Fix benchmarks source set #200
@ -31,4 +31,4 @@ internal class BufferBenchmark {
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companion object {
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companion object {
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const val size: Int = 100
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const val size: Int = 100
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}
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}
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}
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}
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@ -14,7 +14,7 @@ import org.openjdk.jmh.annotations.State
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import kotlin.random.Random
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import kotlin.random.Random
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@State(Scope.Benchmark)
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@State(Scope.Benchmark)
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class DotBenchmark {
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internal class DotBenchmark {
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companion object {
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companion object {
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val random = Random(12224)
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val random = Random(12224)
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val dim = 1000
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val dim = 1000
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@ -64,4 +64,4 @@ class DotBenchmark {
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matrix1 dot matrix2
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matrix1 dot matrix2
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}
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}
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}
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}
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}
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}
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@ -1,6 +1,8 @@
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package kscience.kmath.ast
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package kscience.kmath.benchmarks
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import kscience.kmath.asm.compile
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import kscience.kmath.asm.compile
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import kscience.kmath.ast.MstField
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import kscience.kmath.ast.mstInField
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import kscience.kmath.expressions.Expression
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import kscience.kmath.expressions.Expression
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import kscience.kmath.expressions.expressionInField
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import kscience.kmath.expressions.expressionInField
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import kscience.kmath.expressions.invoke
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import kscience.kmath.expressions.invoke
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@ -37,7 +39,7 @@ internal class ExpressionsInterpretersBenchmark {
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@Benchmark
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@Benchmark
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fun asmExpression() {
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fun asmExpression() {
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val expr = algebra.mstInField {
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val expr = algebra.mstInField {
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symbol("x") * 2.0 + 2.0 / symbol("x") - 16.0
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MstField.symbol("x") * 2.0 + 2.0 / MstField.symbol("x") - 16.0
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}.compile()
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}.compile()
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invokeAndSum(expr)
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invokeAndSum(expr)
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@ -1,5 +1,4 @@
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package kscience.kmath.linear
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package kscience.kmath.benchmarks
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import kotlinx.benchmark.Benchmark
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import kotlinx.benchmark.Benchmark
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import kscience.kmath.commons.linear.CMMatrixContext
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import kscience.kmath.commons.linear.CMMatrixContext
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@ -7,14 +6,17 @@ import kscience.kmath.commons.linear.CMMatrixContext.dot
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import kscience.kmath.commons.linear.inverse
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import kscience.kmath.commons.linear.inverse
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import kscience.kmath.ejml.EjmlMatrixContext
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import kscience.kmath.ejml.EjmlMatrixContext
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import kscience.kmath.ejml.inverse
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import kscience.kmath.ejml.inverse
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import kscience.kmath.linear.Matrix
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import kscience.kmath.linear.MatrixContext
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import kscience.kmath.linear.inverseWithLup
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import kscience.kmath.linear.real
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import kscience.kmath.operations.invoke
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import kscience.kmath.operations.invoke
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import kscience.kmath.structures.Matrix
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import org.openjdk.jmh.annotations.Scope
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import org.openjdk.jmh.annotations.Scope
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import org.openjdk.jmh.annotations.State
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import org.openjdk.jmh.annotations.State
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import kotlin.random.Random
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import kotlin.random.Random
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@State(Scope.Benchmark)
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@State(Scope.Benchmark)
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class LinearAlgebraBenchmark {
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internal class LinearAlgebraBenchmark {
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companion object {
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companion object {
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val random = Random(1224)
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val random = Random(1224)
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val dim = 100
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val dim = 100
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@ -43,4 +45,4 @@ class LinearAlgebraBenchmark {
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inverse(matrix)
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inverse(matrix)
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}
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}
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}
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}
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}
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}
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@ -42,4 +42,4 @@ internal class NDFieldBenchmark {
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val specializedField: RealNDField = NDAlgebra.real(dim, dim)
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val specializedField: RealNDField = NDAlgebra.real(dim, dim)
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val genericField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
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val genericField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
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}
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}
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}
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}
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@ -49,4 +49,4 @@ internal class ViktorBenchmark {
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var res = one
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var res = one
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repeat(n) { res = res + one }
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repeat(n) { res = res + one }
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}
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}
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}
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}
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@ -46,4 +46,4 @@ internal class ViktorLogBenchmark {
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res = fortyTwo.log()
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res = fortyTwo.log()
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}
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}
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}
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}
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}
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}
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