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Multik went MPP

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Alexander Nozik 2022-08-04 09:54:59 +03:00
parent ee0d44e12e
commit a8182fad23
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17 changed files with 100 additions and 46 deletions
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1
CHANGELOG.md
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@ -10,6 +10,7 @@
- Kotlin 1.7.20
- `LazyStructure` `deffered` -> `async` to comply with coroutines code style
- Default `dot` operation in tensor algebra no longer support broadcasting. Instead `matmul` operation is added to `DoubleTensorAlgebra`.
- Multik went MPP
### Deprecated

10
benchmarks/build.gradle.kts
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@ -1,5 +1,6 @@
@file:Suppress("UNUSED_VARIABLE")
import org.jetbrains.kotlin.gradle.tasks.KotlinJvmCompile
import space.kscience.kmath.benchmarks.addBenchmarkProperties
plugins {
@ -15,6 +16,8 @@ repositories {
mavenCentral()
}
val multikVersion: String by rootProject.extra
kotlin {
jvm()
@ -39,7 +42,9 @@ kotlin {
implementation(project(":kmath-dimensions"))
implementation(project(":kmath-for-real"))
implementation(project(":kmath-tensors"))
implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.4.2")
implementation(project(":kmath-multik"))
implementation("org.jetbrains.kotlinx:multik-default:$multikVersion")
implementation(npmlibs.kotlinx.benchmark.runtime)
}
}
@ -51,7 +56,6 @@ kotlin {
implementation(project(":kmath-kotlingrad"))
implementation(project(":kmath-viktor"))
implementation(project(":kmath-jafama"))
implementation(project(":kmath-multik"))
implementation(projects.kmath.kmathTensorflow)
implementation("org.tensorflow:tensorflow-core-platform:0.4.0")
implementation("org.nd4j:nd4j-native:1.0.0-M1")
@ -155,7 +159,7 @@ kotlin.sourceSets.all {
}
}
tasks.withType<org.jetbrains.kotlin.gradle.dsl.KotlinJvmCompile> {
tasks.withType<KotlinJvmCompile> {
kotlinOptions {
jvmTarget = "11"
freeCompilerArgs = freeCompilerArgs + "-Xjvm-default=all" + "-Xlambdas=indy"

3
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
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@ -13,7 +13,6 @@ import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
import space.kscience.kmath.linear.invoke
import space.kscience.kmath.linear.linearSpace
import space.kscience.kmath.multik.multikAlgebra
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.tensorflow.produceWithTF
@ -78,7 +77,7 @@ internal class DotBenchmark {
}
@Benchmark
fun multikDot(blackhole: Blackhole) = with(DoubleField.multikAlgebra) {
fun multikDot(blackhole: Blackhole) = with(multikAlgebra) {
blackhole.consume(matrix1 dot matrix2)
}

6
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt
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@ -13,7 +13,6 @@ import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ones
import org.jetbrains.kotlinx.multik.ndarray.data.DN
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
import space.kscience.kmath.multik.multikAlgebra
import space.kscience.kmath.nd.BufferedFieldOpsND
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.ndAlgebra
@ -43,7 +42,7 @@ internal class NDFieldBenchmark {
}
@Benchmark
fun multikAdd(blackhole: Blackhole) = with(multikField) {
fun multikAdd(blackhole: Blackhole) = with(multikAlgebra) {
var res: StructureND<Double> = one(shape)
repeat(n) { res += 1.0 }
blackhole.consume(res)
@ -71,7 +70,7 @@ internal class NDFieldBenchmark {
}
@Benchmark
fun multikInPlaceAdd(blackhole: Blackhole) = with(DoubleField.multikAlgebra) {
fun multikInPlaceAdd(blackhole: Blackhole) = with(multikAlgebra) {
val res = Multik.ones<Double, DN>(shape, DataType.DoubleDataType).wrap()
repeat(n) { res += 1.0 }
blackhole.consume(res)
@ -91,7 +90,6 @@ internal class NDFieldBenchmark {
private val specializedField = DoubleField.ndAlgebra
private val genericField = BufferedFieldOpsND(DoubleField)
private val nd4jField = DoubleField.nd4j
private val multikField = DoubleField.multikAlgebra
private val viktorField = DoubleField.viktorAlgebra
}
}

11
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/globals.kt Normal file
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@ -0,0 +1,11 @@
/*
* 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/LICENSE.txt file.
*/
package space.kscience.kmath.benchmarks
import org.jetbrains.kotlinx.multik.default.DefaultEngine
import space.kscience.kmath.multik.MultikDoubleAlgebra
val multikAlgebra = MultikDoubleAlgebra(DefaultEngine())

