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提交 d9dfffd4 authored 作者: Arnaud Bergeron's avatar Arnaud Bergeron
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Make col2im and im2col callable on low-registers GPUs.

The previous fixed 1024 threads would sometimes bust the register limit.
上级 34f1dd14
隐藏空白字符变更
内嵌 并排
正在显示 包含 45 行增加 和 42 行删除
theano/gpuarray/corr_gemm.c
浏览文件 @ d9dfffd4
......@@ -195,8 +195,7 @@ KERNEL void col2im_kernel(const ga_size n,
#section support_code_struct
int im2col(const size_t max_threads_dim,
gpudata * data_im, const size_t data_im_offset, const size_t channels,
int im2col(gpudata *data_im, const size_t data_im_offset, const size_t channels,
const size_t height, const size_t width, const size_t kernel_h, const size_t kernel_w,
const size_t dilation_h, const size_t dilation_w,
const size_t pad_h, const size_t pad_w,
......@@ -209,13 +208,10 @@ int im2col(const size_t max_threads_dim,
size_t height_col = (height + 2 * pad_h - dil_kernel_h) / stride_h + 1;
size_t width_col = (width + 2 * pad_w - dil_kernel_w) / stride_w + 1;
size_t num_kernels = channels * height_col * width_col;
size_t threads_per_block = max_threads_dim;
size_t n_blocks = (num_kernels + threads_per_block - 1) / threads_per_block;
int err;
GpuKernel *kernel;
if(dilation_h != 1 || dilation_w != 1){
err = dilated_im2col_kernel_call(
1, &n_blocks, &threads_per_block, 0,
if (dilation_h != 1 || dilation_w != 1) {
err = dilated_im2col_kernel_scall(
1, &num_kernels, 0,
num_kernels, data_im, data_im_offset, height, width, kernel_h, kernel_w,
dilation_h, dilation_w, pad_h, pad_w, stride_h, stride_w, height_col,
width_col, data_col);
......@@ -224,10 +220,9 @@ int im2col(const size_t max_threads_dim,
"gpuarray error: dilated_im2col_kernel: %s.",
GpuKernel_error(&k_dilated_im2col_kernel, err));
}
}
else{
err = im2col_kernel_call(
1, &n_blocks, &threads_per_block, 0,
} else {
err = im2col_kernel_scall(
1, &num_kernels, 0,
num_kernels, data_im, data_im_offset, height, width, kernel_h, kernel_w,
pad_h, pad_w, stride_h, stride_w, height_col,
width_col, data_col);
......@@ -240,7 +235,7 @@ int im2col(const size_t max_threads_dim,
return err;
}
int col2im(const size_t max_threads_dim, gpudata * data_col, const size_t channels,
int col2im(gpudata * data_col, const size_t channels,
const size_t height, const size_t width, const size_t patch_h, const size_t patch_w,
const size_t dilation_h, const size_t dilation_w,
const size_t pad_h, const size_t pad_w, const size_t stride_h,
......@@ -250,14 +245,12 @@ int col2im(const size_t max_threads_dim, gpudata * data_col, const size_t channe
size_t height_col = (height + 2 * pad_h - dil_patch_h) / stride_h + 1;
size_t width_col = (width + 2 * pad_w - dil_patch_w) / stride_w + 1;
size_t num_kernels = channels * height * width;
size_t threads_per_block = max_threads_dim;
size_t n_blocks = (num_kernels + threads_per_block - 1) / threads_per_block;
// To avoid involving atomic operations, we will launch one kernel per
// bottom dimension, and then in the kernel add up the top dimensions.
