air_interpreter_data::interpreter_data::serialize: 21.00µs
signing_step::sign_produced_cids: 98.00µs
verification_step::verify: 32.00µs
verify: 9.00µs
parser-calls-10000-100 (25.70ms; 54.375 MiB, 54.375 MiB): multiple calls parser benchmark
air::runner::execute_air: 25.70ms
preparation_step::preparation::parse_data: 140.00µs
serialize: 27.00µs
try_from_slice: 30.00µs
preparation_step::preparation::prepare: 24.30ms
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
air::preparation_step::preparation::make_exec_ctx: 40.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 24.10ms
runner::execute: 26.00µs
runner::farewell: 261.00µs
from_success_result: 237.00µs
populate_outcome_from_contexts: 204.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 17.00µs
air_interpreter_data::interpreter_data::serialize: 20.00µs
signing_step::sign_produced_cids: 99.00µs
verification_step::verify: 33.00µs
verify: 10.00µs
populate-map-multiple-keys (4.21ms; 53.000 MiB, 53.000 MiB): benchmarking a map insert operation
air::runner::execute_air: 4.21ms
preparation_step::preparation::parse_data: 165.00µs
serialize: 16.00µs
try_from_slice: 65.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
preparation_step::preparation::prepare: 216.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
air::preparation_step::preparation::make_exec_ctx: 40.00µs
CallResultsRepr.deserialize: 12.00µs
feat(air-parser): VM-347 After next validator fold check (#774)
2023-12-28 20:48:16 +03:00
air_parser::parser::air_parser::parse: 50.00µs
chore(benches): this is a set of RAM intensive benchmarks to understand memory consumption patterns in AquaVM
2024-01-15 15:10:01 +03:00
runner::execute: 2.83ms
runner::farewell: 357.00µs
from_success_result: 334.00µs
populate_outcome_from_contexts: 298.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 22.00µs
air_interpreter_data::interpreter_data::serialize: 62.00µs
signing_step::sign_produced_cids: 112.00µs
verification_step::verify: 398.00µs
verify: 24.00µs
populate-map-single-key (3.48ms; 52.938 MiB, 52.938 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.48ms
preparation_step::preparation::parse_data: 166.00µs
serialize: 16.00µs
try_from_slice: 64.00µs
preparation_step::preparation::prepare: 209.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 45.00µs
runner::execute: 1.97ms
runner::farewell: 491.00µs
from_success_result: 464.00µs
populate_outcome_from_contexts: 407.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 22.00µs
air_interpreter_data::interpreter_data::serialize: 89.00µs
signing_step::sign_produced_cids: 103.00µs
verification_step::verify: 402.00µs
verify: 40.00µs
chore(bench): add bench results (#464) add bench results
2023-02-13 15:34:26 +03:00
Machine c1f3ea5950db0a10b44da931c25774d64ab25084f47d504f72f311e694550ff1:
Platform: macOS-12.0.1-x86_64-i386-64bit
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
Timestamp: 2023-02-13 13:19:34.106863+00:00
chore(bench): add bench results (#464) add bench results
2023-02-13 15:34:26 +03:00
AquaVM version: 0.35.1
Benches:
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
big_values_data (16.56ms): Loading a trace with huge values
air::runner::execute_air: 16.56ms
farewell_step::outcome::from_success_result: 7.35ms
populate_outcome_from_contexts: 7.27ms
to_vec(call_results): 22.00µs
to_vec(data): 5.96ms
preparation_step::preparation::prepare: 8.97ms
air::preparation_step::preparation::make_exec_ctx: 46.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 8.65ms
air_parser::parser::air_parser::parse: 78.00µs
runner::execute: 19.00µs
dashboard (105.40ms): big dashboard test
air::runner::execute_air: 105.40ms
farewell_step::outcome::from_success_result: 549.00µs
populate_outcome_from_contexts: 488.00µs
chore(bench): sort items in text bench resutls (#466)
2023-02-13 19:55:03 +03:00
to_vec(call_results): 43.00µs
feat(avm)!: integrate Marine 0.26.0 (#461)
2023-03-15 17:11:53 +03:00
to_vec(data): 234.00µs
preparation_step::preparation::prepare: 1.31ms
air::preparation_step::preparation::make_exec_ctx: 64.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 737.00µs
air_parser::parser::air_parser::parse: 276.00µs
runner::execute: 103.00ms
execute: 92.47ms
execute: 9.52ms
instructions::call::resolved_call::prepare_request_params: 799.00µs
instructions::call::resolved_call::serde_json::to_string(tetraplets): 51.00µs
resolver::resolve::resolve_ast_variable: 460.00µs
resolve_variable: 145.00µs
resolver::resolve::resolve_ast_variable: 1.42ms
resolve_variable: 477.00µs
new: 59.93ms
resolve_ast_scalar: 44.46ms
resolve_ast_variable: 27.31ms
resolve_variable: 8.72ms
long_data (4.47ms): Long data trace
air::runner::execute_air: 4.47ms
farewell_step::outcome::from_success_result: 1.38ms
populate_outcome_from_contexts: 1.27ms
to_vec(call_results): 20.00µs
to_vec(data): 652.00µs
preparation_step::preparation::prepare: 2.82ms
air::preparation_step::preparation::make_exec_ctx: 64.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 2.53ms
air_parser::parser::air_parser::parse: 63.00µs
runner::execute: 25.00µs
network_explore (9.70ms): 5 peers of network are discovered
air::runner::execute_air: 9.70ms
farewell_step::outcome::from_success_result: 291.00µs
populate_outcome_from_contexts: 230.00µs
to_vec(call_results): 26.00µs
to_vec(data): 79.00µs
preparation_step::preparation::prepare: 847.00µs
air::preparation_step::preparation::make_exec_ctx: 64.00µs
air_interpreter_data::interpreter_data::serde_json::from_slice: 315.00µs
air_parser::parser::air_parser::parse: 206.00µs
runner::execute: 8.29ms
execute: 7.28ms
execute: 1.28ms
resolve_ast_variable: 497.00µs
resolve_variable: 155.00µs
new: 4.24ms
resolve_ast_scalar: 2.99ms
resolve_ast_variable: 1.81ms
resolve_variable: 569.00µs
parser_10000_100 (33.06ms): Running very long AIR script with lot of variables and assignments
air::runner::execute_air: 33.06ms
farewell_step::outcome::from_success_result: 207.00µs
populate_outcome_from_contexts: 158.00µs
to_vec(call_results): 18.00µs
to_vec(data): 47.00µs
preparation_step::preparation::prepare: 30.52ms
air::preparation_step::preparation::make_exec_ctx: 63.00µs
air_parser::parser::air_parser::parse: 30.28ms
runner::execute: 270.00µs
execute: 167.00µs
execute: 29.00µs
new: 38.00µs
