未验证 提交 f077276f 编写于 作者: X xiebaiyuan 提交者: GitHub

optimise conv 1x1 ... ,test=develop (#2388)

optimise conv 1x1 ... ,test=develop (#2388)
上级 e74609b7
......@@ -1006,8 +1006,160 @@ __kernel void conv_1x1(__private const int global_size_dim0,
write_imageh(output_image, output_pos, output);
}
__kernel void conv_1x1_simple(
__private const int global_size_dim0, __private const int global_size_dim1,
__private const int global_size_dim2, __read_only image2d_t input_image,
__read_only image2d_t filter,
#if defined(BIASE_CH) || defined(BIASE_ELE)
__read_only image2d_t bias,
#endif
#ifdef BATCH_NORM
__read_only image2d_t new_scale, __read_only image2d_t new_biase,
#endif
__write_only image2d_t output_image, __private const int stride,
__private const int offset, __private const int input_c,__private const int input_c_origin,
__private const int dilation,
__private const int input_width, /* of one block */
__private const int input_height, /* of one block */
__private const int output_width,
__private const int output_height,
__private const int old_w
) {
half zero = 0.0f;
const int out_c = get_global_id(0);
const int out_w = get_global_id(1);
const int out_nh = get_global_id(2);
int out_w0 = out_w;
int out_w1 = out_w + global_size_dim1;
int out_w2 = out_w + global_size_dim1 * 2;
int out_w3 = out_w + global_size_dim1 * 3;
int outpos_main = mul24(out_c , old_w);
int2 output_pos0 = (int2)(outpos_main + out_w0, out_nh);
int2 output_pos1 = (int2)(outpos_main + out_w1, out_nh);
int2 output_pos2 = (int2)(outpos_main + out_w2, out_nh);
int2 output_pos3 = (int2)(outpos_main + out_w3, out_nh);
const sampler_t sampler =
CLK_NORMALIZED_COORDS_TRUE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
int2 stride_xy = (int2)(stride, stride);
int2 ouput_pos_in_one_block0 = (int2)(out_w0, out_nh);
int2 in_pos_in_one_block0 =
ouput_pos_in_one_block0 * stride_xy + (int2)(offset, offset);
int2 ouput_pos_in_one_block1 = (int2)(out_w1, out_nh);
int2 in_pos_in_one_block1 =
ouput_pos_in_one_block1 * stride_xy + (int2)(offset, offset);
int2 ouput_pos_in_one_block2 = (int2)(out_w2, out_nh);
int2 in_pos_in_one_block2 =
ouput_pos_in_one_block2 * stride_xy + (int2)(offset, offset);
__kernel void conv_1x1_spl(
int2 ouput_pos_in_one_block3 = (int2)(out_w3, out_nh);
int2 in_pos_in_one_block3 =
ouput_pos_in_one_block3 * stride_xy + (int2)(offset, offset);
#ifdef BIASE_CH
half4 output0 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output1 = output0;
half4 output2 = output0;
half4 output3 = output0;
#elif defined(BIASE_ELE)
half4 output0 = read_imageh(bias, sampler, output_pos0);
half4 output1 = output0;
half4 output2 = output0;
half4 output3 = output0;
#else
half4 output0 = 0.0f;
half4 output1 = 0.0f;
half4 output2 = 0.0f;
half4 output3 = 0.0f;
#endif
for (int i = 0; i < input_c; ++i) {
// ------------0---------------
int2 pos_in = (int2)(i * input_width + in_pos_in_one_block0.x, in_pos_in_one_block0.y);
half4 input0 = read_imageh(input_image, sampler, pos_in);
half4 weight0 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 0));
half4 weight1 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 1));
half4 weight2 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 2));
half4 weight3 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 3));
output0 = mad(input0.x, weight0, output0);
output0 = mad(input0.y, weight1, output0);
output0 = mad(input0.z, weight2, output0);
output0 = mad(input0.w, weight3, output0);
// -------------1--------------
pos_in = (int2)(i * input_width + in_pos_in_one_block1.x, in_pos_in_one_block1.y);
half4 input1 = read_imageh(input_image, sampler, pos_in);
output1 = mad(input1.x, weight0, output1);
output1 = mad(input1.y, weight1, output1);
output1 = mad(input1.z, weight2, output1);
output1 = mad(input1.w, weight3, output1);
// -------------2--------------
pos_in = (int2)(i * input_width + in_pos_in_one_block2.x, in_pos_in_one_block2.y);
half4 input2 = read_imageh(input_image, sampler, pos_in);
output2 = mad(input2.x, weight0, output2);
output2 = mad(input2.y, weight1, output2);
output2 = mad(input2.z, weight2, output2);
output2 = mad(input2.w, weight3, output2);
// -------------3--------------
pos_in = (int2)(i * input_width + in_pos_in_one_block3.x, in_pos_in_one_block3.y);
half4 input3 = read_imageh(input_image, sampler, pos_in);
output3 = mad(input3.x, weight0, output3);
output3 = mad(input3.y, weight1, output3);
output3 = mad(input3.z, weight2, output3);
output3 = mad(input3.w, weight3, output3);
