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BENCHMARKING.md

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Running JMH Benchmarks in Besu

Besu includes JMH microbenchmarks for performance testing. This guide explains how to build and run them using Gradle.

🛠️ Prerequisites

  • Java 21+ (ensure JAVA_HOME is set)
  • Gradle (you can use the wrapper: ./gradlew)
  • Optional: Async Profiler for low-overhead profiling

🏃 Running Benchmarks

JMH tasks are defined in various modules such as ethereum:core, ethereum:eth, and ethereum:rlp.

▶️ Run All Benchmarks

./gradlew :ethereum:core:jmh

This runs all available benchmarks in the core module using default settings.

Gradle won't rerun a task by default with no changes, so to run subsequent times without changes add the gradle --rerun-tasks option.

🔁 Rerun All Benchmarks

./gradlew :ethereum:core:jmh --rerun-tasks

🎯 Filter Benchmarks by Name

To run a specific benchmark class, use the -Pincludes and/or -Pexcludes project properties:

./gradlew :ethereum:core:jmh -Pincludes=SomeBenchmark -Pexcludes=TransientStorage,BlockHash

This uses a regex pattern so other kinds of regexes can be used.

⚙️ Benchmark Configuration Options

For other configuration options run:

./gradlew help --task jmh

🔥 Async Profiler Integration (Optional)

To profile benchmarks with Async Profiler:

./gradlew :ethereum:core:jmh \
  -Pincludes=SomeBenchmark \
  -PasyncProfiler=/path/to/libasyncProfiler.so \
  -PasyncProfilerOptions="output=flamegraph"

This will generate two html profiling files flame-cpu-forward.html and flame-cpu-reverse.html after the benchmark run.

🧪 Sample Output

Benchmark                                Mode  Cnt  Score   Error  Units
SomeBenchmark.benchmark                  avgt   20  3.893 ± 0.021  ns/op
SomeBenchmark.benchmark                  avgt   20  8.951 ± 0.149  ns/op

📚 References