feat(tools): VM-194 performance metering (#440) * Experimental performance metering * Average on repeated runs with `--repeat` option * Add "version" field to the report The version is got from `air/Cargo.toml`. * Allow disabling preparing binaries with the `--no-prepare-binaries` option. * Human-readable execution time in the report * Add dashboard benchmark * Human-readable text report
2023-02-03 23:26:06 +07:00
Machine d77ebe8481884bc3b2778c8083f1bf459e548e929edd87041beb14f6b868d35f:
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
Platform: macOS-14.3-arm64-arm-64bit
Timestamp: 2024-02-04 13:21:31.362831+00:00
AquaVM version: 0.59.0
feat(aquavm-air)!: signature checking (#607)
2023-10-13 23:19:02 +04:00
Benches:
Features: check_signatures,gen_signatures
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
big-values-data (2.27ms; 14.250 MiB, 14.250 MiB): Loading a trace with huge values
air::runner::execute_air: 2.27ms
preparation_step::preparation::parse_data: 472.00µs
serialize: 29.00µs
try_from_slice: 352.00µs
preparation_step::preparation::prepare: 154.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 42.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 29.00µs
runner::execute: 8.00µs
runner::farewell: 395.00µs
from_success_result: 376.00µs
populate_outcome_from_contexts: 340.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 59.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 147.00µs
signing_step::sign_produced_cids: 64.00µs
verification_step::verify: 1.02ms
verify: 786.00µs
call-requests500 (20.33ms; 15.375 MiB, 15.438 MiB): multiple call requests
air::runner::execute_air: 20.33ms
preparation_step::preparation::parse_data: 188.00µs
serialize: 29.00µs
try_from_slice: 66.00µs
preparation_step::preparation::prepare: 207.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 45.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
CallResultsRepr.deserialize: 18.00µs
air_parser::parser::air_parser::parse: 68.00µs
runner::execute: 18.82ms
runner::farewell: 794.00µs
from_success_result: 774.00µs
populate_outcome_from_contexts: 665.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 426.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 24.00µs
air_interpreter_data::interpreter_data::serialize: 74.00µs
signing_step::sign_produced_cids: 68.00µs
verification_step::verify: 85.00µs
verify: 9.00µs
call-result-100mb (200.30ms; 538.375 MiB, 538.375 MiB): Memory intensive benchmarking test
air::runner::execute_air: 200.30ms
preparation_step::preparation::parse_data: 24.96ms
serialize: 33.00µs
try_from_slice: 24.82ms
preparation_step::preparation::prepare: 197.00µs
air::preparation_step::preparation::make_exec_ctx: 50.00µs
CallResultsRepr.deserialize: 12.00µs
air_parser::parser::air_parser::parse: 61.00µs
runner::execute: 78.53ms
runner::farewell: 24.61ms
from_success_result: 24.59ms
populate_outcome_from_contexts: 24.55ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 7.05ms
air_interpreter_data::interpreter_data::serialize: 17.33ms
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 71.80ms
verify: 71.53ms
call-results500 (16.47ms; 12.438 MiB, 12.438 MiB): multiple call results
air::runner::execute_air: 16.47ms
preparation_step::preparation::parse_data: 286.00µs
serialize: 28.00µs
try_from_slice: 164.00µs
preparation_step::preparation::prepare: 351.00µs
air::preparation_step::preparation::make_exec_ctx: 189.00µs
CallResultsRepr.deserialize: 161.00µs
air_parser::parser::air_parser::parse: 74.00µs
runner::execute: 13.99ms
runner::farewell: 1.33ms
from_success_result: 1.31ms
populate_outcome_from_contexts: 831.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 50.00µs
air_interpreter_data::interpreter_data::serialize: 341.00µs
signing_step::sign_produced_cids: 252.00µs
verification_step::verify: 99.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
canon-map-100mb (417.10ms; 1.264 GiB, 1.264 GiB): Memory intensive benchmarking test with canon map
air::runner::execute_air: 417.10ms
preparation_step::preparation::parse_data: 25.18ms
serialize: 32.00µs
try_from_slice: 25.02ms
preparation_step::preparation::prepare: 207.00µs
air::preparation_step::preparation::make_exec_ctx: 44.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 72.00µs
runner::execute: 259.30ms
runner::farewell: 60.18ms
from_success_result: 60.15ms
populate_outcome_from_contexts: 60.09ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 14.16ms
air_interpreter_data::interpreter_data::serialize: 45.78ms
signing_step::sign_produced_cids: 76.00µs
verification_step::verify: 71.92ms
verify: 71.65ms
canon-map-key-by-lens (8.77ms; 13.312 MiB, 13.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 8.77ms
preparation_step::preparation::parse_data: 1.63ms
serialize: 30.00µs
try_from_slice: 1.51ms
preparation_step::preparation::prepare: 360.00µs
air::preparation_step::preparation::make_exec_ctx: 206.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 69.00µs
runner::execute: 2.17ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::farewell: 1.21ms
from_success_result: 1.19ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 867.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 46.00µs
air_interpreter_data::interpreter_data::serialize: 510.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 3.18ms
verify: 2.94ms
canon-map-key-element-by-lens (8.73ms; 13.312 MiB, 13.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 8.73ms
preparation_step::preparation::parse_data: 1.62ms
serialize: 32.00µs
try_from_slice: 1.50ms
preparation_step::preparation::prepare: 360.00µs
air::preparation_step::preparation::make_exec_ctx: 206.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 70.00µs
runner::execute: 2.16ms
runner::farewell: 1.20ms
from_success_result: 1.18ms
populate_outcome_from_contexts: 868.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 48.00µs
air_interpreter_data::interpreter_data::serialize: 509.00µs
signing_step::sign_produced_cids: 62.00µs
verification_step::verify: 3.18ms
verify: 2.94ms
canon-map-multiple-keys (9.15ms; 12.562 MiB, 12.562 MiB): benchmarking a map insert operation
air::runner::execute_air: 9.15ms
preparation_step::preparation::parse_data: 259.00µs
serialize: 34.00µs
try_from_slice: 132.00µs
