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体验新版 GitCode,发现更多精彩内容 >>
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提交
a7a4843c
编写于
6月 29, 2022
作者:
Z
zmxdream
提交者:
GitHub
6月 29, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[GPUPS]Optimize dymf kernel (#43911)
上级
aa45f931
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
217 addition
and
42 deletion
+217
-42
paddle/fluid/framework/fleet/heter_ps/hashtable_kernel.cu
paddle/fluid/framework/fleet/heter_ps/hashtable_kernel.cu
+32
-19
paddle/fluid/framework/fleet/heter_ps/heter_comm_inl.h
paddle/fluid/framework/fleet/heter_ps/heter_comm_inl.h
+1
-0
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.cu
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.cu
+158
-16
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.h
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.h
+26
-7
未找到文件。
paddle/fluid/framework/fleet/heter_ps/hashtable_kernel.cu
浏览文件 @
a7a4843c
...
@@ -89,31 +89,42 @@ __global__ void dy_mf_search_kernel(Table* table,
...
@@ -89,31 +89,42 @@ __global__ void dy_mf_search_kernel(Table* table,
char
*
vals
,
char
*
vals
,
size_t
len
,
size_t
len
,
size_t
pull_feature_value_size
)
{
size_t
pull_feature_value_size
)
{
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
y
+
threadIdx
.
y
;
// return
;
const
size_t
k
=
threadIdx
.
x
;
if
(
i
<
len
)
{
if
(
i
<
len
)
{
auto
it
=
table
->
find
(
keys
[
i
]);
auto
it
=
table
->
find
(
keys
[
i
]);
if
(
it
!=
table
->
end
())
{
if
(
it
!=
table
->
end
())
{
uint64_t
offset
=
i
*
pull_feature_value_size
;
uint64_t
offset
=
i
*
pull_feature_value_size
;
FeatureValue
*
cur
=
(
FeatureValue
*
)(
vals
+
offset
);
FeatureValue
*
cur
=
(
FeatureValue
*
)(
vals
+
offset
);
FeatureValue
&
input
=
*
(
FeatureValue
*
)(
it
->
second
);
FeatureValue
&
input
=
*
(
FeatureValue
*
)(
it
->
second
);
cur
->
slot
=
input
.
slot
;
char
*
cur_p
=
(
char
*
)
cur
;
cur
->
show
=
input
.
show
;
char
*
input_p
=
(
char
*
)(
&
input
);
cur
->
clk
=
input
.
clk
;
int
len
=
9
+
input
.
mf_dim
+
1
;
cur
->
mf_dim
=
input
.
mf_dim
;
if
(
k
==
3
||
k
==
6
||
k
==
7
)
cur
->
lr
=
input
.
lr
;
*
(
int
*
)(
cur_p
+
k
*
4
)
=
*
(
int
*
)(
input_p
+
k
*
4
);
cur
->
mf_size
=
input
.
mf_size
;
else
if
(
k
<
8
)
cur
->
cpu_ptr
=
input
.
cpu_ptr
;
*
(
float
*
)(
cur_p
+
k
*
4
)
=
*
(
float
*
)(
input_p
+
k
*
4
);
cur
->
delta_score
=
input
.
delta_score
;
else
if
(
k
==
8
)
{
cur
->
lr_g2sum
=
input
.
lr_g2sum
;
*
(
uint64_t
*
)(
cur_p
+
k
*
4
)
=
*
(
uint64_t
*
)(
input_p
+
k
*
4
);
for
(
int
j
=
0
;
j
<
cur
->
mf_dim
+
1
;
++
j
)
{
}
else
{
cur
->
mf
[
j
]
=
input
.
mf
[
j
];
int
len_per_thread
=
(
len
-
9
)
/
(
blockDim
.
y
-
9
);
int
remain
=
(
len
-
9
)
%
(
blockDim
.
