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体验新版 GitCode,发现更多精彩内容 >>
提交
62be492e
编写于
3月 08, 2017
作者:
A
A. Unique TensorFlower
提交者:
TensorFlower Gardener
3月 08, 2017
浏览文件
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电子邮件补丁
差异文件
Fixed bfloat16 integration of LIBXSMM sparse mat-mul.
Change: 149617825
上级
89df2a1b
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
21 addition
and
18 deletion
+21
-18
tensorflow/core/kernels/sparse_matmul_op.cc
tensorflow/core/kernels/sparse_matmul_op.cc
+21
-18
未找到文件。
tensorflow/core/kernels/sparse_matmul_op.cc
浏览文件 @
62be492e
...
...
@@ -1522,21 +1522,24 @@ void wrapper_libxsmm_spmdm_createSparseSlice_generic_thread(
void
wrapper_libxsmm_spmdm_compute_generic_thread
(
empty_type_wrapper
<
bfloat16
>
,
const
libxsmm_spmdm_handle
*
handle
,
char
transA
,
char
transB
,
const
bfloat16
*
alpha
,
libxsmm_CSR_sparseslice
*
A_sparse
,
const
bfloat16
*
B
,
char
transC
,
const
bfloat16
*
beta
,
float
*
C
,
int
block_id
,
int
tid
,
int
nthreads
)
{
char
transA
,
char
transB
,
libxsmm_CSR_sparseslice
*
A_sparse
,
const
bfloat16
*
B
,
char
transC
,
float
*
C
,
int
block_id
,
int
tid
,
int
nthreads
)
{
const
uint16
alpha
=
1
;
const
uint16
beta
=
0
;
return
libxsmm_spmdm_compute_bfloat16_thread
(
handle
,
transA
,
transB
,
reinterpret_cast
<
const
uint16
*>
(
alpha
)
,
A_sparse
,
reinterpret_cast
<
const
uint16
*>
(
B
),
transC
,
reinterpret_cast
<
const
uint16
*>
(
beta
),
C
,
block_id
,
tid
,
nthreads
);
handle
,
transA
,
transB
,
&
alpha
,
A_sparse
,
reinterpret_cast
<
const
uint16
*>
(
B
),
transC
,
&
beta
,
C
,
block_id
,
tid
,
nthreads
);
}
void
wrapper_libxsmm_spmdm_compute_generic_thread
(
empty_type_wrapper
<
float
>
,
const
libxsmm_spmdm_handle
*
handle
,
char
transA
,
char
transB
,
const
float
*
alpha
,
libxsmm_CSR_sparseslice
*
A_sparse
,
const
float
*
B
,
char
transC
,
const
float
*
beta
,
float
*
C
,
int
block_id
,
int
tid
,
int
nthreads
)
{
return
libxsmm_spmdm_compute_fp32_thread
(
handle
,
transA
,
transB
,
alpha
,
A_sparse
,
B
,
transC
,
beta
,
C
,
char
transB
,
libxsmm_CSR_sparseslice
*
A_sparse
,
const
float
*
B
,
char
transC
,
float
*
C
,
int
block_id
,
int
tid
,
int
nthreads
)
{
const
float
alpha
=
1.
f
;
const
float
beta
=
0.
f
;
return
libxsmm_spmdm_compute_fp32_thread
(
handle
,
transA
,
transB
,
&
alpha
,
A_sparse
,
B
,
transC
,
&
beta
,
C
,
block_id
,
tid
,
nthreads
);
}
...
...
@@ -1648,13 +1651,11 @@ inline void LibxsmmSparseMatMul<TL, TR>::Compute(
while
(
true
)
{
int
work_item
=
cur_mult_block_number
.
fetch_add
(
1
);
if
(
work_item
>=
total_num_mult_blocks
)
break
;
const
TL
alpha
(
1.0
);
// Stored in a variable so we can get a pointer
const
TL
beta
(
0.0
);
// Stored in a variable so we can get a pointer
wrapper_libxsmm_spmdm_compute_generic_thread
(
empty_type_wrapper
<
TL
>
{},
&
entry
->
handle
,
(
transpose_left
?
'T'
:
'N'
),
'N'
,
&
alpha
,
entry
->
output_csr
,
right_data
,
(
transpose_output
?
'T'
:
'N'
),
&
beta
,
output_data
,
work_item
,
i
,
actual_num_threads
);
(
transpose_left
?
'T'
:
'N'
),
'N'
,
entry
->
output_csr
,
right_data
,
(
transpose_output
?
'T'
:
'N'
),
output_data
,
work_item
,
i
,
actual_num_threads
);
}
});
// Put handle + CSR storage back into cache
...
...
@@ -1802,15 +1803,17 @@ inline void SparseMatMul<TL, TR>::Compute(
SparseMatMulOp<TA, TB, LibxsmmSparseMatMul>);
#endif
REGISTER_SPARSE_MATMUL
(
bfloat16
,
bfloat16
);
REGISTER_SPARSE_MATMUL
(
float
,
bfloat16
);
REGISTER_SPARSE_MATMUL
(
bfloat16
,
float
);
#ifdef TENSORFLOW_USE_LIBXSMM
REGISTER_SPARSE_MATMUL_LIBXSMM
(
bfloat16
,
bfloat16
);
REGISTER_SPARSE_MATMUL_LIBXSMM
(
float
,
float
);
#else
REGISTER_SPARSE_MATMUL
(
bfloat16
,
bfloat16
);
REGISTER_SPARSE_MATMUL
(
float
,
float
);
#endif
...
...
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