preparation_step::preparation::prepare: 180.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 57.00µs
runner::execute: 7.06ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::farewell: 1.16ms
from_success_result: 1.14ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 831.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 38.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 497.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 282.00µs
verify: 34.00µs
canon-map-scalar-multiple-keys (3.74ms; 11.125 MiB, 11.125 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.74ms
preparation_step::preparation::parse_data: 249.00µs
serialize: 31.00µs
try_from_slice: 130.00µs
preparation_step::preparation::prepare: 178.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 56.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::execute: 2.45ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::farewell: 371.00µs
from_success_result: 350.00µs
populate_outcome_from_contexts: 305.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
air_interpreter_data::interpreter_data::serialize: 61.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 281.00µs
verify: 35.00µs
canon-map-scalar-single-key (2.92ms; 11.062 MiB, 11.062 MiB): benchmarking a map insert operation
air::runner::execute_air: 2.92ms
preparation_step::preparation::parse_data: 243.00µs
serialize: 30.00µs
try_from_slice: 124.00µs
preparation_step::preparation::prepare: 175.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 54.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::execute: 1.64ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::farewell: 353.00µs
from_success_result: 334.00µs
populate_outcome_from_contexts: 277.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
air_interpreter_data::interpreter_data::serialize: 55.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 296.00µs
verify: 55.00µs
canon-map-single-key (7.34ms; 12.438 MiB, 12.438 MiB): benchmarking a map insert operation
air::runner::execute_air: 7.34ms
preparation_step::preparation::parse_data: 240.00µs
serialize: 31.00µs
try_from_slice: 121.00µs
preparation_step::preparation::prepare: 175.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 54.00µs
runner::execute: 5.32ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::farewell: 1.10ms
from_success_result: 1.08ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 821.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 42.00µs
air_interpreter_data::interpreter_data::serialize: 512.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 293.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 54.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
dashboard (3.99ms; 10.688 MiB, 10.688 MiB): big dashboard test
air::runner::execute_air: 3.99ms
preparation_step::preparation::parse_data: 441.00µs
try_from_slice: 350.00µs
preparation_step::preparation::prepare: 300.00µs
air::preparation_step::preparation::make_exec_ctx: 52.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 163.00µs
runner::execute: 752.00µs
runner::farewell: 392.00µs
from_success_result: 372.00µs
populate_outcome_from_contexts: 328.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 23.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 21.00µs
air_interpreter_data::interpreter_data::serialize: 95.00µs
signing_step::sign_produced_cids: 64.00µs
verification_step::verify: 1.88ms
verify: 160.00µs
hybrid-100mb (638.60ms; 1.975 GiB, 1.975 GiB): Memory intensive benchmarking test with mixed workload
air::runner::execute_air: 638.60ms
preparation_step::preparation::parse_data: 25.04ms
serialize: 31.00µs
try_from_slice: 24.92ms
preparation_step::preparation::prepare: 210.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 42.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 79.00µs
runner::execute: 451.90ms
runner::farewell: 89.10ms
from_success_result: 89.10ms
populate_outcome_from_contexts: 89.04ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 25.82ms
air_interpreter_data::interpreter_data::serialize: 63.05ms
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 72.13ms
verify: 71.87ms
lense-100mb (405.90ms; 1.166 GiB, 1.166 GiB): Memory intensive benchmarking test with lense
air::runner::execute_air: 405.90ms
preparation_step::preparation::parse_data: 25.29ms
serialize: 33.00µs
try_from_slice: 25.15ms
preparation_step::preparation::prepare: 200.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 71.00µs
runner::execute: 248.10ms
runner::farewell: 60.11ms
from_success_result: 60.09ms
populate_outcome_from_contexts: 60.06ms
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 14.23ms
air_interpreter_data::interpreter_data::serialize: 45.63ms
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 71.97ms
verify: 71.72ms
long-data (2.77ms; 11.125 MiB, 11.188 MiB): Long data trace
air::runner::execute_air: 2.77ms
preparation_step::preparation::parse_data: 795.00µs
serialize: 32.00µs
try_from_slice: 673.00µs
preparation_step::preparation::prepare: 169.00µs
air::preparation_step::preparation::make_exec_ctx: 55.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 30.00µs
runner::execute: 8.00µs
runner::farewell: 368.00µs
from_success_result: 349.00µs
populate_outcome_from_contexts: 314.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 30.00µs
air_interpreter_data::interpreter_data::serialize: 68.00µs
signing_step::sign_produced_cids: 62.00µs
verification_step::verify: 1.22ms
verify: 430.00µs
map-100mb (418.10ms; 1.264 GiB, 1.264 GiB): Memory intensive benchmarking test with map 2 scalar
air::runner::execute_air: 418.10ms
preparation_step::preparation::parse_data: 25.13ms
serialize: 32.00µs
try_from_slice: 24.98ms
preparation_step::preparation::prepare: 203.00µs
air::preparation_step::preparation::make_exec_ctx: 45.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 68.00µs
runner::execute: 259.60ms
runner::farewell: 60.99ms
from_success_result: 60.98ms
populate_outcome_from_contexts: 60.92ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 15.12ms
air_interpreter_data::interpreter_data::serialize: 45.65ms
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 71.92ms
verify: 71.64ms
multiple-cids10 (2.09ms; 10.500 MiB, 10.500 MiB): verifying multiple CIDs for single peer
