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体验新版 GitCode,发现更多精彩内容 >>
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f269614b
编写于
8月 24, 2018
作者:
T
tensor-tang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
further optimize tanh with avx and mkl
上级
c70a3fec
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
90 addition
and
85 deletion
+90
-85
paddle/fluid/operators/math/cpu_vec.h
paddle/fluid/operators/math/cpu_vec.h
+90
-85
未找到文件。
paddle/fluid/operators/math/cpu_vec.h
浏览文件 @
f269614b
...
...
@@ -45,6 +45,13 @@ inline void vec_exp(const int n, const T* x, T* y) {
}
}
template
<
typename
T
>
inline
void
vec_scal
(
const
int
n
,
const
T
a
,
T
*
x
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
x
[
i
]
=
a
*
x
[
i
];
}
}
#ifdef PADDLE_WITH_MKLML
template
<
>
inline
void
vec_exp
<
float
>
(
const
int
n
,
const
float
*
x
,
float
*
y
)
{
...
...
@@ -55,7 +62,74 @@ template <>
inline
void
vec_exp
<
double
>
(
const
int
n
,
const
double
*
x
,
double
*
y
)
{
platform
::
dynload
::
vdExp
(
n
,
x
,
y
);
}
template
<
>
inline
void
vec_scal
<
float
>
(
const
int
n
,
const
float
a
,
float
*
x
)
{
platform
::
dynload
::
cblas_sscal
(
n
,
a
,
x
,
1
);
}
template
<
>
inline
void
vec_scal
<
double
>
(
const
int
n
,
const
double
a
,
double
*
x
)
{
platform
::
dynload
::
cblas_dscal
(
n
,
a
,
x
,
1
);
}
#endif
// MKL scal only support inplace, choose this if src and dst are not equal
template
<
typename
T
,
platform
::
jit
::
cpu_isa_t
isa
=
platform
::
jit
::
isa_any
>
inline
void
vec_scal
(
const
int
n
,
const
T
a
,
const
T
*
x
,
T
*
y
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
y
[
i
]
=
a
*
x
[
i
];
}
}
template
<
>
inline
void
vec_scal
<
float
,
platform
::
jit
::
avx
>
(
const
int
n
,
const
float
a
,
const
float
*
x
,
float
*
y
)
{
#ifdef __AVX__
constexpr
int
block
=
AVX_FLOAT_BLOCK
;
if
(
n
<
block
*
4
)
{
// use larger threshold, since small ones has no boost
vec_scal
<
float
,
platform
::
jit
::
isa_any
>
(
n
,
a
,
x
,
y
);
return
;
}
const
int
rest
=
n
%
block
;
const
int
end
=
n
-
rest
;
int
i
=
0
;
__m256
scalar
=
_mm256_set1_ps
(
a
);
__m256
tmp
;
#define MOVE_ONE_STEP \
tmp = _mm256_loadu_ps(x + i); \
tmp = _mm256_mul_ps(tmp, scalar); \
_mm256_storeu_ps(y + i, tmp)
for
(
i
=
0
;
i
<
end
;
i
+=
block
)
{
MOVE_ONE_STEP
;
}
#undef MOVE_ONE_STEP
if
(
rest
==
0
)
{
return
;
}
// can not continue move step if src and dst are inplace
for
(
i
=
n
-
rest
;
i
<
n
;
++
i
)
{
y
[
i
]
=
a
*
x
[
i
];
}
#else
vec_scal
<
float
,
platform
::
jit
::
isa_any
>
(
n
,
a
,
x
,
y
);
#endif
}
template
<
>
inline
void
vec_scal
<
float
,
platform
::
jit
::
avx2
>
(
const
int
n
,
const
float
a
,
const
float
*
x
,
float
*
y
)
{
vec_scal
<
float
,
platform
::
jit
::
avx
>
(
n
,
a
,
x
,
y
);
}
template
<
>
inline
void
vec_scal
<
float
,
platform
::
jit
::
avx512_common
>
(
const
int
n
,
const
float
a
,
const
float
*
x
,
float
*
y
)
{
// TODO(TJ): enable me
vec_scal
<
float
,
platform
::
jit
::
avx2
>
(
n
,
a
,
x
,
y
);
}
template
<
typename
T
,
platform
::
jit
::
cpu_isa_t
isa
=
platform
::
jit
::
isa_any
>
inline
void
vec_identity
(
const
int
n
,
const
T
*
x
,
T
*
y
)
{
...
...
@@ -82,7 +156,7 @@ inline void vec_sigmoid<float, platform::jit::avx>(const int n, const float* x,
float
*
y
)
{
#ifdef __AVX__
constexpr
int
block
=
AVX_FLOAT_BLOCK
;
if
(
n
<
block
)
{
// can use larger threshold if necessary
if
(
n
<
block
)
{
vec_sigmoid
<
float
,
platform
::
jit
::
isa_any
>
(
n
,
x
,
y
);
return
;
}
...
...
@@ -102,11 +176,15 @@ inline void vec_sigmoid<float, platform::jit::avx>(const int n, const float* x,
for
(
i
=
0
;
i
<
end
;
i
+=
block
)
{
MOVE_ONE_STEP
;
}
#undef MOVE_ONE_STEP
if
(
rest
!=
0
)
{
i
=
n
-
block
;
MOVE_ONE_STEP
;
// can not continue move step since the src and dst address could be equal
const
float
xmin
=
SIGMOID_THRESHOLD_MIN
;
const
float
xmax
=
SIGMOID_THRESHOLD_MAX
;
for
(
i
=
n
-
rest
;
i
<
n
;
++
i
)
{
y
[
i
]
=
0.
f
-
((
x
[
i
]
<
xmin
)
?
xmin
:
((
x
[
i
]
>
xmax
)
?
xmax
:
x
[
i
]));
}
}
#undef MOVE_ONE_STEP
vec_exp
<
float
>
(
n
,
y
,
y
);
...