2
build.gradle.kts
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@ -74,3 +74,5 @@ ksciencePublish {
}
apiValidation.nonPublicMarkers.add("space.kscience.kmath.misc.UnstableKMathAPI")
val multikVersion by extra("0.2.0")

3
examples/build.gradle.kts
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@ -8,6 +8,8 @@ repositories {
maven("https://maven.pkg.jetbrains.space/kotlin/p/kotlin/kotlin-js-wrappers")
}
val multikVersion: String by rootProject.extra
dependencies {
implementation(project(":kmath-ast"))
implementation(project(":kmath-kotlingrad"))
@ -30,6 +32,7 @@ dependencies {
implementation(project(":kmath-jafama"))
//multik
implementation(project(":kmath-multik"))
implementation("org.jetbrains.kotlinx:multik-default:$multikVersion")
implementation("org.nd4j:nd4j-native:1.0.0-beta7")

9
examples/src/main/kotlin/space/kscience/kmath/tensors/multik.kt
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@ -7,11 +7,14 @@ package space.kscience.kmath.tensors
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarray
import space.kscience.kmath.multik.multikAlgebra
import org.jetbrains.kotlinx.multik.default.DefaultEngine
import space.kscience.kmath.multik.MultikDoubleAlgebra
import space.kscience.kmath.nd.one
import space.kscience.kmath.operations.DoubleField
fun main(): Unit = with(DoubleField.multikAlgebra) {
val multikAlgebra = MultikDoubleAlgebra(DefaultEngine())
fun main(): Unit = with(multikAlgebra) {
val a = Multik.ndarray(intArrayOf(1, 2, 3)).asType<Double>().wrap()
val b = Multik.ndarray(doubleArrayOf(1.0, 2.0, 3.0)).wrap()
one(a.shape) - a + b * 3.0

19
kmath-multik/build.gradle.kts
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@ -1,12 +1,25 @@
plugins {
id("space.kscience.gradle.jvm")
id("space.kscience.gradle.mpp")
}
description = "JetBrains Multik connector"
dependencies {
val multikVersion: String by rootProject.extra
kotlin{
sourceSets{
commonMain{
dependencies{
api(project(":kmath-tensors"))
api("org.jetbrains.kotlinx:multik-default:0.2.0")
api("org.jetbrains.kotlinx:multik-core:$multikVersion")
}
}
commonTest{
dependencies{
api("org.jetbrains.kotlinx:multik-default:$multikVersion")
}
}
}
}
readme {

9
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikDoubleAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikDoubleAlgebra.kt
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@ -5,6 +5,7 @@
package space.kscience.kmath.multik
import org.jetbrains.kotlinx.multik.api.Engine
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarrayOf
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
@ -14,7 +15,9 @@ import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.ExponentialOperations
import space.kscience.kmath.operations.TrigonometricOperations
public object MultikDoubleAlgebra : MultikDivisionTensorAlgebra<Double, DoubleField>(),
public class MultikDoubleAlgebra(
multikEngine: Engine
) : MultikDivisionTensorAlgebra<Double, DoubleField>(multikEngine),
TrigonometricOperations<StructureND<Double>>, ExponentialOperations<StructureND<Double>> {
override val elementAlgebra: DoubleField get() = DoubleField
override val type: DataType get() = DataType.DoubleDataType
@ -60,6 +63,6 @@ public object MultikDoubleAlgebra : MultikDivisionTensorAlgebra<Double, DoubleFi
override fun scalar(value: Double): MultikTensor<Double> = Multik.ndarrayOf(value).wrap()
}
public val Double.Companion.multikAlgebra: MultikTensorAlgebra<Double, DoubleField> get() = MultikDoubleAlgebra
public val DoubleField.multikAlgebra: MultikTensorAlgebra<Double, DoubleField> get() = MultikDoubleAlgebra
//public val Double.Companion.multikAlgebra: MultikTensorAlgebra<Double, DoubleField> get() = MultikDoubleAlgebra
//public val DoubleField.multikAlgebra: MultikTensorAlgebra<Double, DoubleField> get() = MultikDoubleAlgebra