air::runner::execute_air: 2.09ms
preparation_step::preparation::parse_data: 300.00µs
try_from_slice: 210.00µs
preparation_step::preparation::prepare: 193.00µs
air::preparation_step::preparation::make_exec_ctx: 49.00µs
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 60.00µs
runner::execute: 390.00µs
runner::farewell: 326.00µs
from_success_result: 307.00µs
populate_outcome_from_contexts: 252.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
air_interpreter_data::interpreter_data::serialize: 74.00µs
signing_step::sign_produced_cids: 62.00µs
verification_step::verify: 671.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 194.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
multiple-peers8 (7.30ms; 11.438 MiB, 11.438 MiB): verifying many CIDs for many peers
air::runner::execute_air: 7.30ms
preparation_step::preparation::parse_data: 817.00µs
try_from_slice: 728.00µs
preparation_step::preparation::prepare: 240.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 88.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 67.00µs
runner::execute: 2.58ms
runner::farewell: 680.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
from_success_result: 659.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 554.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 28.00µs
air_interpreter_data::interpreter_data::serialize: 272.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 2.76ms
verify: 821.00µs
multiple-sigs30 (15.12ms; 13.500 MiB, 14.125 MiB): signing multiple CIDs
air::runner::execute_air: 15.12ms
preparation_step::preparation::parse_data: 2.44ms
try_from_slice: 2.35ms
preparation_step::preparation::prepare: 320.00µs
air::preparation_step::preparation::make_exec_ctx: 170.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 64.00µs
runner::execute: 7.11ms
runner::farewell: 1.90ms
from_success_result: 1.88ms
populate_outcome_from_contexts: 1.72ms
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 46.00µs
air_interpreter_data::interpreter_data::serialize: 824.00µs
signing_step::sign_produced_cids: 394.00µs
verification_step::verify: 2.79ms
verify: 1.41ms
network-explore (2.13ms; 10.438 MiB, 10.438 MiB): 5 peers of network are discovered
air::runner::execute_air: 2.13ms
preparation_step::preparation::parse_data: 226.00µs
try_from_slice: 139.00µs
preparation_step::preparation::prepare: 207.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 42.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 82.00µs
runner::execute: 150.00µs
runner::farewell: 248.00µs
from_success_result: 228.00µs
populate_outcome_from_contexts: 188.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 15.00µs
air_interpreter_data::interpreter_data::serialize: 31.00µs
signing_step::sign_produced_cids: 64.00µs
verification_step::verify: 1.09ms
verify: 62.00µs
null (818.00µs; 10.375 MiB, 10.375 MiB): Empty data and null script
air::runner::execute_air: 818.00µs
preparation_step::preparation::parse_data: 165.00µs
serialize: 42.00µs
try_from_slice: 31.00µs
preparation_step::preparation::prepare: 175.00µs
air::preparation_step::preparation::make_exec_ctx: 37.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 36.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 8.00µs
runner::farewell: 218.00µs
from_success_result: 198.00µs
populate_outcome_from_contexts: 163.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
air_interpreter_data::interpreter_data::serialize: 14.00µs
signing_step::sign_produced_cids: 74.00µs
verification_step::verify: 35.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
parser-10000-100 (25.40ms; 12.625 MiB, 12.625 MiB): long air script with lot of variable assignments
air::runner::execute_air: 25.40ms
preparation_step::preparation::parse_data: 170.00µs
serialize: 42.00µs
try_from_slice: 32.00µs
preparation_step::preparation::prepare: 23.80ms
air::preparation_step::preparation::make_exec_ctx: 38.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 23.69ms
runner::execute: 36.00µs
runner::farewell: 224.00µs
from_success_result: 205.00µs
populate_outcome_from_contexts: 169.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 22.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air_interpreter_data::interpreter_data::serialize: 16.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
signing_step::sign_produced_cids: 69.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
verification_step::verify: 35.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
parser-air-100mb (637.20ms; 68.500 MiB, 68.500 MiB): multiple calls parser benchmark
air::runner::execute_air: 637.20ms
preparation_step::preparation::parse_data: 176.00µs
serialize: 42.00µs
try_from_slice: 36.00µs
preparation_step::preparation::prepare: 607.00ms
air::preparation_step::preparation::make_exec_ctx: 47.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 606.80ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::execute: 46.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::farewell: 240.00µs
from_success_result: 221.00µs
populate_outcome_from_contexts: 180.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 23.00µs
air_interpreter_data::interpreter_data::serialize: 20.00µs
signing_step::sign_produced_cids: 76.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verification_step::verify: 36.00µs
verify: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
parser-calls-10000-100 (23.81ms; 12.375 MiB, 12.375 MiB): multiple calls parser benchmark
air::runner::execute_air: 23.81ms
preparation_step::preparation::parse_data: 169.00µs
serialize: 39.00µs
try_from_slice: 33.00µs
preparation_step::preparation::prepare: 22.03ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 40.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 21.91ms
runner::execute: 34.00µs
runner::farewell: 223.00µs
from_success_result: 204.00µs
populate_outcome_from_contexts: 167.00µs
feat(data)!: Rkyv for `InterprerterData` (#783) * Refactor out the `InterpreterDataEnvelope` It is an envelope for the data that makes `version` info accessible in standard non-changing way. Inner data in `InterpreterDataEnv` is a binary blob. * Use `rkyv` for `InterpreterData` * `InterpreterDataEnvelope` uses MsgPack directly It will be changed when `interpreter-sede` will support types with serde borrows.
