build: aligned DNNL_BLAS_VENDOR option description with documentation

This commit is contained in:
Pirogov, Vadim
2024-02-28 11:50:32 -08:00
committed by Vadim Pirogov
parent 3f05deb553
commit b1ffb3d193
2 changed files with 10 additions and 7 deletions

View File

@ -1,5 +1,6 @@
# *******************************************************************************
# Copyright 2020-2021 Arm Limited and affiliates.
# Copyright 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
@ -34,6 +35,11 @@ if (NOT "${DNNL_BLAS_VENDOR}" MATCHES "^(NONE|MKL|OPENBLAS|ARMPL|ACCELERATE|ANY)
message(FATAL_ERROR "Unsupported DNNL_BLAS_VENDOR: ${DNNL_BLAS_VENDOR}.")
endif()
if (NOT "${DNNL_BLAS_VENDOR}" MATCHES "^(NONE|ARMPL|ACCELERATE)$")
message(WARNING "Use of DNNL_BLAS_VENDOR=${DNNL_BLAS_VENDOR} is not "
"recommended. This vendor is supported for performance analysis purposes only.")
endif()
macro(expect_arch_or_generic arch)
if(NOT "${DNNL_TARGET_ARCH}" MATCHES "^(${arch}|ARCH_GENERIC)$")
message(FATAL_ERROR "DNNL_BLAS_VENDOR=${DNNL_BLAS_VENDOR} is not supported "

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@ -380,19 +380,16 @@ option(DNNL_ENABLE_STACK_CHECKER "enables stack checker that can be used to get
set(DNNL_BLAS_VENDOR "NONE" CACHE STRING
"Use an external BLAS library. Valid values:
- NONE (default)
Use in-house implementation.
- MKL
Intel oneAPI Math Kernel Library (Intel oneMKL)
(https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html)
- OPENBLAS
(https://www.openblas.net)
Use internal BLAS implementation. Recommended in most situations.
- ACCELERATE
(https://developer.apple.com/documentation/accelerate/blas)
- ARMPL
Arm Performance Libraries
(https://developer.arm.com/tools-and-software/server-and-hpc/downloads/arm-performance-libraries)
- ANY
FindBLAS will search default library paths for a known BLAS installation.")
FindBLAS will search default library paths for a known BLAS
installation. This vendor is supported for performance analysis
purposes only.")
# ==============================================
# AArch64 optimizations with Arm Compute Library