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lapack/testlapack: add benchmark for Dlangb
This commit is contained in:

committed by
Vladimír Chalupecký

parent
80ff04b367
commit
48873a0cd3
@@ -11,4 +11,5 @@ import (
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)
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func BenchmarkDgeev(b *testing.B) { testlapack.DgeevBenchmark(b, impl) }
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func BenchmarkDgeev(b *testing.B) { testlapack.DgeevBenchmark(b, impl) }
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func BenchmarkDlangb(b *testing.B) { testlapack.DlangbBenchmark(b, impl) }
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func BenchmarkDlantb(b *testing.B) { testlapack.DlantbBenchmark(b, impl) }
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func BenchmarkDlantb(b *testing.B) { testlapack.DlantbBenchmark(b, impl) }
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94
lapack/testlapack/dlangb_bench.go
Normal file
94
lapack/testlapack/dlangb_bench.go
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@@ -0,0 +1,94 @@
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// Copyright ©2021 The Gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package testlapack
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import (
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"fmt"
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"testing"
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"golang.org/x/exp/rand"
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"gonum.org/v1/gonum/lapack"
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)
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func DlangbBenchmark(b *testing.B, impl Dlangber) {
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const (
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safmin = dlamchS
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safmax = 1 / safmin
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ulp = dlamchP
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smlnum = safmin / ulp
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bignum = safmax * ulp
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)
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rnd := rand.New(rand.NewSource(1))
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for _, bm := range []struct {
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n, k int
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}{
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{n: 1000, k: 0},
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{n: 1000, k: 1},
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{n: 1000, k: 2},
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{n: 1000, k: 5},
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{n: 1000, k: 8},
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{n: 1000, k: 10},
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{n: 1000, k: 20},
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{n: 1000, k: 30},
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{n: 10000, k: 0},
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{n: 10000, k: 1},
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{n: 10000, k: 2},
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{n: 10000, k: 5},
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{n: 10000, k: 8},
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{n: 10000, k: 10},
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{n: 10000, k: 30},
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{n: 10000, k: 60},
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{n: 10000, k: 100},
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} {
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n := bm.n
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k := bm.k
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lda := 2*k + 1
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aCopy := make([]float64, n*lda)
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for i := range aCopy {
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aCopy[i] = 1 - 2*rnd.Float64()
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}
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a := make([]float64, len(aCopy))
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for _, norm := range []lapack.MatrixNorm{lapack.MaxAbs, lapack.MaxRowSum, lapack.MaxColumnSum} {
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name := fmt.Sprintf("%v_N=%v_K=%v", normToString(norm), n, k)
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b.Run(name, func(b *testing.B) {
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for i := 0; i < b.N; i++ {
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result = impl.Dlangb(norm, n, n, k, k, a, lda)
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}
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})
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}
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// Frobenius norm is benchmarked separately because its execution time
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// depends on the element magnitude.
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norm := lapack.Frobenius
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for _, scale := range []string{"Small", "Medium", "Big"} {
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name := fmt.Sprintf("%v_N=%v_K=%v_%v", normToString(norm), n, k, scale)
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var scl float64
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switch scale {
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default:
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scl = 1
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case "Small":
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scl = smlnum
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case "Big":
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scl = bignum
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}
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// Scale some elements so that the matrix contains a mix of small
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// and medium, all medium, or big and medium values.
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copy(a, aCopy)
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for i := range a {
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if i%2 == 0 {
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a[i] *= scl
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}
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}
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b.Run(name, func(b *testing.B) {
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for i := 0; i < b.N; i++ {
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result = impl.Dlangb(norm, n, n, k, k, a, lda)
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}
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})
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}
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}
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}
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