Files
blis/config/template/kernels/1f/bli_axpyf_opt_var1.c
Field G. Van Zee fde5f1fdec Added extensive support for configuration defaults.
Details:
- Standard names for reference kernels (levels-1v, -1f and 3) are now
  macro constants. Examples:
    BLIS_SAXPYV_KERNEL_REF
    BLIS_DDOTXF_KERNEL_REF
    BLIS_ZGEMM_UKERNEL_REF
- Developers no longer have to name all datatype instances of a kernel
  with a common base name; [sdcz] datatype flavors of each kernel or
  micro-kernel (level-1v, -1f, or 3) may now be named independently.
  This means you can now, if you wish, encode the datatype-specific
  register blocksizes in the name of the micro-kernel functions.
- Any datatype instances of any kernel (1v, 1f, or 3) that is left
  undefined in bli_kernel.h will default to the corresponding reference
  implementation. For example, if BLIS_DGEMM_UKERNEL is left undefined,
  it will be defined to be BLIS_DGEMM_UKERNEL_REF.
- Developers no longer need to name level-1v/-1f kernels with multiple
  datatype chars to match the number of types the kernel WOULD take in
  a mixed type environment, as in bli_dddaxpyv_opt(). Now, one char is
  sufficient, as in bli_daxpyv_opt().
- There is no longer a need to define an obj_t wrapper to go along with
  your level-1v/-1f kernels. The framework now prvides a _kernel()
  function which serves as the obj_t wrapper for whatever kernels are
  specified (or defaulted to) via bli_kernel.h
- Developers no longer need to prototype their kernels, and thus no
  longer need to include any prototyping headers from within
  bli_kernel.h. The framework now generates kernel prototypes, with the
  proper type signature, based on the kernel names defined (or defaulted
  to) via bli_kernel.h.
- If the complex datatype x (of [cz]) implementation of the gemm micro-
  kernel is left undefined by bli_kernel.h, but its same-precision real
  domain equivalent IS defined, BLIS will use a 4m-based implementation
  for the datatype x implementations of all level-3 operations, using
  only the real gemm micro-kernel.
2014-02-25 13:34:56 -06:00

379 lines
12 KiB
C

/*
BLIS
An object-based framework for developing high-performance BLAS-like
libraries.
Copyright (C) 2014, The University of Texas
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
- Neither the name of The University of Texas nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include "blis.h"
void bli_saxpyf_opt_var1(
conj_t conja,
conj_t conjx,
dim_t m,
dim_t b_n,
float* restrict alpha,
float* restrict a, inc_t inca, inc_t lda,
float* restrict x, inc_t incx,
float* restrict y, inc_t incy
)
{
/* Just call the reference implementation. */
BLIS_SAXPYF_KERNEL_REF( conja,
conjx,
m,
b_n,
alpha,
a, inca, lda,
x, incx,
y, incy );
}
void bli_daxpyf_opt_var1(
conj_t conja,
conj_t conjx,
dim_t m,
dim_t b_n,
double* restrict alpha,
double* restrict a, inc_t inca, inc_t lda,
double* restrict x, inc_t incx,
double* restrict y, inc_t incy
)
{
/* Just call the reference implementation. */
BLIS_DAXPYF_KERNEL_REF( conja,
conjx,
m,
b_n,
alpha,
a, inca, lda,
x, incx,
y, incy );
}
void bli_caxpyf_opt_var1(
conj_t conja,
conj_t conjx,
dim_t m,
dim_t b_n,
scomplex* restrict alpha,
scomplex* restrict a, inc_t inca, inc_t lda,
scomplex* restrict x, inc_t incx,
scomplex* restrict y, inc_t incy
)
{
/* Just call the reference implementation. */
BLIS_CAXPYF_KERNEL_REF( conja,
conjx,
m,
b_n,
alpha,
a, inca, lda,
x, incx,
y, incy );
}
void bli_zaxpyf_opt_var1(
conj_t conja,
conj_t conjx,
dim_t m,
dim_t b_n,
dcomplex* restrict alpha,
dcomplex* restrict a, inc_t inca, inc_t lda,
dcomplex* restrict x, inc_t incx,
dcomplex* restrict y, inc_t incy
)
{
/*
Template axpyf kernel implementation
This function contains a template implementation for a double-precision
complex kernel, coded in C, which can serve as the starting point for one
to write an optimized kernel on an arbitrary architecture. (We show a
template implementation for only double-precision complex because the
templates for the other three floating-point types would be similar, with
the real instantiations being noticeably simpler due to the disappearance
of conjugation in the real domain.)
This kernel performs the following gemv-like operation:
y := y + alpha * conja( A ) * conjx( x )
where A is an m x b_n matrix, x is a vector of length b_n, y is a vector
of length m, and alpha is a scalar. The operation is performed as a series
of fused axpyv operations, and therefore A should be column-stored.
Parameters:
- conja: Compute with conjugated values of A?
- conjx: Compute with conjugated values of x?
- m: The number of rows in matrix A.
- b_n: The number of columns in matrix A. Must be equal to or less than
the fusing factor.
- alpha: The address of a scalar.
- a: The address of matrix A.
- inca: The row stride of A. inca should be unit unless the
implementation makes special accomodation for non-unit values.
- lda: The column stride of A.
- x: The address of vector x.
- incx: The vector increment of x.
- y: The address of vector y.
- incy: The vector increment of y. incy should be unit unless the
implementation makes special accomodation for non-unit values.
This template code calls the reference implementation if any of the
following conditions are true:
- Either of the strides inca or incy is non-unit.
- The address of A, the second column of A, and y are unaligned with
different offsets.