y
-
9
);
int
real_len
=
len_per_thread
;
if
((
k
-
9
)
<
remain
)
real_len
++
;
int
left
=
-
1
,
right
=
-
1
;
if
((
k
-
9
)
<
remain
)
{
left
=
9
+
(
k
-
9
)
*
(
len_per_thread
+
1
);
right
=
left
+
real_len
;
}
else
{
left
=
9
+
remain
*
(
len_per_thread
+
1
)
+
(
k
-
9
-
remain
)
*
len_per_thread
;
right
=
left
+
real_len
;
}
for
(
int
j
=
left
;
j
<
right
;
j
++
)
*
(
float
*
)(
cur_p
+
(
j
+
1
)
*
4
)
=
*
(
float
*
)(
input_p
+
(
j
+
1
)
*
4
);
}
}
}
else
{
}
else
{
if
(
keys
[
i
]
!=
0
)
{
if
(
keys
[
i
]
!=
0
)
printf
(
"pull miss key: %llu"
,
keys
[
i
]);
printf
(
"warning::pull miss key: %llu"
,
keys
[
i
]);
}
}
}
}
}
}
}
...
@@ -220,8 +231,10 @@ void HashTable<KeyType, ValType>::get(const KeyType* d_keys,
...
@@ -220,8 +231,10 @@ void HashTable<KeyType, ValType>::get(const KeyType* d_keys,
if
(
len
==
0
)
{
if
(
len
==
0
)
{
return
;
return
;
}
}
const
int
grid_size
=
(
len
-
1
)
/
BLOCK_SIZE_
+
1
;
dim3
block_dims
(
32
,
32
);
dy_mf_search_kernel
<<<
grid_size
,
BLOCK_SIZE_
,
0
,
stream
>>>
(
const
int
grid_size
=
(
len
-
1
)
/
32
+
1
;
dim3
grid_dims
(
grid_size
);
dy_mf_search_kernel
<<<
grid_dims
,
block_dims
,
0
,
stream
>>>
(
container_
,
d_keys
,
d_vals
,
len
,
pull_feature_value_size_
);
container_
,
d_keys
,
d_vals
,
len
,
pull_feature_value_size_
);
}
}
...
...
paddle/fluid/framework/fleet/heter_ps/heter_comm_inl.h
浏览文件 @
a7a4843c
...
@@ -760,6 +760,7 @@ void HeterComm<KeyType, ValType, GradType>::dynamic_merge_grad(
...
@@ -760,6 +760,7 @@ void HeterComm<KeyType, ValType, GradType>::dynamic_merge_grad(
(
char
*
)
d_grads
,
(
char
*
)
d_grads
,
(
char
*
)
d_merge_grads_ptr
,
(
char
*
)
d_merge_grads_ptr
,
uniq_len
,
uniq_len
,
max_mf_dim_
,
grad_value_size
,
grad_value_size
,
merger_
,
merger_
,
stream
);
stream
);
...
...
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.cu
浏览文件 @
a7a4843c
...
@@ -144,28 +144,106 @@ __global__ void dy_mf_fill_shard_grads_kernel(KeyType* d_shard_keys,
...
@@ -144,28 +144,106 @@ __global__ void dy_mf_fill_shard_grads_kernel(KeyType* d_shard_keys,
}
}
}
}
__global__
void
merge_gradients_kernel
(
const
uint32_t
*
offset
,
// optimized version
const
uint32_t
*
fea_num
,
template
<
>
const
uint32_t
*
index
,
__global__
void
const
char
*
input
,
dy_mf_fill_shard_grads_kernel
<
FeatureKey
,
FeaturePushValue
,
int
>
(
char
*
output
,
FeatureKey
*
d_shard_keys
,
int
n
,
FeatureKey
*
d_keys
,
size_t
grad_value_size
,
FeaturePushValue
*
d_shard_grads
,
DynamicGradMerger
&
merger_
)
{
FeaturePushValue
*
d_grads
,
int
*
idx
,
size_t
len
,
size_t
grad_value_size
)
{
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
y
+
threadIdx
.
y
;
const
size_t
k
=
threadIdx
.
