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/*
* Copyright (c) 2026 AtLarge Research
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
package org.opendc.experiments
import jdk.jfr.Configuration
import jdk.jfr.Recording
import org.openjdk.jmh.annotations.Level
import org.openjdk.jmh.annotations.Setup
import org.openjdk.jmh.annotations.TearDown
import org.openjdk.jmh.infra.BenchmarkParams
import org.openjdk.jmh.infra.IterationParams
import org.openjdk.jmh.runner.IterationType
import java.io.File
import java.nio.file.Path
import kotlin.math.sqrt
/** Computes the population standard deviation of the receiver list. */
private fun List<Double>.std(): Double {
val avg = average()
return sqrt(sumOf { (it - avg) * (it - avg) } / size)
}
/**
* Abstract base class for JMH benchmarks in OpenDC.
*
* This base class provides:
*
* **JFR profiling** — a Java Flight Recorder session using the built-in `profile`
* configuration is started before every JMH iteration and stopped afterwards.
* The recording is written to `build/bench.jfr` and overwritten each iteration,
* so only the most-recent recording is kept on disk.
*
* **Heap statistics** — after each *measurement* iteration the JFR file is processed
* to get the average and peak heap usage. At the end of the trial, per-iteration [HeapStats]
* are aggregated (mean ± std-dev). The jmh task configuration in [build.gradle.kts](../build.gradle.kts)
* is set up to merge these heap stats into the final JSON report as a
* `heapMetric` field for each benchmark entry.
*
* ### Subclassing
* Concrete benchmark classes should:
* 1. Annotate the class with the desired JMH mode/time-unit annotations. See [CIBenchmark] as example.
* 2. Implement one or more `@Benchmark` methods.
* 3. Add any extra `@Setup` / `@TearDown` methods as needed; the lifecycle callbacks
* defined here run at [Level.Iteration] and [Level.Trial] respectively.
*
* @see analyzeHeap
* @see HeapStats
*/
abstract class OpenDCBenchmark {
/** Active JFR recording for the current iteration, or `null` between iterations. */
private var recording: Recording? = null
/** Destination path for the JFR file; overwritten on every iteration. */
private val jfrPath = Path.of("build/bench.jfr")
/** Accumulated heap statistics, one entry per completed measurement iteration. */
private val heapResults = mutableListOf<HeapStats>()
/**
* Starts a JFR recording before each iteration.
*
* Uses the JDK's built-in `profile` configuration, which captures GC heap
* summaries, CPU load, thread activity, and other standard events needed for
* heap analysis.
*/
@Setup(Level.Iteration)
fun setupIteration() {
recording = Recording(Configuration.getConfiguration("profile"))
recording!!.setDestination(jfrPath)
recording!!.start()
}
/**
* Stops the JFR recording after each iteration and, for measurement iterations,
* parses the resulting file to extract [HeapStats].
*
* Warmup iterations are skipped so that only steady-state heap behaviour is
* included in the final CSV report.
*
* @param params JMH-injected iteration metadata; used to distinguish warmup
* from measurement iterations via [IterationParams.type].
*/
@TearDown(Level.Iteration)
fun tearDownIteration(params: IterationParams) {
recording?.stop()
recording = null
if (params.type == IterationType.MEASUREMENT) {
analyzeHeap(jfrPath)?.let { heapResults.add(it) }
}
}
/**
* Aggregates heap statistics across all measurement iterations and appends a
* summary row to `build/heap-stats.csv`.
*
* The CSV columns are:
* `benchmark, avg_heap_mb, std_avg_heap_mb, max_heap_mb, std_max_heap_mb`
*
* If no measurement iterations produced heap data (e.g., the JFR file was
* empty), the method returns without writing anything.
*
* @param params JMH-injected trial metadata; provides the fully-qualified
* benchmark name used as the first CSV column.
*/
@TearDown(Level.Trial)
fun tearDownTrial(params: BenchmarkParams) {
if (heapResults.isEmpty()) return
val avgs = heapResults.map { it.avgMb }
val maxes = heapResults.map { it.maxMb }
val line =
"\"${params.benchmark}\"," +
"${"%.4f".format(avgs.average())}," +
"${"%.4f".format(avgs.std())}," +
"${"%.4f".format(maxes.average())}," +
"${"%.4f".format(maxes.std())}\n"
println(line)
val heapFile = File("build/heap-stats.csv")
heapFile.parentFile.mkdirs()
heapFile.appendText(line)
}
}
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