2024-01-09 21:22:11 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 15.00µs
signing_step::sign_produced_cids: 68.00µs
verification_step::verify: 38.00µs
verify: 10.00µs
populate-map-multiple-keys (3.28ms; 11.062 MiB, 11.062 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.28ms
preparation_step::preparation::parse_data: 199.00µs
serialize: 32.00µs
try_from_slice: 77.00µs
preparation_step::preparation::prepare: 181.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::preparation_step::preparation::make_exec_ctx: 40.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
CallResultsRepr.deserialize: 9.00µs
air_parser::parser::air_parser::parse: 58.00µs
runner::execute: 2.12ms
runner::farewell: 304.00µs
from_success_result: 285.00µs
populate_outcome_from_contexts: 247.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
air_interpreter_data::interpreter_data::serialize: 64.00µs
signing_step::sign_produced_cids: 62.00µs
verification_step::verify: 269.00µs
verify: 36.00µs
populate-map-single-key (2.55ms; 11.000 MiB, 11.000 MiB): benchmarking a map insert operation
air::runner::execute_air: 2.55ms
preparation_step::preparation::parse_data: 199.00µs
serialize: 33.00µs
try_from_slice: 77.00µs
preparation_step::preparation::prepare: 182.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
CallResultsRepr.deserialize: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 57.00µs
runner::execute: 1.36ms
runner::farewell: 309.00µs
from_success_result: 290.00µs
populate_outcome_from_contexts: 233.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 20.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 57.00µs
signing_step::sign_produced_cids: 63.00µs
verification_step::verify: 284.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 54.00µs
feat(aquavm-air)!: signature checking (#607)
2023-10-13 23:19:02 +04:00
Machine e536f8eaae8c978493a773ba566ae3393e2e6240d6ea8e05b5ca1b8f77e9c441:
Platform: Linux-5.15.0-76-generic-x86_64-with-glibc2.29
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
Timestamp: 2024-02-04 13:57:37.754749+00:00
AquaVM version: 0.59.0
feat(aquavm-air)!: signature checking (#607)
2023-10-13 23:19:02 +04:00
Benches:
Features: check_signatures,gen_signatures
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
big-values-data (2.85ms; 14.250 MiB, 14.250 MiB): Loading a trace with huge values
air::runner::execute_air: 2.85ms
preparation_step::preparation::parse_data: 820.00µs
serialize: 19.00µs
try_from_slice: 714.00µs
preparation_step::preparation::prepare: 164.00µs
air::preparation_step::preparation::make_exec_ctx: 42.00µs
CallResultsRepr.deserialize: 10.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
air_parser::parser::air_parser::parse: 20.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::execute: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::farewell: 652.00µs
from_success_result: 631.00µs
populate_outcome_from_contexts: 596.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 74.00µs
air_interpreter_data::interpreter_data::serialize: 364.00µs
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 1.00ms
verify: 720.00µs
call-requests500 (22.00ms; 15.375 MiB, 15.375 MiB): multiple call requests
air::runner::execute_air: 22.00ms
preparation_step::preparation::parse_data: 154.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 16.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 56.00µs
preparation_step::preparation::prepare: 198.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
CallResultsRepr.deserialize: 14.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 50.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 19.93ms
runner::farewell: 1.41ms
from_success_result: 1.39ms
populate_outcome_from_contexts: 1.27ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 1.03ms
air::farewell_step::outcome::InterpreterDataEnv::serialize: 21.00µs
air_interpreter_data::interpreter_data::serialize: 57.00µs
signing_step::sign_produced_cids: 85.00µs
verification_step::verify: 83.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verify: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
call-result-100mb (319.90ms; 538.375 MiB, 538.375 MiB): Memory intensive benchmarking test
air::runner::execute_air: 319.90ms
preparation_step::preparation::parse_data: 76.47ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 17.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 76.34ms
preparation_step::preparation::prepare: 185.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 41.00µs
runner::execute: 84.71ms
runner::farewell: 81.94ms
from_success_result: 81.92ms
populate_outcome_from_contexts: 81.88ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 16.44ms
air_interpreter_data::interpreter_data::serialize: 65.18ms
signing_step::sign_produced_cids: 94.00µs
verification_step::verify: 76.46ms
verify: 76.12ms
call-results500 (17.55ms; 12.438 MiB, 12.438 MiB): multiple call results
air::runner::execute_air: 17.55ms
preparation_step::preparation::parse_data: 210.00µs
serialize: 15.00µs
try_from_slice: 116.00µs
preparation_step::preparation::prepare: 342.00µs
air::preparation_step::preparation::make_exec_ctx: 186.00µs
CallResultsRepr.deserialize: 158.00µs
air_parser::parser::air_parser::parse: 50.00µs
runner::execute: 14.95ms
runner::farewell: 1.48ms
from_success_result: 1.45ms
populate_outcome_from_contexts: 1.05ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 91.00µs
air_interpreter_data::interpreter_data::serialize: 473.00µs
signing_step::sign_produced_cids: 337.00µs
verification_step::verify: 84.00µs
verify: 9.00µs
canon-map-100mb (849.10ms; 1.264 GiB, 1.264 GiB): Memory intensive benchmarking test with canon map
air::runner::execute_air: 849.10ms
preparation_step::preparation::parse_data: 75.31ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 17.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 75.17ms
preparation_step::preparation::prepare: 194.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 49.00µs
runner::execute: 486.00ms
runner::farewell: 210.90ms
from_success_result: 210.90ms
populate_outcome_from_contexts: 210.90ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 22.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 39.78ms
air_interpreter_data::interpreter_data::serialize: 170.70ms
signing_step::sign_produced_cids: 97.00µs
verification_step::verify: 76.21ms
verify: 75.88ms
canon-map-key-by-lens (10.81ms; 13.312 MiB, 13.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 10.81ms
preparation_step::preparation::parse_data: 2.16ms
serialize: 19.00µs
