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gaoqiong
composable_kernel
Commits
f906b23d
Commit
f906b23d
authored
May 30, 2022
by
Anthony Chang
Browse files
account for extra flops/bytes from normalization
parent
9f6dbb55
Changes
1
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30 additions
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16 deletions
+30
-16
example/21_gemm_layernorm/gemm_xdl_layernorm_single_kernel_fp16.cpp
..._gemm_layernorm/gemm_xdl_layernorm_single_kernel_fp16.cpp
+30
-16
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example/21_gemm_layernorm/gemm_xdl_layernorm_single_kernel_fp16.cpp
View file @
f906b23d
...
...
@@ -26,18 +26,18 @@ using F32 = float;
using
Row
=
ck
::
tensor_layout
::
gemm
::
RowMajor
;
using
Col
=
ck
::
tensor_layout
::
gemm
::
ColumnMajor
;
using
ADataType
=
F16
;
using
BDataType
=
F16
;
using
CDataType
=
F16
;
using
ADataType
=
F16
;
using
BDataType
=
F16
;
using
CDataType
=
F16
;
using
AccDataType
=
F32
;
using
ALayout
=
ck
::
tensor_layout
::
gemm
::
RowMajor
;
using
BLayout
=
ck
::
tensor_layout
::
gemm
::
ColumnMajor
;
using
CLayout
=
ck
::
tensor_layout
::
gemm
::
RowMajor
;
using
AElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
BElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
CElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
AElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
BElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
CElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
static
constexpr
auto
GemmDefault
=
ck
::
tensor_operation
::
device
::
GemmSpecialization
::
Default
;
...
...
@@ -50,8 +50,13 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmLayerNorm_Xdl
<
Row
,
Col
,
Row
,
F16
,
F16
,
F16
,
AccDataType
,
AccDataType
,
AccDataType
,
AElementOp
,
BElementOp
,
CElementOp
,
GemmDefault
,
1
,
256
,
256
,
128
,
32
,
8
,
8
,
32
,
32
,
4
,
2
,
S
<
4
,
64
,
1
>
,
S
<
1
,
0
,
2
>
,
S
<
1
,
0
,
2
>
,
2
,
8
,
8
,
1
,
S
<
4
,
64
,
1
>
,
S
<
1
,
0
,
2
>
,
S
<
1
,
0
,
2
>
,
2
,
8
,
8
,
1
,
1
,
2
,
S
<
1
,
32
,
1
,
8
>
,
8
,
S
<
64
,
4
>
,
4
,
1
>
;
// clang-format on
using
ReferenceInstance
=
ck
::
tensor_operation
::
host
::
ReferenceGemmLayernorm
<
ADataType
,
BDataType
,
CDataType
,
AccDataType
,
AElementOp
,
BElementOp
,
CElementOp
>
;
using
ReferenceInstance
=
ck
::
tensor_operation
::
host
::
ReferenceGemmLayernorm
<
ADataType
,
BDataType
,
CDataType
,
AccDataType
,
AElementOp
,
BElementOp
,
CElementOp
>
;
int
main
(
int
argc
,
char
*
argv
[])
{
...
...
@@ -167,9 +172,9 @@ int main(int argc, char* argv[])
c0_gamma_buf
.
ToDevice
(
c0_n_gamma
.
mData
.
data
());
c0_beta_buf
.
ToDevice
(
c0_n_beta
.
mData
.
data
());
auto
a_element_op
=
AElementOp
{};
auto
b_element_op
=
BElementOp
{};
auto
c_element_op
=
CElementOp
{};
auto
a_element_op
=
AElementOp
{};
auto
b_element_op
=
BElementOp
{};
auto
c_element_op
=
CElementOp
{};
// do GEMM
auto
gemm
=
DeviceGemmInstance
{};
...
...
@@ -199,9 +204,11 @@ int main(int argc, char* argv[])
float
ave_time
=
invoker
.
Run
(
argument
,
StreamConfig
{
nullptr
,
time_kernel
});
std
::
size_t
flop
=
std
::
size_t
(
2
)
*
M
*
N
*
K
;
std
::
size_t
num_btype
=
sizeof
(
ADataType
)
*
M
*
K
+
sizeof
(
BDataType
)
*
K
*
N
+
sizeof
(
CDataType
)
*
M
*
N
;
// extra 5MN flops due to: bias + gamma + beta + norm_sub + norm_div,
// excluding reduction steps
std
::
size_t
flop
=
std
::
size_t
(
2
)
*
M
*
N
*
K
+
std
::
size_t
(
5
)
*
M
*
N
;
std
::
size_t
num_btype
=
sizeof
(
ADataType
)
*
M
*
K
+
sizeof
(
BDataType
)
*
K
*
N
+
sizeof
(
CDataType
)
*
M
*
N
+
sizeof
(
CDataType
)
*
3
*
N
;
float
tflops
=
static_cast
<
float
>
(
flop
)
/
1.E9
/
ave_time
;
...
...
@@ -218,8 +225,15 @@ int main(int argc, char* argv[])
auto
ref_gemm
=
ReferenceInstance
{};
auto
ref_invoker
=
ref_gemm
.
MakeInvoker
();
auto
ref_argument
=
ref_gemm
.
MakeArgument
(
a_m_k
,
b_k_n
,
c0_n_bias
,
c0_n_gamma
,
c0_n_beta
,
c_m_n_host_result
,
a_element_op
,
b_element_op
,
c_element_op
);
auto
ref_argument
=
ref_gemm
.
MakeArgument
(
a_m_k
,
b_k_n
,
c0_n_bias
,
c0_n_gamma
,
c0_n_beta
,
c_m_n_host_result
,
a_element_op
,
b_element_op
,
c_element_op
);
ref_invoker
.
Run
(
ref_argument
);
...
...
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