9
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikFloatAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikFloatAlgebra.kt
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@ -5,12 +5,15 @@
package space.kscience.kmath.multik
import org.jetbrains.kotlinx.multik.api.Engine
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarrayOf
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
import space.kscience.kmath.operations.FloatField
public object MultikFloatAlgebra : MultikDivisionTensorAlgebra<Float, FloatField>() {
public class MultikFloatAlgebra(
multikEngine: Engine
) : MultikDivisionTensorAlgebra<Float, FloatField>(multikEngine) {
override val elementAlgebra: FloatField get() = FloatField
override val type: DataType get() = DataType.FloatDataType
@ -18,5 +21,5 @@ public object MultikFloatAlgebra : MultikDivisionTensorAlgebra<Float, FloatField
}
public val Float.Companion.multikAlgebra: MultikTensorAlgebra<Float, FloatField> get() = MultikFloatAlgebra
public val FloatField.multikAlgebra: MultikTensorAlgebra<Float, FloatField> get() = MultikFloatAlgebra
//public val Float.Companion.multikAlgebra: MultikTensorAlgebra<Float, FloatField> get() = MultikFloatAlgebra
//public val FloatField.multikAlgebra: MultikTensorAlgebra<Float, FloatField> get() = MultikFloatAlgebra

9
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikIntAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikIntAlgebra.kt
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@ -5,16 +5,19 @@
package space.kscience.kmath.multik
import org.jetbrains.kotlinx.multik.api.Engine
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarrayOf
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
import space.kscience.kmath.operations.IntRing
public object MultikIntAlgebra : MultikTensorAlgebra<Int, IntRing>() {
public class MultikIntAlgebra(
multikEngine: Engine
) : MultikTensorAlgebra<Int, IntRing>(multikEngine) {
override val elementAlgebra: IntRing get() = IntRing
override val type: DataType get() = DataType.IntDataType
override fun scalar(value: Int): MultikTensor<Int> = Multik.ndarrayOf(value).wrap()
}
public val Int.Companion.multikAlgebra: MultikTensorAlgebra<Int, IntRing> get() = MultikIntAlgebra
public val IntRing.multikAlgebra: MultikTensorAlgebra<Int, IntRing> get() = MultikIntAlgebra
//public val Int.Companion.multikAlgebra: MultikTensorAlgebra<Int, IntRing> get() = MultikIntAlgebra
//public val IntRing.multikAlgebra: MultikTensorAlgebra<Int, IntRing> get() = MultikIntAlgebra

9
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikLongAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikLongAlgebra.kt
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@ -5,12 +5,15 @@
package space.kscience.kmath.multik
import org.jetbrains.kotlinx.multik.api.Engine
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarrayOf
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
import space.kscience.kmath.operations.LongRing
public object MultikLongAlgebra : MultikTensorAlgebra<Long, LongRing>() {
public class MultikLongAlgebra(
multikEngine: Engine
) : MultikTensorAlgebra<Long, LongRing>(multikEngine) {
override val elementAlgebra: LongRing get() = LongRing
override val type: DataType get() = DataType.LongDataType
@ -18,5 +21,5 @@ public object MultikLongAlgebra : MultikTensorAlgebra<Long, LongRing>() {
}
public val Long.Companion.multikAlgebra: MultikTensorAlgebra<Long, LongRing> get() = MultikLongAlgebra
public val LongRing.multikAlgebra: MultikTensorAlgebra<Long, LongRing> get() = MultikLongAlgebra
//public val Long.Companion.multikAlgebra: MultikTensorAlgebra<Long, LongRing> get() = MultikLongAlgebra
//public val LongRing.multikAlgebra: MultikTensorAlgebra<Long, LongRing> get() = MultikLongAlgebra

9
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikShortAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikShortAlgebra.kt
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@ -5,16 +5,19 @@
package space.kscience.kmath.multik
import org.jetbrains.kotlinx.multik.api.Engine
import org.jetbrains.kotlinx.multik.api.Multik
import org.jetbrains.kotlinx.multik.api.ndarrayOf
import org.jetbrains.kotlinx.multik.ndarray.data.DataType
import space.kscience.kmath.operations.ShortRing
public object MultikShortAlgebra : MultikTensorAlgebra<Short, ShortRing>() {
public class MultikShortAlgebra(
multikEngine: Engine
) : MultikTensorAlgebra<Short, ShortRing>(multikEngine) {
override val elementAlgebra: ShortRing get() = ShortRing
override val type: DataType get() = DataType.ShortDataType
override fun scalar(value: Short): MultikTensor<Short> = Multik.ndarrayOf(value).wrap()
}
public val Short.Companion.multikAlgebra: MultikTensorAlgebra<Short, ShortRing> get() = MultikShortAlgebra
public val ShortRing.multikAlgebra: MultikTensorAlgebra<Short, ShortRing> get() = MultikShortAlgebra
//public val Short.Companion.multikAlgebra: MultikTensorAlgebra<Short, ShortRing> get() = MultikShortAlgebra
//public val ShortRing.multikAlgebra: MultikTensorAlgebra<Short, ShortRing> get() = MultikShortAlgebra