}
#ifdef BATCH_NORM
output0 = output0 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
read_imageh(new_biase, sampler, (int2)(out_c, 0));
output1 = output1 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
read_imageh(new_biase, sampler, (int2)(out_c, 0));
output2 = output2 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
read_imageh(new_biase, sampler, (int2)(out_c, 0));
output3 = output3 * read_imageh(new_scale, sampler, (int2)(out_c, 0)) +
read_imageh(new_biase, sampler, (int2)(out_c, 0));
#endif
#ifdef RELU
output0 = activation(output0);
output1 = activation(output1);
output2 = activation(output2);
output3 = activation(output3);
#endif
if (out_w0 < old_w) {
write_imageh(output_image, output_pos0, output0);
}
if (out_w1 < old_w){
write_imageh(output_image, output_pos1, output1);
}
if (out_w2 < old_w){
write_imageh(output_image, output_pos2, output2);
}
if (out_w3 < old_w){
write_imageh(output_image, output_pos3, output3);
}
}
__kernel void conv_1x1_wrapped(
__private const int global_size_dim0, __private const int global_size_dim1,
__private const int global_size_dim2, __read_only image2d_t input_image,
__read_only image2d_t filter,
......@@ -1026,7 +1178,7 @@ __kernel void conv_1x1_spl(
__private const int output_height,
__private const int old_w
) {
half zero = 0.0f;
const int out_c = get_global_id(0);
const int out_w = get_global_id(1);
const int out_nh = get_global_id(2);
......@@ -1065,14 +1217,14 @@ __kernel void conv_1x1_spl(
#ifdef BIASE_CH
half4 output0 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output1 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output2 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output3 = read_imageh(bias, sampler, (int2)(out_c, 0));
half4 output1 = output0;
half4 output2 = output0;
half4 output3 = output0;
#elif defined(BIASE_ELE)
half4 output0 = read_imageh(bias, sampler, output_pos0);
half4 output1 = read_imageh(bias, sampler, output_pos1);
half4 output2 = read_imageh(bias, sampler, output_pos2);
half4 output3 = read_imageh(bias, sampler, output_pos3);
half4 output1 = output0;
half4 output2 = output0;
half4 output3 = output0;
#else
half4 output0 = 0.0f;
......@@ -1083,6 +1235,10 @@ __kernel void conv_1x1_spl(
int max_w_bound = input_c * input_width;
int burndary_index = input_c * 4 - input_c_origin;
bool burndary_index_w = burndary_index==1||burndary_index==2||burndary_index==3;
bool burndary_index_z = burndary_index==2||burndary_index==3;
bool burndary_index_y = burndary_index==3;
for (int i = 0; i < input_c; ++i) {
// ------------0---------------
int2 pos_in = (int2)(i * input_width + in_pos_in_one_block0.x, in_pos_in_one_block0.y);
......@@ -1092,22 +1248,13 @@ __kernel void conv_1x1_spl(
half4 weight1 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 1));
half4 weight2 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 2));
half4 weight3 = read_imageh(filter, sampler, (int2)(out_c, i * 4 + 3));
int bound_gap = max_w_bound - pos_in.x - 1;
if (bound_gap < input_width && bound_gap >= 0){
if (burndary_index==0){
// do nothing
} else if (burndary_index==1){
input0.w = 0.0f;
} else if (burndary_index==2){
input0.z = 0.0f;
input0.w = 0.0f;
} else if (burndary_index==3){
input0.y = 0.0f;
input0.z = 0.0f;
input0.w = 0.0f;
}
}
bool outof_bound = bound_gap < input_width && bound_gap >= 0;
input0.w = select(input0.w,zero,outof_bound && burndary_index_w);
input0.z = select(input0.z,zero,outof_bound && burndary_index_z);
input0.y = select(input0.y,zero,outof_bound && burndary_index_y);
output0 = mad(input0.x, weight0, output0);
output0 = mad(input0.y, weight1, output0);
output0 = mad(input0.z, weight2, output0);
......@@ -1117,20 +1264,12 @@ __kernel void conv_1x1_spl(
half4 input1 = read_imageh(input_image, sampler, pos_in);
bound_gap = max_w_bound - pos_in.x - 1;
if (bound_gap < input_width && bound_gap >= 0){
if (burndary_index==0){
// do nothing
} else if (burndary_index==1){
input1.w = 0.0f;
} else if (burndary_index==2){
input1.z = 0.0f;
input1.w = 0.0f;
} else if (burndary_index==3){
input1.y = 0.0f;
input1.z = 0.0f;
input1.w = 0.0f;
}
}
outof_bound = bound_gap < input_width && bound_gap >= 0;
input1.w = select(input1.w,zero,outof_bound && burndary_index_w);
input1.z = select(input1.z,zero,outof_bound && burndary_index_z);
input1.y = select(input1.y,zero,outof_bound && burndary_index_y);
output1 = mad(input1.x, weight0, output1);
output1 = mad(input1.y, weight1, output1);
