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!8502 GPU optimize check sm warning log 

From: @VectorSL
Reviewed-by: @cristoval
Signed-off-by: @cristoval
This commit is contained in:
mindspore-ci-bot 2020-11-13 09:23:55 +08:00 committed by Gitee
parent dbe5229c56 b60be1a023
commit fb3a7b4d5a
2 changed files with 6 additions and 1 deletions
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4
mindspore/ccsrc/backend/kernel_compiler/gpu/gpu_kernel_factory.cc
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@ -127,13 +127,15 @@ std::pair<bool, size_t> GpuKernelFactory::GpuKernelAttrCheck(const std::string &
auto attr_size = (&(iter->second))->at(attr_index).first.GetInputSize(); auto attr_size = (&(iter->second))->at(attr_index).first.GetInputSize();
// data type matching check of all input parameters of kernel // data type matching check of all input parameters of kernel
for (size_t input_index = 0; input_index < kernel_info->GetInputNum(); input_index++) { for (size_t input_index = 0; input_index < kernel_info->GetInputNum(); input_index++) {
if (marjor_sm < RECOMMEND_SM && kernel_info->GetInputDeviceType(input_index) == kNumberTypeFloat16) { const bool check_sm = mindspore::device::gpu::CudaCommon::GetInstance().check_sm();
if (check_sm && marjor_sm < RECOMMEND_SM && kernel_info->GetInputDeviceType(input_index) == kNumberTypeFloat16) {
if (marjor_sm < MINIUM_SM) { if (marjor_sm < MINIUM_SM) {
MS_LOG(EXCEPTION) << "Half precision ops can be used on Devices which computing capacity is >= " << MINIUM_SM MS_LOG(EXCEPTION) << "Half precision ops can be used on Devices which computing capacity is >= " << MINIUM_SM
<< ", but the current device's computing capacity is " << marjor_sm; << ", but the current device's computing capacity is " << marjor_sm;
} }
MS_LOG(WARNING) << "It is recommended to use devices with a computing capacity >= " << RECOMMEND_SM MS_LOG(WARNING) << "It is recommended to use devices with a computing capacity >= " << RECOMMEND_SM
<< ", but the current device's computing capacity is " << marjor_sm; << ", but the current device's computing capacity is " << marjor_sm;
mindspore::device::gpu::CudaCommon::GetInstance().set_check_sm(false);
} }
if (kernel_info->GetInputDeviceType(input_index) != if (kernel_info->GetInputDeviceType(input_index) !=
(iter->second)[attr_index].first.GetInputAttr(input_index % attr_size).first) { (iter->second)[attr_index].first.GetInputAttr(input_index % attr_size).first) {

3
mindspore/ccsrc/runtime/device/gpu/cuda_common.h
View File

@ -31,6 +31,8 @@ class CudaCommon {
return std::min(((total_threads - 1) / threads_per_block_) + 1, max_blocks_); return std::min(((total_threads - 1) / threads_per_block_) + 1, max_blocks_);
} }
size_t share_memory_size() const { return max_share_memory_; } size_t share_memory_size() const { return max_share_memory_; }
void set_check_sm(const bool &flag) { check_sm_ = flag; }
bool check_sm() const { return check_sm_; }
static CudaCommon &GetInstance() { static CudaCommon &GetInstance() {
static CudaCommon instance; static CudaCommon instance;
@ -55,6 +57,7 @@ class CudaCommon {
int threads_per_block_; int threads_per_block_;
int major_sm_; int major_sm_;
size_t max_share_memory_; size_t max_share_memory_;
bool check_sm_{true};
}; };
#define GET_BLOCKS(total_threads) mindspore::device::gpu::CudaCommon::GetInstance().blocks_num(total_threads) #define GET_BLOCKS(total_threads) mindspore::device::gpu::CudaCommon::GetInstance().blocks_num(total_threads)
#define GET_THREADS mindspore::device::gpu::CudaCommon::GetInstance().threads_num() #define GET_THREADS mindspore::device::gpu::CudaCommon::GetInstance().threads_num()