Adjust benchmarks.

This commit is contained in:
Alexander Nozik 2021-09-22 22:09:46 +03:00
parent 89eebbecb7
commit 974d73e25c
3 changed files with 77 additions and 30 deletions

View File

@ -11,7 +11,10 @@ import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State import org.openjdk.jmh.annotations.State
import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.* import space.kscience.kmath.operations.BigIntField
import space.kscience.kmath.operations.JBigIntegerField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.operations.parseBigInteger
import java.math.BigInteger import java.math.BigInteger
@ -19,12 +22,24 @@ import java.math.BigInteger
@State(Scope.Benchmark) @State(Scope.Benchmark)
internal class BigIntBenchmark { internal class BigIntBenchmark {
val kmSmallNumber = BigIntField.number(100)
val jvmSmallNumber = JBigIntegerField.number(100)
val kmNumber = BigIntField.number(Int.MAX_VALUE) val kmNumber = BigIntField.number(Int.MAX_VALUE)
val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE) val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE)
val largeKmNumber = BigIntField { number(11).pow(100_000U) } val kmLargeNumber = BigIntField { number(11).pow(100_000U) }
val largeJvmNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) } val jvmLargeNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) }
val bigExponent = 50_000 val bigExponent = 50_000
@Benchmark
fun kmSmallAdd(blackhole: Blackhole) = BigIntField {
blackhole.consume(kmSmallNumber + kmSmallNumber + kmSmallNumber)
}
@Benchmark
fun jvmSmallAdd(blackhole: Blackhole) = JBigIntegerField {
blackhole.consume(jvmSmallNumber + jvmSmallNumber + jvmSmallNumber)
}
@Benchmark @Benchmark
fun kmAdd(blackhole: Blackhole) = BigIntField { fun kmAdd(blackhole: Blackhole) = BigIntField {
blackhole.consume(kmNumber + kmNumber + kmNumber) blackhole.consume(kmNumber + kmNumber + kmNumber)
@ -37,12 +52,12 @@ internal class BigIntBenchmark {
@Benchmark @Benchmark
fun kmAddLarge(blackhole: Blackhole) = BigIntField { fun kmAddLarge(blackhole: Blackhole) = BigIntField {
blackhole.consume(largeKmNumber + largeKmNumber + largeKmNumber) blackhole.consume(kmLargeNumber + kmLargeNumber + kmLargeNumber)
} }
@Benchmark @Benchmark
fun jvmAddLarge(blackhole: Blackhole) = JBigIntegerField { fun jvmAddLarge(blackhole: Blackhole) = JBigIntegerField {
blackhole.consume(largeJvmNumber + largeJvmNumber + largeJvmNumber) blackhole.consume(jvmLargeNumber + jvmLargeNumber + jvmLargeNumber)
} }
@Benchmark @Benchmark
@ -52,7 +67,7 @@ internal class BigIntBenchmark {
@Benchmark @Benchmark
fun kmMultiplyLarge(blackhole: Blackhole) = BigIntField { fun kmMultiplyLarge(blackhole: Blackhole) = BigIntField {
blackhole.consume(largeKmNumber*largeKmNumber) blackhole.consume(kmLargeNumber*kmLargeNumber)
} }
@Benchmark @Benchmark
@ -62,7 +77,7 @@ internal class BigIntBenchmark {
@Benchmark @Benchmark
fun jvmMultiplyLarge(blackhole: Blackhole) = JBigIntegerField { fun jvmMultiplyLarge(blackhole: Blackhole) = JBigIntegerField {
blackhole.consume(largeJvmNumber*largeJvmNumber) blackhole.consume(jvmLargeNumber*jvmLargeNumber)
} }
@Benchmark @Benchmark

View File

@ -11,7 +11,6 @@ import kotlinx.benchmark.Scope
import kotlinx.benchmark.State import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMLinearSpace import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.invoke import space.kscience.kmath.linear.invoke
import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.linearSpace
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
@ -26,8 +25,12 @@ internal class DotBenchmark {
const val dim = 1000 const val dim = 1000
//creating invertible matrix //creating invertible matrix
val matrix1 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } val matrix1 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j ->
val matrix2 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } if (i <= j) random.nextDouble() else 0.0
}
val matrix2 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j ->
if (i <= j) random.nextDouble() else 0.0
}
val cmMatrix1 = CMLinearSpace { matrix1.toCM() } val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
val cmMatrix2 = CMLinearSpace { matrix2.toCM() } val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
@ -37,37 +40,32 @@ internal class DotBenchmark {
} }
@Benchmark @Benchmark
fun cmDot(blackhole: Blackhole) { fun cmDotWithConversion(blackhole: Blackhole) = CMLinearSpace {
CMLinearSpace { blackhole.consume(matrix1 dot matrix2)
blackhole.consume(cmMatrix1 dot cmMatrix2)
}
} }
@Benchmark @Benchmark
fun ejmlDot(blackhole: Blackhole) { fun cmDot(blackhole: Blackhole) = CMLinearSpace {
EjmlLinearSpaceDDRM { blackhole.consume(cmMatrix1 dot cmMatrix2)
blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
}
} }
@Benchmark @Benchmark
fun ejmlDotWithConversion(blackhole: Blackhole) { fun ejmlDot(blackhole: Blackhole) = EjmlLinearSpaceDDRM {
EjmlLinearSpaceDDRM { blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
blackhole.consume(matrix1 dot matrix2)
}
} }
@Benchmark @Benchmark
fun bufferedDot(blackhole: Blackhole) { fun ejmlDotWithConversion(blackhole: Blackhole) = EjmlLinearSpaceDDRM {
with(DoubleField.linearSpace(Buffer.Companion::auto)) { blackhole.consume(matrix1 dot matrix2)
blackhole.consume(matrix1 dot matrix2)
}
} }
@Benchmark @Benchmark
fun doubleDot(blackhole: Blackhole) { fun bufferedDot(blackhole: Blackhole) = with(DoubleField.linearSpace(Buffer.Companion::auto)) {
with(Double.algebra.linearSpace) { blackhole.consume(matrix1 dot matrix2)
blackhole.consume(matrix1 dot matrix2) }
}
@Benchmark
fun doubleDot(blackhole: Blackhole) = with(Double.algebra.linearSpace) {
blackhole.consume(matrix1 dot matrix2)
} }
} }

View File

@ -0,0 +1,34 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
*/
package space.kscience.kmath.linear
import space.kscience.kmath.operations.algebra
import kotlin.random.Random
import kotlin.system.measureTimeMillis
fun main() {
val random = Random(12224)
val dim = 1000
//creating invertible matrix
val matrix1 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j ->
if (i <= j) random.nextDouble() else 0.0
}
val matrix2 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j ->
if (i <= j) random.nextDouble() else 0.0
}
val time = measureTimeMillis {
with(Double.algebra.linearSpace) {
repeat(10) {
val res = matrix1 dot matrix2
}
}
}
println(time)
}