try_from_slice: 2.05ms
preparation_step::preparation::prepare: 476.00µs
air::preparation_step::preparation::make_exec_ctx: 312.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 58.00µs
runner::execute: 2.86ms
runner::farewell: 1.55ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
from_success_result: 1.52ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 1.21ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 111.00µs
air_interpreter_data::interpreter_data::serialize: 751.00µs
signing_step::sign_produced_cids: 82.00µs
verification_step::verify: 3.55ms
verify: 3.28ms
canon-map-key-element-by-lens (10.64ms; 13.312 MiB, 13.312 MiB): benchmarking a map insert operation
air::runner::execute_air: 10.64ms
preparation_step::preparation::parse_data: 2.13ms
serialize: 16.00µs
try_from_slice: 2.03ms
preparation_step::preparation::prepare: 464.00µs
air::preparation_step::preparation::make_exec_ctx: 303.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 59.00µs
runner::execute: 2.83ms
runner::farewell: 1.50ms
from_success_result: 1.48ms
populate_outcome_from_contexts: 1.18ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 107.00µs
air_interpreter_data::interpreter_data::serialize: 727.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 3.51ms
verify: 3.24ms
canon-map-multiple-keys (10.54ms; 12.562 MiB, 12.562 MiB): benchmarking a map insert operation
air::runner::execute_air: 10.54ms
preparation_step::preparation::parse_data: 206.00µs
serialize: 17.00µs
try_from_slice: 104.00µs
preparation_step::preparation::prepare: 187.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 48.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 8.18ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
runner::farewell: 1.44ms
from_success_result: 1.42ms
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
populate_outcome_from_contexts: 1.11ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 69.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 715.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 299.00µs
verify: 26.00µs
canon-map-scalar-multiple-keys (4.37ms; 11.125 MiB, 11.125 MiB): benchmarking a map insert operation
air::runner::execute_air: 4.37ms
preparation_step::preparation::parse_data: 208.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 18.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 108.00µs
preparation_step::preparation::prepare: 189.00µs
air::preparation_step::preparation::make_exec_ctx: 40.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 47.00µs
runner::execute: 3.09ms
runner::farewell: 372.00µs
from_success_result: 350.00µs
populate_outcome_from_contexts: 313.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 19.00µs
air_interpreter_data::interpreter_data::serialize: 44.00µs
signing_step::sign_produced_cids: 79.00µs
verification_step::verify: 300.00µs
verify: 26.00µs
canon-map-scalar-single-key (3.51ms; 11.062 MiB, 11.062 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.51ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
preparation_step::preparation::parse_data: 196.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
serialize: 18.00µs
try_from_slice: 96.00µs
preparation_step::preparation::prepare: 184.00µs
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 44.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 2.25ms
runner::farewell: 373.00µs
from_success_result: 352.00µs
populate_outcome_from_contexts: 301.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 19.00µs
air_interpreter_data::interpreter_data::serialize: 52.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 306.00µs
verify: 34.00µs
canon-map-single-key (8.74ms; 12.438 MiB, 12.438 MiB): benchmarking a map insert operation
air::runner::execute_air: 8.74ms
preparation_step::preparation::parse_data: 199.00µs
serialize: 17.00µs
try_from_slice: 100.00µs
preparation_step::preparation::prepare: 189.00µs
air::preparation_step::preparation::make_exec_ctx: 40.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 45.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 6.42ms
runner::farewell: 1.40ms
from_success_result: 1.38ms
populate_outcome_from_contexts: 1.13ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 79.00µs
air_interpreter_data::interpreter_data::serialize: 749.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 321.00µs
verify: 35.00µs
dashboard (4.83ms; 10.688 MiB, 10.688 MiB): big dashboard test
air::runner::execute_air: 4.83ms
preparation_step::preparation::parse_data: 470.00µs
try_from_slice: 392.00µs
preparation_step::preparation::prepare: 288.00µs
air::preparation_step::preparation::make_exec_ctx: 59.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 127.00µs
runner::execute: 999.00µs
runner::farewell: 423.00µs
from_success_result: 402.00µs
populate_outcome_from_contexts: 357.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 22.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 32.00µs
air_interpreter_data::interpreter_data::serialize: 102.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 2.44ms
verify: 163.00µs
hybrid-100mb (1.43s; 1.975 GiB, 1.975 GiB): Memory intensive benchmarking test with mixed workload
air::runner::execute_air: 1.43s
preparation_step::preparation::parse_data: 75.89ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 16.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 75.72ms
preparation_step::preparation::prepare: 199.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 56.00µs
runner::execute: 898.60ms
runner::farewell: 378.30ms
from_success_result: 378.30ms
populate_outcome_from_contexts: 378.30ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 142.60ms
air_interpreter_data::interpreter_data::serialize: 235.30ms
signing_step::sign_produced_cids: 93.00µs
verification_step::verify: 71.72ms
verify: 71.39ms
lense-100mb (792.20ms; 1.166 GiB, 1.166 GiB): Memory intensive benchmarking test with lense
air::runner::execute_air: 792.20ms
preparation_step::preparation::parse_data: 76.47ms
serialize: 18.00µs
try_from_slice: 76.31ms
preparation_step::preparation::prepare: 198.00µs
air::preparation_step::preparation::make_exec_ctx: 41.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 53.00µs
runner::execute: 434.10ms
runner::farewell: 208.50ms
from_success_result: 208.50ms
populate_outcome_from_contexts: 208.50ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 15.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 42.97ms
air_interpreter_data::interpreter_data::serialize: 165.30ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