x
;
if
(
i
<
len
)
{
if
(
k
==
0
)
{
d_shard_keys
[
i
]
=
d_keys
[
idx
[
i
]];
}
FeaturePushValue
*
cur
=
(
FeaturePushValue
*
)((
char
*
)
d_shard_grads
+
i
*
grad_value_size
);
FeaturePushValue
&
input
=
*
(
FeaturePushValue
*
)((
char
*
)
d_grads
+
uint64_t
(
idx
[
i
])
*
grad_value_size
);
char
*
cur_p
=
(
char
*
)
cur
;
char
*
input_p
=
(
char
*
)(
&
input
);
int
len
=
5
+
input
.
mf_dim
;
if
(
k
==
2
||
k
==
4
)
*
(
int
*
)(
cur_p
+
k
*
4
)
=
*
(
int
*
)(
input_p
+
k
*
4
);
else
if
(
k
<
5
)
*
(
float
*
)(
cur_p
+
k
*
4
)
=
*
(
float
*
)(
input_p
+
k
*
4
);
else
{
int
len_per_thread
=
(
len
-
5
)
/
(
blockDim
.
y
-
5
);
int
remain
=
(
len
-
5
)
%
(
blockDim
.
y
-
5
);
int
real_len
=
len_per_thread
;
if
((
k
-
5
)
<
remain
)
real_len
++
;
int
left
=
-
1
,
right
=
-
1
;
if
((
k
-
5
)
<
remain
)
{
left
=
5
+
(
k
-
5
)
*
(
len_per_thread
+
1
);
right
=
left
+
real_len
;
}
else
{
left
=
5
+
remain
*
(
len_per_thread
+
1
)
+
(
k
-
5
-
remain
)
*
len_per_thread
;
right
=
left
+
real_len
;
}
for
(
int
j
=
left
;
j
<
right
;
j
++
)
*
(
float
*
)(
cur_p
+
j
*
4
)
=
*
(
float
*
)(
input_p
+
j
*
4
);
}
}
}
__global__
void
merge_gradients_basic_kernel
(
const
uint32_t
*
offset
,
const
uint32_t
*
fea_num
,
const
uint32_t
*
index
,
const
char
*
input
,
char
*
output
,
int
n
,
size_t
grad_value_size
,
DynamicGradMerger
&
merger
)
{
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
i
<
n
)
{
if
(
i
<
n
)
{
uint32_t
start
=
offset
[
i
];
uint32_t
start
=
offset
[
i
];
uint32_t
num
=
fea_num
[
i
];
uint32_t
num
=
fea_num
[
i
];
int
ori_index
=
index
[
start
];
int
ori_index
=
index
[
start
];
FeaturePushValue
&
out
=
*
(
FeaturePushValue
*
)(
output
+
i
*
grad_value_size
);
FeaturePushValue
&
lhs
=
*
(
FeaturePushValue
*
)(
output
+
i
*
grad_value_size
);
FeaturePushValue
&
in
=
FeaturePushValue
&
in
=
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
merger
_
.
update_one
(
out
,
in
);
merger
.
update_basic
(
lhs
,
in
);
for
(
int
j
=
1
;
j
<
num
;
++
j
)
{
for
(
int
j
=
1
;
j
<
num
;
++
j
)
{
ori_index
=
index
[
start
+
j
];
ori_index
=
index
[
start
+
j
];
FeaturePushValue
&
rhs
=
FeaturePushValue
&
rhs
=
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
merger_
.
merge_one
(
out
,
rhs
);
merger
.
merge_basic
(
lhs
,
rhs
);
}
}
}
__global__
void
merge_gradients_embedx_kernel
(
const
uint32_t
*
offset
,
const
uint32_t
*
fea_num
,
const
uint32_t
*
index
,
const
char
*
input
,
char
*
output
,
int
n
,
size_t
grad_dim
,
size_t
grad_value_size
,
DynamicGradMerger
&
merger
)
{
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
i
<
n
)
{
size_t
value_idx
=
i
/
grad_dim
;
size_t
field_idx
=
i
%
grad_dim
;
uint32_t
start
=
offset
[
value_idx
];
uint32_t
num
=
fea_num
[
value_idx
];
int
ori_index
=
index
[
start
];
FeaturePushValue
&
in
=
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
FeaturePushValue
&
lhs
=
*
(
FeaturePushValue
*
)(
output
+
value_idx
*
grad_value_size
);
merger
.
update_embedx
(
lhs
,
in
,
field_idx
);
for
(
int
j
=
1
;
j
<
num
;
++
j
)
{
int
ori_index
=
index
[
start
+
j
];
FeaturePushValue
&
rhs
=
*
(
FeaturePushValue
*
)(
input
+
size_t
(
ori_index
)
*
grad_value_size
);
merger
.
merge_embedx
(
lhs
,
rhs
,
field_idx
);
}
}
}
}
}
}
...
