perf(benchmark): add executor-aware metrics, automated benchmarking pipeline, and performance report#1533
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neetance wants to merge 1 commit intohyperledger-labs:mainfrom
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Hi @neetance , great effort. I really appreciate. Thanks a lot 🙏 |
…d comparison plots Signed-off-by: Ankit Basu <ankitbasu14@gmail.com>
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Summary
Extends the benchmarking framework to support executor-aware analysis and improves visibility into system behavior under different execution strategies.
Changes
run_benchmarks.py:
all three executor strategies for every parallel benchmark
so all strategies coexist in one CSV row
and stored as TestParallelBenchmarkSender[pool]/8 goroutines
plot_benchmark_results.py:
count annotations, coloured by executor strategy
runner.go:
GoRoutinesCreatedfield added to Result, captured as net delta ofruntime.NumGoroutine()across the recording windowGoroutines CreatedBenchmark Results
I ran the benchmark across the 3 different strategies with 10 workers to show the number of goroutines created and here are the results:
Serial
Pool
Unbounded
Comparison report
I have attached the pdf of the comparison report of the results of different benchmarks with different configurations
benchmark_results.pdf
Let me know if this is good 🙏