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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/05/09 08:14:10 UTC
[GitHub] [incubator-mxnet] pengzhao-intel commented on a change in pull
request #14893: Integrating the MKL VML functions to MXNET to speed-up the
(element-wised) mathematic computation
pengzhao-intel commented on a change in pull request #14893: Integrating the MKL VML functions to MXNET to speed-up the (element-wised) mathematic computation
URL: https://github.com/apache/incubator-mxnet/pull/14893#discussion_r282379956
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File path: src/operator/mkl_functions-inl.h
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@@ -0,0 +1,218 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2018 by Contributors
+ * \file mkl_functions-inl.h
+ * \brief
+ * \author
+*/
+#ifndef MXNET_OPERATOR_MKL_FUNCTIONS_INL_H_
+#define MXNET_OPERATOR_MKL_FUNCTIONS_INL_H_
+
+#if MSHADOW_USE_MKL == 1
+#include "mkl.h"
+
+namespace mxnet {
+namespace op {
+namespace mkl_func {
+
+MSHADOW_XINLINE
+static bool check_size(const size_t n) {
+ const size_t MKL_INT_MAX = (sizeof(MKL_INT) == sizeof(int)) ? INT_MAX : LLONG_MAX;
+ return (n <= MKL_INT_MAX);
+}
+
+MSHADOW_XINLINE
+static bool check_type(const int t) {
+ return (t == mshadow::kFloat32 || t == mshadow::kFloat64);
+}
+
+#define MXNET_MKL_UNARY_MATH_FUNC(name, func) \
+struct name { \
+ MSHADOW_XINLINE static void Vectorize(const index_t n, const float *src, float *dst) { \
+ vs##func(static_cast<MKL_INT>(n), src, dst); \
+ } \
+ MSHADOW_XINLINE static void Vectorize(const index_t n, const double *src, double *dst) { \
+ vd##func(static_cast<MKL_INT>(n), src, dst); \
+ } \
+};
+
+#define MXNET_MKL_BINARY_MATH_FUNC(name, func) \
+struct name { \
+ MSHADOW_XINLINE static void Vectorize(const index_t n, \
+ const float *a, \
+ const float *b, \
+ float *c) { \
+ vs##func(static_cast<MKL_INT>(n), a, b, c); \
+ } \
+ MSHADOW_XINLINE static void Vectorize(const index_t n, \
+ const double *a, \
+ const double *b, \
+ double *c) { \
+ vd##func(static_cast<MKL_INT>(n), a, b, c); \
+ } \
+};
+
+MXNET_MKL_UNARY_MATH_FUNC(erf, Erf);
+MXNET_MKL_UNARY_MATH_FUNC(exp, Exp);
+MXNET_MKL_UNARY_MATH_FUNC(exp2, Exp2);
+MXNET_MKL_UNARY_MATH_FUNC(exp10, Exp10);
+MXNET_MKL_UNARY_MATH_FUNC(expm1, Expm1);
+MXNET_MKL_UNARY_MATH_FUNC(log, Ln);
+MXNET_MKL_UNARY_MATH_FUNC(log2, Log2);
+MXNET_MKL_UNARY_MATH_FUNC(log10, Log10);
+MXNET_MKL_UNARY_MATH_FUNC(log1p, Log1p);
+
+MXNET_MKL_UNARY_MATH_FUNC(sin, Sin);
+MXNET_MKL_UNARY_MATH_FUNC(cos, Cos);
+MXNET_MKL_UNARY_MATH_FUNC(tan, Tan);
+MXNET_MKL_UNARY_MATH_FUNC(asin, Asin);
+MXNET_MKL_UNARY_MATH_FUNC(acos, Acos);
+MXNET_MKL_UNARY_MATH_FUNC(atan, Atan);
+
+MXNET_MKL_UNARY_MATH_FUNC(sinh, Sinh);
+MXNET_MKL_UNARY_MATH_FUNC(cosh, Cosh);
+MXNET_MKL_UNARY_MATH_FUNC(tanh, Tanh);
+MXNET_MKL_UNARY_MATH_FUNC(asinh, Asinh);
+MXNET_MKL_UNARY_MATH_FUNC(acosh, Acosh);
+MXNET_MKL_UNARY_MATH_FUNC(atanh, Atanh);
+
+MXNET_MKL_UNARY_MATH_FUNC(sqrt, Sqrt);
+MXNET_MKL_UNARY_MATH_FUNC(abs, Abs);
+MXNET_MKL_UNARY_MATH_FUNC(cbrt, Cbrt);
+MXNET_MKL_UNARY_MATH_FUNC(round, Round);
+MXNET_MKL_UNARY_MATH_FUNC(ceil, Ceil);
+MXNET_MKL_UNARY_MATH_FUNC(floor, Floor);
+MXNET_MKL_UNARY_MATH_FUNC(trunc, Trunc);
+
+MXNET_MKL_UNARY_MATH_FUNC(lgamma, LGamma);
+MXNET_MKL_UNARY_MATH_FUNC(tgamma, TGamma);
+MXNET_MKL_UNARY_MATH_FUNC(square, Sqr);
+
+MXNET_MKL_BINARY_MATH_FUNC(add, Add);
+MXNET_MKL_BINARY_MATH_FUNC(sub, Sub);
+MXNET_MKL_BINARY_MATH_FUNC(mul, Mul);
+MXNET_MKL_BINARY_MATH_FUNC(pow, Pow);
+MXNET_MKL_BINARY_MATH_FUNC(hypot, Hypot);
+
+
+template <typename DType>
+MSHADOW_XINLINE static void sub_(index_t n, DType *in, DType b, DType *dst) {
+ for (index_t i = 0; i < n; i++)
+ dst[i] = in[i] - b;
+}
+
+template <typename DType>
+MSHADOW_XINLINE static void div_(index_t n, DType *in, DType b, DType *dst) {
+ for (index_t i = 0; i < n; i++)
+ dst[i] = in[i] / b;
+}
+
+template <typename DType>
+MSHADOW_XINLINE static void sum_(index_t n, DType *in, DType *dst) {
+ // dst[0] = cblas_sasum(n, in, 1);
+ DType sum = 0.0f;
+ for (index_t i = 0; i < n; i++)
+ sum += in[i];
+
+ dst[0] = sum;
+}
+
+template <typename DType>
+MSHADOW_XINLINE static void max_(int n, DType * __restrict__ in, DType *dst) {
+ dst[0] = in[0];
+ for (int i = 1; i < n; i++)
+ dst[0] = (dst[0] < in[i]) ? in[i] : dst[0];
+}
+
+// LayerNorm on the last dimension
+template <typename DType>
+MSHADOW_XINLINE static void LayerNormLastDim(const index_t m,
+ const index_t n,
+ const DType *a,
+ const DType *b,
+ const DType *ws,
+ const DType *gamma,
+ const DType *beta,
+ const DType *mean,
+ const DType *var,
+ const DType eps) {
+#pragma omp parallel for
Review comment:
Add the number of threads
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