output1 = mad(input1.z, weight2, output1);
......@@ -1141,20 +1280,12 @@ __kernel void conv_1x1_spl(
half4 input2 = read_imageh(input_image, sampler, pos_in);
bound_gap = max_w_bound - pos_in.x - 1;
if (bound_gap < input_width && bound_gap >= 0){
if (burndary_index==0){
// do nothing
} else if (burndary_index==1){
input2.w = 0.0f;
} else if (burndary_index==2){
input2.z = 0.0f;
input2.w = 0.0f;
} else if (burndary_index==3){
input2.y = 0.0f;
input2.z = 0.0f;
input2.w = 0.0f;
}
}
outof_bound = bound_gap < input_width && bound_gap >= 0;
input2.w = select(input2.w,zero,outof_bound && burndary_index_w);
input2.z = select(input2.z,zero,outof_bound && burndary_index_z);
input2.y = select(input2.y,zero,outof_bound && burndary_index_y);
output2 = mad(input2.x, weight0, output2);
output2 = mad(input2.y, weight1, output2);
output2 = mad(input2.z, weight2, output2);
......@@ -1164,20 +1295,11 @@ __kernel void conv_1x1_spl(
pos_in = (int2)(i * input_width + in_pos_in_one_block3.x, in_pos_in_one_block3.y);
half4 input3 = read_imageh(input_image, sampler, pos_in);
bound_gap = max_w_bound - pos_in.x - 1;
if (bound_gap < input_width && bound_gap >= 0){
if (burndary_index==0){
// do nothing
} else if (burndary_index==1){
input3.w = 0.0f;
} else if (burndary_index==2){
input3.z = 0.0f;
input3.w = 0.0f;
} else if (burndary_index==3){
input3.y = 0.0f;
input3.z = 0.0f;
input3.w = 0.0f;
}
}
outof_bound = bound_gap < input_width && bound_gap >= 0;
input3.w = select(input3.w,zero,outof_bound && (burndary_index==1||burndary_index==2||burndary_index==3));
input3.z = select(input3.z,zero,outof_bound && (burndary_index==2||burndary_index==3));
input3.y = select(input3.y,zero,outof_bound && burndary_index==3);
output3 = mad(input3.x, weight0, output3);
output3 = mad(input3.y, weight1, output3);
......
......@@ -152,8 +152,13 @@ bool ConvAddBNReluKernel<GPU_CL, float>::Init(
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file, build_options);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file,
build_options);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file,
build_options);
}
} else if (param->Filter()->dims()[1] == 1 &&
param->Input()->dims()[1] == param->Output()->dims()[1] &&
param->Filter()->dims()[2] == 3) {
......
......@@ -48,8 +48,13 @@ bool ConvAddKernel<GPU_CL, float>::Init(FusionConvAddParam<GPU_CL> *param) {
param->ExecMode() = ConvParam<GPU_CL>::EXEC_SLIDINGWINDOW1x1_FLOAT;
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file, build_options);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file,
build_options);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file,
build_options);
}
} else if (param->Filter()->dims()[1] == 1 &&
param->Input()->dims()[1] == param->Output()->dims()[1] &&
......
......@@ -50,8 +50,13 @@ bool ConvAddReluKernel<GPU_CL, float>::Init(
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file, build_options);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file,
build_options);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file,
build_options);
}
} else if (param->Filter()->dims()[1] == 1 &&
param->Input()->dims()[1] == param->Output()->dims()[1] &&
param->Filter()->dims()[2] == 3) {
......
......@@ -107,8 +107,13 @@ bool ConvBNReluKernel<GPU_CL, float>::Init(
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file, build_options);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file,
build_options);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file,
build_options);
}
} else if (param->Filter()->dims()[1] == 1 &&
param->Input()->dims()[1] == param->Output()->dims()[1] &&
param->Filter()->dims()[2] == 3) {
......
......@@ -45,7 +45,11 @@ bool ConvKernel<GPU_CL, float>::Init(ConvParam<GPU_CL> *param) {
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file);
}
DLOG << "conv 1x1";
} else if (param->Filter()->dims()[1] == 1 &&
......
......@@ -46,7 +46,13 @@ bool ConvReluKernel<GPU_CL, float>::Init(FusionConvReluParam<GPU_CL> *param) {
param->Filter()->InitNImage(cl_helper_.CLContext(),
cl_helper_.CLCommandQueue());
this->cl_helper_.AddKernel("conv_1x1_spl", conv_kernel_file, build_options);
if (param->Input()->dims()[1] % 4 == 0) {
this->cl_helper_.AddKernel("conv_1x1_simple", conv_kernel_file,
build_options);
} else {
this->cl_helper_.AddKernel("conv_1x1_wrapped", conv_kernel_file,
build_options);
}
DLOG << "conv 1x1";
} else if (param->Filter()->dims()[1] == 1 &&
......
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