If the first/second columns of A and address of y are aligned, or unaligned
by the same offset, then optimized code can be used for the bulk of the
computation. This template shows how the front-edge case can be handled so
that the remaining computation is aligned. (This template guarantees
alignment in the main loops to be BLIS_SIMD_ALIGN_SIZE, which is defined
in bli_config.h.)
Additional things to consider:
- When optimizing, you should fully unroll the loops over b_n. This is the
dimension across which we are fusing axpyv operations.
- This template code chooses to call the reference implementation whenever
b_n is less than the fusing factor, so as to avoid having to handle edge
cases. One may choose to optimize this edge case, if desired.
- Because conjugation disappears in the real domain, real instances of
this kernel can safely ignore the values of any conjugation parameters,
thereby simplifying the implementation.
For more info, please refer to the BLIS website and/or contact the
blis-devel mailing list.
-FGVZ
*/
const dim_t n_elem_per_reg = 1;
const dim_t n_iter_unroll = 1;
const dim_t n_elem_per_iter = n_elem_per_reg * n_iter_unroll;
const siz_t type_size = sizeof( *a );
dcomplex* ap[ bli_zaxpyf_fusefac ];
dcomplex* xp[ bli_zaxpyf_fusefac ];
dcomplex* yp;
dcomplex alpha_x[ bli_zaxpyf_fusefac ];
bool_t use_ref = FALSE;
dim_t m_pre = 0;
dim_t m_iter;
dim_t m_left;
dim_t off_a, off_a2, off_y;
dim_t i, j;
// Return early if possible.
if ( bli_zero_dim2( m, b_n ) ) return;
// If there is anything that would interfere with our use of aligned
// vector loads/stores, call the reference implementation.
if ( b_n < bli_zaxpyf_fusefac )
{
use_ref = TRUE;
}
else if ( bli_has_nonunit_inc3( inca, incx, incy ) )
{
use_ref = TRUE;
}
else if ( bli_is_unaligned_to( a, BLIS_SIMD_ALIGN_SIZE ) ||
bli_is_unaligned_to( a+lda, BLIS_SIMD_ALIGN_SIZE ) ||
bli_is_unaligned_to( y, BLIS_SIMD_ALIGN_SIZE ) )
{
use_ref = TRUE;
// If a, the second column of a, and y are unaligned by the same
// offset, then we can still use an implementation that depends on
// alignment for most of the operation.
off_a = bli_offset_from_alignment( a, BLIS_SIMD_ALIGN_SIZE );
off_a2 = bli_offset_from_alignment( a+lda, BLIS_SIMD_ALIGN_SIZE );
off_y = bli_offset_from_alignment( y, BLIS_SIMD_ALIGN_SIZE );
if ( off_a == off_y && off_a == off_a2 )
{
use_ref = FALSE;
m_pre = off_a / type_size;
}
}
// Call the reference implementation if needed.
if ( use_ref == TRUE )
{
BLIS_ZAXPYF_KERNEL_REF( conja,
conjx,
m,
b_n,
alpha,
a, inca, lda,
x, incx,
y, incy );
return;
}
// Compute the number of unrolled and leftover (edge) iterations.
m_iter = ( m - m_pre ) / n_elem_per_iter;
m_left = ( m - m_pre ) % n_elem_per_iter;
// Initialize pointers into the columns of A and elements of x.
for ( j = 0; j < b_n; ++j )
{
ap[ j ] = a + (j )*lda;
xp[ j ] = x + (j )*incx;
}
yp = y;
// Load elements of x or conj(x) into alpha_x and scale by alpha.
if ( bli_is_noconj( conjx ) )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzcopys( *xp[ j ], alpha_x[ j ] );
bli_zzscals( *alpha, alpha_x[ j ] );
}
}
else // if ( bli_is_conj( conjx ) )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzcopyjs( *xp[ j ], alpha_x[ j ] );
bli_zzscals( *alpha, alpha_x[ j ] );
}
}
// Iterate over rows of A and y to compute:
// y += conja( A )*conjx( x );
if ( bli_is_noconj( conja ) )
{
// Compute front edge cases if a and y were unaligned.
for ( i = 0; i < m_pre; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpys( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += 1;
}
yp += 1;
}
// The bulk of the operation is executed here. For best performance,
// the elements of alpha_x should be loaded once prior to the m_iter
// loop, and the b_n loop should be fully unrolled. The addresses in
// ap[] and yp are guaranteed to be aligned to
// BLIS_SIMD_ALIGN_SIZE.
for ( i = 0; i < m_iter; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpys( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += n_elem_per_iter;
}
yp += n_elem_per_iter;
}
// Compute tail edge cases, if applicable.
for ( i = 0; i < m_left; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpys( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += 1;
}
yp += 1;
}
}
else // if ( bli_is_conj( conja ) )
{
// Compute front edge cases if a and y were unaligned.
for ( i = 0; i < m_pre; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpyjs( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += 1;
}
yp += 1;
}
// The bulk of the operation is executed here. For best performance,
// the elements of alpha_x should be loaded once prior to the m_iter
// loop, and the b_n loop should be fully unrolled. The addresses in
// ap[] and yp are guaranteed to be aligned to
// BLIS_SIMD_ALIGN_SIZE.
for ( i = 0; i < m_iter; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpyjs( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += n_elem_per_iter;
}
yp += n_elem_per_iter;
}
// Compute tail edge cases.
for ( i = 0; i < m_left; ++i )
{
for ( j = 0; j < b_n; ++j )
{
bli_zzzaxpyjs( alpha_x[ j ], *ap[ j ], *yp );
ap[ j ] += 1;
}
yp += 1;
}
}
}