...
@@ -142,65 +220,17 @@ template <>
inline
void
vec_sigmoid
<
float
,
platform
::
jit
::
avx512_common
>
(
const
int
n
,
const
float
*
x
,
float
*
y
)
{
#ifdef __AVX512F__
constexpr
int
block
=
AVX512_FLOAT_BLOCK
;
if
(
n
<
block
)
{
vec_sigmoid
<
float
,
platform
::
jit
::
isa_any
>
(
n
,
x
,
y
);
return
;
}
const
int
rest
=
n
%
block
;
const
int
end
=
n
-
rest
;
int
i
=
0
;
__m512
max
=
_mm512_set1_ps
(
SIGMOID_THRESHOLD_MAX
);
__m512
min
=
_mm512_set1_ps
(
SIGMOID_THRESHOLD_MIN
);
__m512
zeros
=
_mm512_setzero_ps
();
__m512
tmp
;
#define MOVE_ONE_STEP \
tmp = _mm512_loadu_ps(x + i); \
tmp = _mm512_max_ps(tmp, min); \
tmp = _mm512_min_ps(tmp, max); \
tmp = _mm512_sub_ps(zeros, tmp); \
_mm512_storeu_ps(y + i, tmp)
for
(
i
=
0
;
i
<
end
;
i
+=
block
)
{
MOVE_ONE_STEP
;
}
if
(
rest
!=
0
)
{
i
=
n
-
block
;
MOVE_ONE_STEP
;
}
#undef MOVE_ONE_STEP
vec_exp
<
float
>
(
n
,
y
,
y
);
__m512
ones
=
_mm512_set1_ps
(
1.0
f
);
#define MOVE_ONE_STEP \
tmp = _mm512_loadu_ps(y + i); \
tmp = _mm512_add_ps(ones, tmp); \
tmp = _mm512_div_ps(ones, tmp); \
_mm512_storeu_ps(y + i, tmp)
for
(
i
=
0
;
i
<
end
;
i
+=
block
)
{
MOVE_ONE_STEP
;
}
#undef MOVE_ONE_STEP
if
(
rest
==
0
)
{
return
;
}
for
(
i
=
n
-
rest
;
i
<
n
;
++
i
)
{
y
[
i
]
=
1.
f
/
(
1.
f
+
y
[
i
]);
}
#else
vec_sigmoid
<
float
,
platform
::
jit
::
isa_any
>
(
n
,
x
,
y
);
#endif
// TODO(TJ): enable me
vec_sigmoid
<
float
,
platform
::
jit
::
avx2
>
(
n
,
x
,
y
);
}
template
<
typename
T
,
platform
::
jit
::
cpu_isa_t
isa
=
platform
::
jit
::
isa_any
>
inline
void
vec_tanh
(
const
int
n
,
const
T
*
x
,
T
*
y
)
{
vec_scal
<
T
,
isa
>
(
n
,
static_cast
<
T
>
(
2
),
x
,
y
);
vec_sigmoid
<
T
,
isa
>
(
n
,
y
,
y
);
vec_scal
<
T
>
(
n
,
static_cast
<
T
>
(
2
),
y
);
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
y
[
i
]
=
static_cast
<
T
>
(
2
)
*
x
[
i
];
}
vec_sigmoid
<
T
>
(
n
,
y
,
y
);
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
y
[
i
]
=
static_cast
<
T
>
(
2
)
*
y
[
i
]
-
static_cast
<
T
>
(
1
);
y
[
i
]
=
y
[
i
]
-
static_cast
<
T
>
(
1
);
}
}
...
...
@@ -255,35 +285,10 @@ template <>
inline
void
vec_relu
<
float
,
platform
::
jit
::
avx512_common
>
(
const
int
n
,
const
float
*
x
,
float
*
y
)
{
#ifdef __AVX512F__
// test me
constexpr
int
block
=
AVX512_FLOAT_BLOCK
;
if
(
n
<
block
)
{
vec_relu
<
float
,
platform
::
jit
::
avx2
>
(
n
,
x
,
y
);
return
;
}
const
int
rest
=
n
%
block
;
const
int
end
=
n
-
rest
;
int
i
=
0
;
__m512
zeros
=
_mm512_setzero_ps
();
__m512
tmp
;
#define MOVE_ONE_STEP \
tmp = _mm512_loadu_ps(x + i); \
tmp = _mm512_max_ps(tmp, zeros); \
_mm512_storeu_ps(y + i, tmp)
for
(
i
=
0
;
i
<
end
;
i
+=
block
)
{
MOVE_ONE_STEP
;
}
if
(
rest
==
0
)
{
return
;
}
i
=
n
-
block
;
MOVE_ONE_STEP
;
#undef MOVE_ONE_STEP
#else
// TODO(TJ): enable me
vec_relu
<
float
,
platform
::
jit
::
avx2
>
(
n
,
x
,
y
);
#endif
}
// TODO(TJ): add vec add bias, make relu clip
// TODO(TJ): optimize double of sigmoid, tanh and relu if necessary
...
...
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