int err;
if(dilation_h != 1 || dilation_w != 1){
err = dilated_col2im_kernel_call(
1, &n_blocks, &threads_per_block, 0,
if (dilation_h != 1 || dilation_w != 1) {
err = dilated_col2im_kernel_scall(
1, &num_kernels, 0,
num_kernels, data_col, height, width, channels, patch_h, patch_w,
dilation_h, dilation_w, pad_h, pad_w, stride_h, stride_w,
height_col, width_col, data_im, data_im_offset);
......@@ -266,10 +259,9 @@ int col2im(const size_t max_threads_dim, gpudata * data_col, const size_t channe
"gpuarray error: dilated_col2im_kernel: %s.",
GpuKernel_error(&k_dilated_col2im_kernel, err));
}
}
else{
err = col2im_kernel_call(
1, &n_blocks, &threads_per_block, 0,
} else {
err = col2im_kernel_scall(
1, &num_kernels, 0,
num_kernels, data_col, height, width, channels, patch_h, patch_w,
pad_h, pad_w, stride_h, stride_w,
height_col, width_col, data_im, data_im_offset);
......@@ -393,15 +385,6 @@ PyGpuArrayObject* corrMM(PyGpuArrayObject *const bottom,
return NULL;
}
// Get the max threads per blocks
size_t max_threads_dim;
err = gpucontext_property(bottom->context->ctx, GA_CTX_PROP_MAXLSIZE, &max_threads_dim);
if (err != GA_NO_ERROR){
PyErr_Format(PyExc_RuntimeError,
"Could not fetch max_threads_dim.");
return NULL;
}
// Create temporary columns
size_t col_dim[2];
col_dim[0] = nChannels * kW * kH;
......@@ -411,8 +394,7 @@ PyGpuArrayObject* corrMM(PyGpuArrayObject *const bottom,
GA_C_ORDER,
bottom->context,
Py_None);
if (NULL == col)
{
if (NULL == col) {
PyErr_Format(PyExc_RuntimeError,
"GpuCorrMM failed to allocate working memory of %ld x %ld\n",
col_dim[0], col_dim[1]);
......@@ -435,8 +417,8 @@ PyGpuArrayObject* corrMM(PyGpuArrayObject *const bottom,
// Iterate over batch
for (size_t n = 0; n < batchSize; n++) {
// First, im2col
err = im2col(max_threads_dim,
bottom->ga.data, n * bottom_stride, nChannels, bottomHeight,
err = im2col(bottom->ga.data, n * bottom_stride,
nChannels, bottomHeight,
bottomWidth, kH, kW, dilH, dilW,
padH, padW, dH, dW, col->ga.data);
if (err != GA_NO_ERROR) {
......@@ -464,8 +446,8 @@ PyGpuArrayObject* corrMM(PyGpuArrayObject *const bottom,
// Iterate over batch
for (size_t n = 0; n < batchSize; n++) {
// First, im2col
err = im2col(max_threads_dim,
bottom->ga.data, n * bottom_stride, nChannels, bottomHeight,
err = im2col(bottom->ga.data, n * bottom_stride,
nChannels, bottomHeight,
bottomWidth, kH, kW, dilH, dilW,
padH, padW, dH, dW, col->ga.data);
if (err != GA_NO_ERROR) {
......@@ -496,21 +478,42 @@ PyGpuArrayObject* corrMM(PyGpuArrayObject *const bottom,
// Iterate over batch
for (size_t n = 0; n < batchSize; n++) {
// gemm into columns
switch (top->ga.typecode) {
case GA_FLOAT:
err = gpublas_sgemm(cb_fortran, cb_no_trans, cb_trans,
N_, K_, M_, one,
N_, K_, M_, 1,
top->ga.data, n * top_stride, N_,
weight->ga.data, 0, K_,
zero,
0,
col->ga.data, 0, N_);
break;
case GA_DOUBLE:
err = gpublas_dgemm(cb_fortran, cb_no_trans, cb_trans,
N_, K_, M_, 1,
top->ga.data, n * top_stride, N_,
weight->ga.data, 0, K_,
0,
col->ga.data, 0, N_);
break;
case GA_HALF:
err = gpublas_hgemm(cb_fortran, cb_no_trans, cb_trans,
N_, K_, M_, 1,
top->ga.data, n * top_stride, N_,
weight->ga.data, 0, K_,
0,
col->ga.data, 0, N_);
break;
default:
err = GA_UNSUPPORTED_ERROR;
}
if (err != GA_NO_ERROR) {
PyErr_Format(PyExc_RuntimeError,
"GpuCorrMM encountered an error running sgemm.\n");
"(2) GpuCorrMM encountered an error running gemm: %d", err);
Py_DECREF(col);
return NULL;
}
// col2im back to the data
err = col2im(max_threads_dim,
col->ga.data, nChannels, bottomHeight, bottomWidth,
err = col2im(col->ga.data, nChannels, bottomHeight, bottomWidth,
kH, kW, dilH, dilW, padH, padW,
dH, dW, bottom->ga.data, n * bottom_stride);
if (err != GA_NO_ERROR) {
......
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