signing_step::sign_produced_cids: 96.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
verification_step::verify: 72.51ms
verify: 72.19ms
long-data (3.02ms; 11.188 MiB, 11.188 MiB): Long data trace
air::runner::execute_air: 3.02ms
preparation_step::preparation::parse_data: 858.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 17.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 760.00µs
preparation_step::preparation::prepare: 180.00µs
air::preparation_step::preparation::make_exec_ctx: 61.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 19.00µs
runner::execute: 9.00µs
runner::farewell: 382.00µs
from_success_result: 360.00µs
populate_outcome_from_contexts: 326.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 36.00µs
air_interpreter_data::interpreter_data::serialize: 81.00µs
signing_step::sign_produced_cids: 75.00µs
verification_step::verify: 1.40ms
verify: 344.00µs
map-100mb (839.50ms; 1.264 GiB, 1.264 GiB): Memory intensive benchmarking test with map 2 scalar
air::runner::execute_air: 839.50ms
preparation_step::preparation::parse_data: 75.59ms
serialize: 19.00µs
try_from_slice: 75.45ms
preparation_step::preparation::prepare: 196.00µs
air::preparation_step::preparation::make_exec_ctx: 42.00µs
feat(data)!: flexible serialization formats (#757) New crate air_interpreter_sede introduces a flexible serialization and deserialization infrastructure. Low level API: the Format trait and related. It includes simple and universal mechanisms for serializing any possible (e.g. implementing the Serde traits) value. High level API: Representation trait and related. It allows declaring representation types that can serialize and deserialize only certain types (for example, InterpreterDataRepr can serialize only the InterpreterData, but deserialize InterpreterData and Versions` types), producing newtype values as serialization results. The serialized representation of CallResults now contains byte arrays, not strings, because the new infrastructure serializes to byte arrays only. Also, the basic support for multicodecs is added.
2023-12-15 18:23:09 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 48.00µs
runner::execute: 477.40ms
runner::farewell: 210.00ms
from_success_result: 210.00ms
populate_outcome_from_contexts: 210.00ms
air::farewell_step::outcome::CallRequestsRepr.serialize: 19.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 39.89ms
air_interpreter_data::interpreter_data::serialize: 170.00ms
signing_step::sign_produced_cids: 97.00µs
verification_step::verify: 76.06ms
verify: 75.72ms
multiple-cids10 (2.36ms; 10.500 MiB, 10.500 MiB): verifying multiple CIDs for single peer
air::runner::execute_air: 2.36ms
preparation_step::preparation::parse_data: 308.00µs
try_from_slice: 232.00µs
preparation_step::preparation::prepare: 198.00µs
air::preparation_step::preparation::make_exec_ctx: 51.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 45.00µs
runner::execute: 496.00µs
runner::farewell: 362.00µs
from_success_result: 342.00µs
populate_outcome_from_contexts: 288.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 27.00µs
air_interpreter_data::interpreter_data::serialize: 86.00µs
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 796.00µs
verify: 210.00µs
multiple-peers8 (8.89ms; 11.438 MiB, 11.438 MiB): verifying many CIDs for many peers
air::runner::execute_air: 8.89ms
preparation_step::preparation::parse_data: 1.01ms
try_from_slice: 934.00µs
preparation_step::preparation::prepare: 261.00µs
air::preparation_step::preparation::make_exec_ctx: 110.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 50.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 3.17ms
runner::farewell: 765.00µs
from_success_result: 744.00µs
populate_outcome_from_contexts: 633.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 46.00µs
air_interpreter_data::interpreter_data::serialize: 346.00µs
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 3.48ms
verify: 931.00µs
multiple-sigs30 (18.96ms; 13.812 MiB, 13.875 MiB): signing multiple CIDs
air::runner::execute_air: 18.96ms
preparation_step::preparation::parse_data: 3.19ms
try_from_slice: 3.10ms
preparation_step::preparation::prepare: 400.00µs
air::preparation_step::preparation::make_exec_ctx: 243.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 51.00µs
runner::execute: 9.03ms
runner::farewell: 2.29ms
from_success_result: 2.27ms
populate_outcome_from_contexts: 2.11ms
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air::farewell_step::outcome::InterpreterDataEnv::serialize: 157.00µs
air_interpreter_data::interpreter_data::serialize: 1.07ms
signing_step::sign_produced_cids: 508.00µs
verification_step::verify: 3.40ms
verify: 1.60ms
network-explore (2.49ms; 10.375 MiB, 10.375 MiB): 5 peers of network are discovered
air::runner::execute_air: 2.49ms
preparation_step::preparation::parse_data: 211.00µs
try_from_slice: 131.00µs
preparation_step::preparation::prepare: 217.00µs
air::preparation_step::preparation::make_exec_ctx: 44.00µs
CallResultsRepr.deserialize: 10.00µs
air_parser::parser::air_parser::parse: 70.00µs
runner::execute: 165.00µs
runner::farewell: 276.00µs
from_success_result: 255.00µs
populate_outcome_from_contexts: 214.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 17.00µs
air_interpreter_data::interpreter_data::serialize: 35.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 1.41ms
verify: 56.00µs
null (780.00µs; 10.375 MiB, 10.375 MiB): Empty data and null script
air::runner::execute_air: 780.00µs
preparation_step::preparation::parse_data: 139.00µs
serialize: 28.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
try_from_slice: 31.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
preparation_step::preparation::prepare: 168.00µs
air::preparation_step::preparation::make_exec_ctx: 37.00µs
CallResultsRepr.deserialize: 10.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
air_parser::parser::air_parser::parse: 19.00µs
chore(benchmarking): data generators for a set of map-related benchmarks [fixes VM-345] (#735)
2023-11-08 16:22:17 +03:00
runner::execute: 9.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::farewell: 236.00µs
from_success_result: 216.00µs
populate_outcome_from_contexts: 182.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 18.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 16.00µs
signing_step::sign_produced_cids: 80.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
verification_step::verify: 32.00µs
chore(benchmark): restore parser-10000-100 bench (#762) A benchmark with empty datas that has long AIR code with lot of variable (re-)assignments.
