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Add nd add benchmarks

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This commit is contained in:
Alexander Nozik 2021-10-06 12:25:32 +03:00
parent d9f36365d9
commit 30e3e80397
6 changed files with 55 additions and 22 deletions
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6
benchmarks/build.gradle.kts
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@ -36,6 +36,7 @@ kotlin {
implementation(project(":kmath-dimensions"))
implementation(project(":kmath-for-real"))
implementation(project(":kmath-jafama"))
implementation(project(":kmath-tensors"))
implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.1")
}
}
@ -81,6 +82,11 @@ benchmark {
include("BufferBenchmark")
}
configurations.register("nd") {
commonConfiguration()
include("NDFieldBenchmark")
}
configurations.register("dot") {
commonConfiguration()
include("DotBenchmark")

37
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt
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@ -12,44 +12,63 @@ import kotlinx.benchmark.State
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.autoNdAlgebra
import space.kscience.kmath.nd.ndAlgebra
import space.kscience.kmath.nd4j.nd4j
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.tensors.core.DoubleTensor
import space.kscience.kmath.tensors.core.ones
import space.kscience.kmath.tensors.core.tensorAlgebra
@State(Scope.Benchmark)
internal class NDFieldBenchmark {
@Benchmark
fun autoFieldAdd(blackhole: Blackhole) {
with(autoField) {
fun autoFieldAdd(blackhole: Blackhole) = with(autoField) {
var res: StructureND<Double> = one
repeat(n) { res += one }
blackhole.consume(res)
}
}
@Benchmark
fun specializedFieldAdd(blackhole: Blackhole) {
with(specializedField) {
fun specializedFieldAdd(blackhole: Blackhole) = with(specializedField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
@Benchmark
fun boxingFieldAdd(blackhole: Blackhole) {
with(genericField) {
fun boxingFieldAdd(blackhole: Blackhole) = with(genericField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
@Benchmark
fun tensorAdd(blackhole: Blackhole) = with(Double.tensorAlgebra) {
var res: DoubleTensor = ones(dim, dim)
repeat(n) { res = res + 1.0 }
blackhole.consume(res)
}
@Benchmark
fun tensorInPlaceAdd(blackhole: Blackhole) = with(Double.tensorAlgebra) {
val res: DoubleTensor = ones(dim, dim)
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
// @Benchmark
// fun nd4jAdd(blackhole: Blackhole) = with(nd4jField) {
// var res: StructureND<Double> = one
// repeat(n) { res += 1.0 }
// blackhole.consume(res)
// }
private companion object {
private const val dim = 1000
private const val n = 100
private val autoField = DoubleField.autoNdAlgebra(dim, dim)
private val specializedField = DoubleField.ndAlgebra(dim, dim)
private val genericField = DoubleField.ndAlgebra(Buffer.Companion::boxing, dim, dim)
private val nd4jField = DoubleField.nd4j(dim, dim)
}
}

2
kmath-nd4j/build.gradle.kts
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@ -9,7 +9,7 @@ dependencies {
api(project(":kmath-tensors"))
api("org.nd4j:nd4j-api:1.0.0-M1")
testImplementation("org.nd4j:nd4j-native-platform:1.0.0-M1")
testImplementation("org.slf4j:slf4j-simple:1.7.31")
testImplementation("org.slf4j:slf4j-simple:1.7.32")
}
readme {

3
kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt
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@ -45,7 +45,6 @@ public sealed interface Nd4jArrayAlgebra<T, out C : Algebra<T>> : AlgebraND<T, C
return struct
}
@PerformancePitfall
override fun StructureND<T>.map(transform: C.(T) -> T): Nd4jArrayStructure<T> {
val newStruct = ndArray.dup().wrap()
newStruct.elements().forEach { (idx, value) -> newStruct[idx] = elementContext.transform(value) }
@ -265,6 +264,8 @@ public class DoubleNd4jArrayField(override val shape: IntArray) : Nd4jArrayExten
}
}
public fun DoubleField.nd4j(vararg shape: Int): DoubleNd4jArrayField = DoubleNd4jArrayField(intArrayOf(*shape))
/**
* Represents [FieldND] over [Nd4jArrayStructure] of [Float].
*/

1
kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt
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@ -158,7 +158,6 @@ public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra<Double> {
if (shape contentEquals intArrayOf(1)) ndArray.getDouble(0) else null
// TODO rewrite
@PerformancePitfall
override fun diagonalEmbedding(
diagonalEntries: Tensor<Double>,
offset: Int,

8
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorAlgebraExtensions.kt Normal file
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@ -0,0 +1,8 @@
/*
* 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.tensors.core
public fun DoubleTensorAlgebra.ones(vararg shape: Int): DoubleTensor = ones(intArrayOf(*shape))