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go/src/math/export_s390x_test.go

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math: use SIMD to accelerate some scalar math functions on s390x Note, most math functions are structured to use stubs, so that they can be accelerated with assembly on any platform. Sinh, cosh, and tanh were not structued with stubs, so this CL does that. This set of routines was chosen as likely to produce good speedups with assembly on any platform. Technique used was minimax polynomial approximation using tables of polynomial coefficients, with argument range reduction. A table of scaling factors was also used for cosh and log10. before after speedup BenchmarkCos 22.1 ns/op 6.79 ns/op 3.25x BenchmarkCosh 125 ns/op 11.7 ns/op 10.68x BenchmarkLog10 48.4 ns/op 12.5 ns/op 3.87x BenchmarkSin 22.2 ns/op 6.55 ns/op 3.39x BenchmarkSinh 125 ns/op 14.2 ns/op 8.80x BenchmarkTanh 65.0 ns/op 15.1 ns/op 4.30x Accuracy was tested against a high precision reference function to determine maximum error. Approximately 4,000,000 points were tested for each function, producing the following result. Note: ulperr is error in "units in the last place" max ulperr sin 1.43 (returns NaN beyond +-2^50) cos 1.79 (returns NaN beyond +-2^50) cosh 1.05 sinh 3.02 tanh 3.69 log10 1.75 Also includes a set of tests to test non-vector functions even when SIMD is enabled Change-Id: Icb45f14d00864ee19ed973d209c3af21e4df4edc Reviewed-on: https://go-review.googlesource.com/32352 Run-TryBot: Michael Munday <munday@ca.ibm.com> TryBot-Result: Gobot Gobot <gobot@golang.org> Reviewed-by: Michael Munday <munday@ca.ibm.com>
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// Copyright 2016 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package math
// Export internal functions and variable for testing.
var Log10NoVec = log10
var CosNoVec = cos
var CoshNoVec = cosh
var SinNoVec = sin
var SinhNoVec = sinh
var TanhNoVec = tanh
math: use SIMD to accelerate additional scalar math functions on s390x As necessary, math functions were structured to use stubs, so that they can be accelerated with assembly on any platform. Technique used was minimax polynomial approximation using tables of polynomial coefficients, with argument range reduction. Benchmark New Old Speedup BenchmarkAcos 12.2 47.5 3.89 BenchmarkAcosh 18.5 56.2 3.04 BenchmarkAsin 13.1 40.6 3.10 BenchmarkAsinh 19.4 62.8 3.24 BenchmarkAtan 10.1 23 2.28 BenchmarkAtanh 19.1 53.2 2.79 BenchmarkAtan2 16.5 33.9 2.05 BenchmarkCbrt 14.8 58 3.92 BenchmarkErf 10.8 20.1 1.86 BenchmarkErfc 11.2 23.5 2.10 BenchmarkExp 8.77 53.8 6.13 BenchmarkExpm1 10.1 38.3 3.79 BenchmarkLog 13.1 40.1 3.06 BenchmarkLog1p 12.7 38.3 3.02 BenchmarkPowInt 31.7 40.5 1.28 BenchmarkPowFrac 33.1 141 4.26 BenchmarkTan 11.5 30 2.61 Accuracy was tested against a high precision reference function to determine maximum error. Note: ulperr is error in "units in the last place" max ulperr Acos 1.15 Acosh 1.07 Asin 2.22 Asinh 1.72 Atan 1.41 Atanh 3.00 Atan2 1.45 Cbrt 1.18 Erf 1.29 Erfc 4.82 Exp 1.00 Expm1 2.26 Log 0.94 Log1p 2.39 Tan 3.14 Pow will have 99.99% correctly rounded results with reasonable inputs producing numeric (non Inf or NaN) results Change-Id: I850e8cf7b70426e8b54ec49d74acd4cddc8c6cb2 Reviewed-on: https://go-review.googlesource.com/38585 Reviewed-by: Michael Munday <munday@ca.ibm.com> Run-TryBot: Michael Munday <munday@ca.ibm.com> TryBot-Result: Gobot Gobot <gobot@golang.org>
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var Log1pNovec = log1p
var AtanhNovec = atanh
var AcosNovec = acos
var AcoshNovec = acosh
var AsinNovec = asin
var AsinhNovec = asinh
var ErfNovec = erf
var ErfcNovec = erfc
var AtanNovec = atan
var Atan2Novec = atan2
var CbrtNovec = cbrt
var LogNovec = log
var TanNovec = tan
var ExpNovec = exp
var Expm1Novec = expm1
var PowNovec = pow
var HypotNovec = hypot
math: use SIMD to accelerate some scalar math functions on s390x Note, most math functions are structured to use stubs, so that they can be accelerated with assembly on any platform. Sinh, cosh, and tanh were not structued with stubs, so this CL does that. This set of routines was chosen as likely to produce good speedups with assembly on any platform. Technique used was minimax polynomial approximation using tables of polynomial coefficients, with argument range reduction. A table of scaling factors was also used for cosh and log10. before after speedup BenchmarkCos 22.1 ns/op 6.79 ns/op 3.25x BenchmarkCosh 125 ns/op 11.7 ns/op 10.68x BenchmarkLog10 48.4 ns/op 12.5 ns/op 3.87x BenchmarkSin 22.2 ns/op 6.55 ns/op 3.39x BenchmarkSinh 125 ns/op 14.2 ns/op 8.80x BenchmarkTanh 65.0 ns/op 15.1 ns/op 4.30x Accuracy was tested against a high precision reference function to determine maximum error. Approximately 4,000,000 points were tested for each function, producing the following result. Note: ulperr is error in "units in the last place" max ulperr sin 1.43 (returns NaN beyond +-2^50) cos 1.79 (returns NaN beyond +-2^50) cosh 1.05 sinh 3.02 tanh 3.69 log10 1.75 Also includes a set of tests to test non-vector functions even when SIMD is enabled Change-Id: Icb45f14d00864ee19ed973d209c3af21e4df4edc Reviewed-on: https://go-review.googlesource.com/32352 Run-TryBot: Michael Munday <munday@ca.ibm.com> TryBot-Result: Gobot Gobot <gobot@golang.org> Reviewed-by: Michael Munday <munday@ca.ibm.com>
2016-10-29 22:11:37 -06:00
var HasVX = hasVX