Retro68/gcc/libgfortran/m4/matmul.m4
2017-10-07 02:16:47 +02:00

179 lines
5.9 KiB
Plaintext

`/* Implementation of the MATMUL intrinsic
Copyright (C) 2002-2017 Free Software Foundation, Inc.
Contributed by Paul Brook <paul@nowt.org>
This file is part of the GNU Fortran runtime library (libgfortran).
Libgfortran is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public
License as published by the Free Software Foundation; either
version 3 of the License, or (at your option) any later version.
Libgfortran is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
Under Section 7 of GPL version 3, you are granted additional
permissions described in the GCC Runtime Library Exception, version
3.1, as published by the Free Software Foundation.
You should have received a copy of the GNU General Public License and
a copy of the GCC Runtime Library Exception along with this program;
see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
<http://www.gnu.org/licenses/>. */
#include "libgfortran.h"
#include <string.h>
#include <assert.h>'
include(iparm.m4)dnl
`#if defined (HAVE_'rtype_name`)
/* Prototype for the BLAS ?gemm subroutine, a pointer to which can be
passed to us by the front-end, in which case we call it for large
matrices. */
typedef void (*blas_call)(const char *, const char *, const int *, const int *,
const int *, const 'rtype_name` *, const 'rtype_name` *,
const int *, const 'rtype_name` *, const int *,
const 'rtype_name` *, 'rtype_name` *, const int *,
int, int);
/* The order of loops is different in the case of plain matrix
multiplication C=MATMUL(A,B), and in the frequent special case where
the argument A is the temporary result of a TRANSPOSE intrinsic:
C=MATMUL(TRANSPOSE(A),B). Transposed temporaries are detected by
looking at their strides.
The equivalent Fortran pseudo-code is:
DIMENSION A(M,COUNT), B(COUNT,N), C(M,N)
IF (.NOT.IS_TRANSPOSED(A)) THEN
C = 0
DO J=1,N
DO K=1,COUNT
DO I=1,M
C(I,J) = C(I,J)+A(I,K)*B(K,J)
ELSE
DO J=1,N
DO I=1,M
S = 0
DO K=1,COUNT
S = S+A(I,K)*B(K,J)
C(I,J) = S
ENDIF
*/
/* If try_blas is set to a nonzero value, then the matmul function will
see if there is a way to perform the matrix multiplication by a call
to the BLAS gemm function. */
extern void matmul_'rtype_code` ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm);
export_proto(matmul_'rtype_code`);
/* Put exhaustive list of possible architectures here here, ORed together. */
#if defined(HAVE_AVX) || defined(HAVE_AVX2) || defined(HAVE_AVX512F)
#ifdef HAVE_AVX
'define(`matmul_name',`matmul_'rtype_code`_avx')dnl
`static void
'matmul_name` ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm) __attribute__((__target__("avx")));
static' include(matmul_internal.m4)dnl
`#endif /* HAVE_AVX */
#ifdef HAVE_AVX2
'define(`matmul_name',`matmul_'rtype_code`_avx2')dnl
`static void
'matmul_name` ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm) __attribute__((__target__("avx2,fma")));
static' include(matmul_internal.m4)dnl
`#endif /* HAVE_AVX2 */
#ifdef HAVE_AVX512F
'define(`matmul_name',`matmul_'rtype_code`_avx512f')dnl
`static void
'matmul_name` ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm) __attribute__((__target__("avx512f")));
static' include(matmul_internal.m4)dnl
`#endif /* HAVE_AVX512F */
/* Function to fall back to if there is no special processor-specific version. */
'define(`matmul_name',`matmul_'rtype_code`_vanilla')dnl
`static' include(matmul_internal.m4)dnl
`/* Compiling main function, with selection code for the processor. */
/* Currently, this is i386 only. Adjust for other architectures. */
#include <config/i386/cpuinfo.h>
void matmul_'rtype_code` ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm)
{
static void (*matmul_p) ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm);
void (*matmul_fn) ('rtype` * const restrict retarray,
'rtype` * const restrict a, 'rtype` * const restrict b, int try_blas,
int blas_limit, blas_call gemm);
matmul_fn = __atomic_load_n (&matmul_p, __ATOMIC_RELAXED);
if (matmul_fn == NULL)
{
matmul_fn = matmul_'rtype_code`_vanilla;
if (__cpu_model.__cpu_vendor == VENDOR_INTEL)
{
/* Run down the available processors in order of preference. */
#ifdef HAVE_AVX512F
if (__cpu_model.__cpu_features[0] & (1 << FEATURE_AVX512F))
{
matmul_fn = matmul_'rtype_code`_avx512f;
goto store;
}
#endif /* HAVE_AVX512F */
#ifdef HAVE_AVX2
if ((__cpu_model.__cpu_features[0] & (1 << FEATURE_AVX2))
&& (__cpu_model.__cpu_features[0] & (1 << FEATURE_FMA)))
{
matmul_fn = matmul_'rtype_code`_avx2;
goto store;
}
#endif
#ifdef HAVE_AVX
if (__cpu_model.__cpu_features[0] & (1 << FEATURE_AVX))
{
matmul_fn = matmul_'rtype_code`_avx;
goto store;
}
#endif /* HAVE_AVX */
}
store:
__atomic_store_n (&matmul_p, matmul_fn, __ATOMIC_RELAXED);
}
(*matmul_fn) (retarray, a, b, try_blas, blas_limit, gemm);
}
#else /* Just the vanilla function. */
'define(`matmul_name',`matmul_'rtype_code)dnl
define(`target_attribute',`')dnl
include(matmul_internal.m4)dnl
`#endif
#endif
'