2023-11-30 17:33:41 +04:00
verify: 10.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
parser-10000-100 (29.45ms; 12.625 MiB, 12.625 MiB): long air script with lot of variable assignments
air::runner::execute_air: 29.45ms
preparation_step::preparation::parse_data: 135.00µs
serialize: 27.00µs
try_from_slice: 30.00µs
preparation_step::preparation::prepare: 28.15ms
air::preparation_step::preparation::make_exec_ctx: 39.00µs
CallResultsRepr.deserialize: 11.00µs
air_parser::parser::air_parser::parse: 27.98ms
runner::execute: 26.00µs
runner::farewell: 237.00µs
from_success_result: 216.00µs
populate_outcome_from_contexts: 182.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air::farewell_step::outcome::CallRequestsRepr.serialize: 13.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 18.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_interpreter_data::interpreter_data::serialize: 18.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 31.00µs
verify: 9.00µs
parser-air-100mb (692.60ms; 68.500 MiB, 68.500 MiB): multiple calls parser benchmark
air::runner::execute_air: 692.60ms
preparation_step::preparation::parse_data: 137.00µs
serialize: 28.00µs
try_from_slice: 33.00µs
preparation_step::preparation::prepare: 663.20ms
air::preparation_step::preparation::make_exec_ctx: 50.00µs
CallResultsRepr.deserialize: 14.00µs
air_parser::parser::air_parser::parse: 662.80ms
runner::execute: 66.00µs
runner::farewell: 293.00µs
from_success_result: 272.00µs
populate_outcome_from_contexts: 221.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 14.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 24.00µs
air_interpreter_data::interpreter_data::serialize: 32.00µs
signing_step::sign_produced_cids: 92.00µs
verification_step::verify: 30.00µs
verify: 9.00µs
parser-calls-10000-100 (25.19ms; 12.375 MiB, 12.375 MiB): multiple calls parser benchmark
air::runner::execute_air: 25.19ms
preparation_step::preparation::parse_data: 135.00µs
serialize: 27.00µs
try_from_slice: 30.00µs
preparation_step::preparation::prepare: 23.90ms
air::preparation_step::preparation::make_exec_ctx: 40.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
CallResultsRepr.deserialize: 11.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
air_parser::parser::air_parser::parse: 23.76ms
runner::execute: 27.00µs
runner::farewell: 235.00µs
from_success_result: 215.00µs
populate_outcome_from_contexts: 182.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 17.00µs
air_interpreter_data::interpreter_data::serialize: 18.00µs
signing_step::sign_produced_cids: 80.00µs
verification_step::verify: 31.00µs
verify: 9.00µs
populate-map-multiple-keys (3.75ms; 11.000 MiB, 11.000 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.75ms
preparation_step::preparation::parse_data: 157.00µs
serialize: 16.00µs
try_from_slice: 65.00µs
preparation_step::preparation::prepare: 186.00µs
air::preparation_step::preparation::make_exec_ctx: 38.00µs
CallResultsRepr.deserialize: 10.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
air_parser::parser::air_parser::parse: 49.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 2.61ms
runner::farewell: 299.00µs
from_success_result: 279.00µs
populate_outcome_from_contexts: 244.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 18.00µs
air_interpreter_data::interpreter_data::serialize: 48.00µs
signing_step::sign_produced_cids: 78.00µs
verification_step::verify: 294.00µs
verify: 24.00µs
populate-map-single-key (3.04ms; 11.000 MiB, 11.000 MiB): benchmarking a map insert operation
air::runner::execute_air: 3.04ms
preparation_step::preparation::parse_data: 161.00µs
chore(bench): re-run on MacOS arm64 and Linux x64 (#798)
2024-01-15 18:56:01 +04:00
serialize: 17.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
try_from_slice: 66.00µs
preparation_step::preparation::prepare: 188.00µs
air::preparation_step::preparation::make_exec_ctx: 40.00µs
CallResultsRepr.deserialize: 10.00µs
feat(interface)!: Use MessagePack for calls (#780) Top-level structs use multicodec-prefixed MessagePack, the nested structures (arguments, tetraplets) use just ordinary MessagePack. * JS-compatible `CallResults` Binary format implementations like `rmp-serde` do not bother converting keys from strings, unlike `serde_json`. So, we use `CallResults` with string keys, as JS client cannot produce anything else. --------- Co-authored-by: Mike Voronov <michail.vms@gmail.com>
2024-01-08 15:01:58 +04:00
air_parser::parser::air_parser::parse: 47.00µs
chore(performance): use `fluence-blake3` with wasm32 SIMD support (#806) * chore(preformance): use fluence-blake3 Enable wasm32 SIMD on the appropriate target. It gives a noticeable performance improvement. The smaller memory size on benchmarks is due to unrelated stack size reduction.
2024-02-04 18:27:49 +04:00
runner::execute: 1.87ms
runner::farewell: 310.00µs
from_success_result: 289.00µs
populate_outcome_from_contexts: 241.00µs
air::farewell_step::outcome::CallRequestsRepr.serialize: 12.00µs
air::farewell_step::outcome::InterpreterDataEnv::serialize: 19.00µs
air_interpreter_data::interpreter_data::serialize: 54.00µs
signing_step::sign_produced_cids: 79.00µs
verification_step::verify: 305.00µs
verify: 34.00µs
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