@@ -184,6 +262,49 @@ __global__ void dy_mf_fill_dvals_kernel(ValType* d_shard_vals,
...
@@ -184,6 +262,49 @@ __global__ void dy_mf_fill_dvals_kernel(ValType* d_shard_vals,
}
}
}
}
// optimized version
template
<
>
__global__
void
dy_mf_fill_dvals_kernel
<
FeatureValue
,
int
>
(
FeatureValue
*
d_shard_vals
,
FeatureValue
*
d_vals
,
int
*
idx
,
size_t
len
,
size_t
val_size
)
{
const
size_t
i
=
blockIdx
.
x
*
blockDim
.
y
+
threadIdx
.
y
;
const
size_t
k
=
threadIdx
.
x
;
if
(
i
<
len
)
{
uint64_t
new_offset
=
uint64_t
(
idx
[
i
])
*
val_size
;
FeatureValue
*
cur
=
(
FeatureValue
*
)((
char
*
)
d_vals
+
new_offset
);
FeatureValue
&
input
=
*
(
FeatureValue
*
)((
char
*
)
d_shard_vals
+
i
*
val_size
);
char
*
cur_p
=
(
char
*
)
cur
;
char
*
input_p
=
(
char
*
)(
&
input
);
int
len
=
9
+
input
.
mf_dim
+
1
;
if
(
k
==
3
||
k
==
6
||
k
==
7
)
*
(
int
*
)(
cur_p
+
k
*
4
)
=
*
(
int
*
)(
input_p
+
k
*
4
);
else
if
(
k
<
8
)
*
(
float
*
)(
cur_p
+
k
*
4
)
=
*
(
float
*
)(
input_p
+
k
*
4
);
else
if
(
k
==
8
)
{
*
(
uint64_t
*
)(
cur_p
+
k
*
4
)
=
*
(
uint64_t
*
)(
input_p
+
k
*
4
);
}
else
{
int
len_per_thread
=
(
len
-
9
)
/
(
blockDim
.
x
-
9
);
int
remain
=
(
len
-
9
)
%
(
blockDim
.
y
-
9
);
int
real_len
=
len_per_thread
;
if
((
k
-
9
)
<
remain
)
real_len
++
;
int
left
=
-
1
,
right
=
-
1
;
if
((
k
-
9
)
<
remain
)
{
left
=
9
+
(
k
-
9
)
*
(
len_per_thread
+
1
);
right
=
left
+
real_len
;
}
else
{
left
=
9
+
remain
*
(
len_per_thread
+
1
)
+
(
k
-
9
-
remain
)
*
len_per_thread
;
right
=
left
+
real_len
;
}
for
(
int
j
=
left
;
j
<
right
;
j
++
)
*
(
float
*
)(
cur_p
+
(
j
+
1
)
*
4
)
=
*
(
float
*
)(
input_p
+
(
j
+
1
)
*
4
);
}
}
}
// cuda implemention of heter_comm_kernel.h
// cuda implemention of heter_comm_kernel.h
template
<
typename
T
,
typename
StreamType
>
template
<
typename
T
,
typename
StreamType
>
void
HeterCommKernel
::
fill_idx
(
T
*
idx
,
void
HeterCommKernel
::
fill_idx
(
T
*
idx
,
...
@@ -321,9 +442,12 @@ void HeterCommKernel::dy_mf_fill_shard_grads(KeyType* d_shard_keys,
...