1
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensor.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikTensor.kt
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@ -9,6 +9,7 @@ import org.jetbrains.kotlinx.multik.ndarray.data.*
import space.kscience.kmath.misc.PerformancePitfall
import space.kscience.kmath.nd.Shape
import space.kscience.kmath.tensors.api.Tensor
import kotlin.jvm.JvmInline
@JvmInline
public value class MultikTensor<T>(public val array: MutableMultiArray<T, DN>) : Tensor<T> {

18
kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt → kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt
View File

@ -20,14 +20,15 @@ import space.kscience.kmath.tensors.api.Tensor
import space.kscience.kmath.tensors.api.TensorAlgebra
import space.kscience.kmath.tensors.api.TensorPartialDivisionAlgebra
public abstract class MultikTensorAlgebra<T, A : Ring<T>> : TensorAlgebra<T, A>
where T : Number, T : Comparable<T> {
public abstract class MultikTensorAlgebra<T, A : Ring<T>>(
private val multikEngine: Engine,
) : TensorAlgebra<T, A> where T : Number, T : Comparable<T> {
public abstract val type: DataType
protected val multikMath: Math = mk.math
protected val multikLinAl: LinAlg = mk.linalg
protected val multikStat: Statistics = mk.stat
protected val multikMath: Math = multikEngine.getMath()
protected val multikLinAl: LinAlg = multikEngine.getLinAlg()
protected val multikStat: Statistics = multikEngine.getStatistics()
override fun structureND(shape: Shape, initializer: A.(IntArray) -> T): MultikTensor<T> {
val strides = DefaultStrides(shape)
@ -255,12 +256,13 @@ public abstract class MultikTensorAlgebra<T, A : Ring<T>> : TensorAlgebra<T, A>
override fun StructureND<T>.argMax(dim: Int, keepDim: Boolean): Tensor<Int> {
if (keepDim) TODO("keepDim not implemented")
val res = multikMath.argMaxDN(asMultik().array, dim)
return with(MultikIntAlgebra) { res.wrap() }
return with(MultikIntAlgebra(multikEngine)) { res.wrap() }
}
}
public abstract class MultikDivisionTensorAlgebra<T, A : Field<T>>
: MultikTensorAlgebra<T, A>(), TensorPartialDivisionAlgebra<T, A> where T : Number, T : Comparable<T> {
public abstract class MultikDivisionTensorAlgebra<T, A : Field<T>>(
multikEngine: Engine,
) : MultikTensorAlgebra<T, A>(multikEngine), TensorPartialDivisionAlgebra<T, A> where T : Number, T : Comparable<T> {
override fun T.div(arg: StructureND<T>): MultikTensor<T> =
Multik.ones<T, DN>(arg.shape, type).apply { divAssign(arg.asMultik().array) }.wrap()

16
kmath-multik/src/test/kotlin/space/kscience/kmath/multik/MultikNDTest.kt → kmath-multik/src/commonTest/kotlin/space/kscience/kmath/multik/MultikNDTest.kt
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@ -5,33 +5,35 @@
package space.kscience.kmath.multik
import org.junit.jupiter.api.Test
import org.jetbrains.kotlinx.multik.default.DefaultEngine
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.one
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.tensorAlgebra
import kotlin.test.Test
import kotlin.test.assertTrue
internal class MultikNDTest {
val multikAlgebra = MultikDoubleAlgebra(DefaultEngine())
@Test
fun basicAlgebra(): Unit = DoubleField.multikAlgebra{
one(2,2) + 1.0
fun basicAlgebra(): Unit = with(multikAlgebra) {
one(2, 2) + 1.0
}
@Test
fun dotResult(){
fun dotResult() {
val dim = 100
val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224)
val tensor2 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12225)
val multikResult = with(DoubleField.multikAlgebra){
val multikResult = with(multikAlgebra) {
tensor1 dot tensor2
}
val defaultResult = with(DoubleField.tensorAlgebra){
val defaultResult = with(DoubleField.tensorAlgebra) {
tensor1 dot tensor2
}