@@ -321,9 +442,12 @@ void HeterCommKernel::dy_mf_fill_shard_grads(KeyType* d_shard_keys,
long
long
len
,
long
long
len
,
size_t
grad_value_size
,
size_t
grad_value_size
,
const
StreamType
&
stream
)
{
const
StreamType
&
stream
)
{
int
grid_size
=
(
len
-
1
)
/
block_size_
+
1
;
//
int grid_size = (len - 1) / block_size_ + 1;
size_t
c_len
=
(
size_t
)
len
;
size_t
c_len
=
(
size_t
)
len
;
dy_mf_fill_shard_grads_kernel
<<<
grid_size
,
block_size_
,
0
,
stream
>>>
(
dim3
block_dims
(
32
,
32
);
const
size_t
grid_size
=
(
len
-
1
)
/
32
+
1
;
dim3
grid_dims
(
grid_size
);
dy_mf_fill_shard_grads_kernel
<<<
grid_dims
,
block_dims
,
0
,
stream
>>>
(
d_shard_keys
,
d_shard_keys
,
d_keys
,
d_keys
,
d_shard_grads
,
d_shard_grads
,
...
@@ -340,12 +464,26 @@ void HeterCommKernel::merge_gradient(const uint32_t* offset,
...
@@ -340,12 +464,26 @@ void HeterCommKernel::merge_gradient(const uint32_t* offset,
const
char
*
input
,
const
char
*
input
,
char
*
output
,
char
*
output
,
int
n
,
int
n
,
size_t
grad_dim
,
size_t
grad_value_size
,
size_t
grad_value_size
,
DynamicGradMerger
&
merger_
,
DynamicGradMerger
&
merger_
,
const
StreamType
&
stream
)
{
const
StreamType
&
stream
)
{
int
grid_size
=
(
n
-
1
)
/
block_size_
+
1
;
int
grid_size
=
(
n
-
1
)
/
block_size_
+
1
;
merge_gradients_kernel
<<<
grid_size
,
block_size_
,
0
,
stream
>>>
(
merge_gradients_
basic_
kernel
<<<
grid_size
,
block_size_
,
0
,
stream
>>>
(
offset
,
fea_num
,
index
,
input
,
output
,
n
,
grad_value_size
,
merger_
);
offset
,
fea_num
,
index
,
input
,
output
,
n
,
grad_value_size
,
merger_
);
if
(
grad_dim
>
0
)
{
int
grid_size2
=
(
n
*
grad_dim
-
1
)
/
block_size_
+
1
;
merge_gradients_embedx_kernel
<<<
grid_size2
,
block_size_
,
0
,
stream
>>>
(
offset
,
fea_num
,
index
,
input
,
output
,
n
*
grad_dim
,
grad_dim
,
grad_value_size
,
merger_
);
}
}
}
template
<
typename
ValType
,
typename
T
,
typename
StreamType
>
template
<
typename
ValType
,
typename
T
,
typename
StreamType
>
...
@@ -355,9 +493,12 @@ void HeterCommKernel::dy_mf_fill_dvals(ValType* d_shard_vals,
...
@@ -355,9 +493,12 @@ void HeterCommKernel::dy_mf_fill_dvals(ValType* d_shard_vals,
long
long
len
,
long
long
len
,
size_t
val_size
,
size_t
val_size
,
const
StreamType
&
stream
)
{
const
StreamType
&
stream
)
{
int
grid_size
=
(
len
-
1
)
/
block_size_
+
1
;
//
int grid_size = (len - 1) / block_size_ + 1;
size_t
c_len
=
(
size_t
)
len
;
size_t
c_len
=
(
size_t
)
len
;
dy_mf_fill_dvals_kernel
<<<
grid_size
,
block_size_
,
0
,
stream
>>>
(
dim3
block_dims
(
32
,
32
);
const
size_t
grid_size_
=
(
len
-
1
)
/
32
+
1
;
dim3
grid_dims
(
grid_size_
);
dy_mf_fill_dvals_kernel
<<<
grid_dims
,
block_dims
,
0
,
stream
>>>
(
d_shard_vals
,
d_vals
,
idx
,
c_len
,
val_size
);
d_shard_vals
,
d_vals
,
idx
,
c_len
,
val_size
);
}
}
...
@@ -487,6 +628,7 @@ template void HeterCommKernel::merge_gradient<cudaStream_t>(
...
@@ -487,6 +628,7 @@ template void HeterCommKernel::merge_gradient<cudaStream_t>(
const
char
*
input
,
const
char
*
input
,
char
*
output
,
char
*
output
,
int
n
,
int
n
,
size_t
grad_dim
,
size_t
grad_value_size
,
size_t
grad_value_size
,
DynamicGradMerger
&
merger_
,
DynamicGradMerger
&
merger_
,
const
cudaStream_t
&
stream
);
const
cudaStream_t
&
stream
);
...
...
paddle/fluid/framework/fleet/heter_ps/heter_comm_kernel.h
浏览文件 @
a7a4843c
...
@@ -42,23 +42,41 @@ struct DynamicGradMerger {
...
@@ -42,23 +42,41 @@ struct DynamicGradMerger {
}
}
template
<
typename
T
>
template
<
typename
T
>
__device__
__forceinline__
void
update_
one
(
T
&
output
,
const
T
&
input
)
{
__device__
__forceinline__
void
update_
basic
(
T
&
output
,
const
T
&
input
)
{
output
.
slot
=
input
.
slot
;
output
.
slot
=
input
.
slot
;
output
.
show
=
input
.
show
;
output
.
show
=
input
.
show
;
output
.
clk
=
input
.
clk
;
output
.
clk
=
input
.
clk
;
output
.
mf_dim
=
input
.
mf_dim
;
output
.
mf_dim
=
input
.
mf_dim
;
output
.
lr_g
=
input
.
lr_g
;
output
.
lr_g
=
input
.
lr_g
;
for
(
int
i
=
0
;
i
<
output
.
mf_dim
;
++
i
)
{
//
for (int i = 0; i < output.mf_dim; ++i) {
output
.
mf_g
[
i
]
=
input
.
mf_g
[
i
];
//
output.mf_g[i] = input.mf_g[i];
}
//
}
}
}
template
<
typename
T
>
template
<
typename
T
>
__device__
__forceinline__
void
merge_
one
(
T
&
output
,
const
T
&
input
)
{
__device__
__forceinline__
void
merge_
basic
(
T
&
output
,
const
T
&
input
)
{
output
.
show
+=
input
.
show
;
output
.
show
+=
input
.
show
;
output
.
clk
+=
input
.
clk
;
output
.
clk
+=
input
.
clk
;
output
.
lr_g
+=
input
.
lr_g
;
output
.
lr_g
+=
input
.
lr_g
;
for
(
int
i
=
0
;
i
<
input
.
mf_dim
;
++
i
)
{
// for (int i = 0; i < input.mf_dim; ++i) {
output
.
mf_g
[
i
]
+=
input
.
mf_g
[
i
];
// output.mf_g[i] += input.mf_g[i];
//}
}
template
<
typename
T
>
__device__
__forceinline__
void
update_embedx
(
T
&
output
,
const
T
&
input
,
size_t
embedx_id
)
{
if
(
embedx_id
<
output
.
mf_dim
)
{
output
.
mf_g
[
embedx_id
]
=
input
.
mf_g
[
embedx_id
];
}
}
template
<
typename
T
>
__device__
__forceinline__
void
merge_embedx
(
T
&
output
,
const
T
&
input
,
size_t
embedx_id
)
{
if
(
embedx_id
<
output
.
mf_dim
)
{
output
.
mf_g
[
embedx_id
]
+=
input
.
mf_g
[
embedx_id
];
}
}
}
}
};
};
...
@@ -165,6 +183,7 @@ class HeterCommKernel {
...
@@ -165,6 +183,7 @@ class HeterCommKernel {
const
char
*
input
,
const
char
*
input
,
char
*
output
,
char
*
output
,
int
n
,
int
n
,
size_t
grad_dim
,
size_t
grad_value_size
,
size_t
grad_value_size
,
DynamicGradMerger
&
merger_
,
DynamicGradMerger
&
merger_
,
const
StreamType
&
stream
);
const
StreamType
&
stream
);
...
...
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