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Gemm+Reduce Fusion (#128)

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* add gridwise gemm v4r1

* rename

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* use sfc in shuffling

* remove hardcode

* remove hardcode

* refactor

* fix build

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* adding gemm+reduce

* format

* clean

* adding gemm+reduce

* adding profiler for gemm+reduce

* adding gemm+reduce profiler

* fix build

* clean up

* gemm+reduce

* fix build

* update DeviceGemm_Xdl_CShuffle; update enum to enum class

* clean up

* add test for gemm+reduce

* clean up

* refactor

* fix build

* fix build
This commit is contained in:
Chao Liu
2022-03-23 22:18:42 -05:00
committed by GitHub
parent f91579aab6
commit f95267f166
56 changed files with 4429 additions and 297 deletions
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10
library/include/ck/library/host_tensor/device.hpp
View File

@@ -13,8 +13,10 @@ struct DeviceMem
DeviceMem() = delete;
DeviceMem(std::size_t mem_size);
void* GetDeviceBuffer();
std::size_t GetBufferSize();
void ToDevice(const void* p);
void FromDevice(void* p);
void SetZero();
~DeviceMem();
void* mpDeviceBuf;
@@ -48,7 +50,6 @@ template <typename... Args, typename F>
float launch_and_time_kernel(
F kernel, int nrepeat, dim3 grid_dim, dim3 block_dim, std::size_t lds_byte, Args... args)
{
#if 1
KernelTimer timer;
printf("%s: grid_dim {%d, %d, %d}, block_dim {%d, %d, %d} \n",
@@ -78,13 +79,6 @@ float launch_and_time_kernel(
timer.End();
// std::this_thread::sleep_for (std::chrono::microseconds(10));
return timer.GetElapsedTime() / nrepeat;
#else
launch_kernel(kernel, grid_dim, block_dim, lds_byte, args...);
return 0;
#endif
}
#endif

79
library/include/ck/library/host_tensor/host_tensor.hpp
View File

@@ -40,20 +40,6 @@ std::ostream& LogRangeAsType(std::ostream& os, Range&& range, std::string delim)
return os;
}
typedef enum
{
Half = 0,
Float = 1,
} DataType_t;
template <typename T>
struct DataType;
template <>
struct DataType<float> : std::integral_constant<DataType_t, DataType_t::Float>
{
};
template <typename F, typename T, std::size_t... Is>
auto call_f_unpack_args_impl(F f, T args, std::index_sequence<Is...>)
{
@@ -312,49 +298,58 @@ HostTensorDescriptor::HostTensorDescriptor(std::vector<X> lens, std::vector<Y> s
void ostream_HostTensorDescriptor(const HostTensorDescriptor& desc, std::ostream& os = std::cout);
#if 1
// FIXME: remove
float bf16_to_f32_(ck::bhalf_t src_val);
// FIXME: remove
void bf16_to_f32_(const Tensor<ck::bhalf_t>& src, Tensor<float>& dst);
#endif
template <typename T>
float check_error(const Tensor<T>& ref, const Tensor<T>& result)
{
float error = 0;
float max_diff = -1;
float ref_value = 0, result_value = 0;
float l1_error = 0;
float linf_error = -1;
float linf_rel_error = -1;
if constexpr(std::is_same<ck::bhalf_t, T>::value)
float linf_ref_value = 0, linf_result_value = 0;
float linf_rel_ref_value = 0, linf_rel_result_value = 0;
constexpr float eps = 1e-10;
for(int i = 0; i < ref.mData.size(); ++i)
{
for(int i = 0; i < ref.mData.size(); ++i)
float ref_v = ck::type_convert<float>(ref.mData[i]);
float result_v = ck::type_convert<float>(result.mData[i]);
float diff = std::abs(ref_v - result_v);
float rel_diff = diff / std::max(std::abs(ref_v), eps);
l1_error += diff;
if(linf_error < diff)
{
error += std::abs(bf16_to_f32_(ref.mData[i]) - bf16_to_f32_(result.mData[i]));
float diff = std::abs(bf16_to_f32_(ref.mData[i]) - bf16_to_f32_(result.mData[i]));
if(max_diff < diff)
{
max_diff = diff;
ref_value = bf16_to_f32_(ref.mData[i]);
result_value = bf16_to_f32_(result.mData[i]);
}
linf_error = diff;
linf_ref_value = ref_v;
linf_result_value = result_v;
}
}
else
{
for(int i = 0; i < ref.mData.size(); ++i)
if(linf_rel_error < rel_diff)
{
error += std::abs(double(ref.mData[i]) - double(result.mData[i]));
float diff = std::abs(double(ref.mData[i]) - double(result.mData[i]));
if(max_diff < diff)
{
max_diff = diff;
ref_value = ref.mData[i];
result_value = result.mData[i];
}
linf_rel_error = rel_diff;
linf_rel_ref_value = ref_v;
linf_rel_result_value = result_v;
}
}
std::cout << "error: " << error << std::endl;
std::cout << "max_diff: " << max_diff << ", " << ref_value << ", " << result_value << std::endl;
return max_diff;
std::cout << "Absolute Error L1 Norm (sum of abs diff): " << l1_error << std::endl;
std::cout << "Absolute Error L-inf Norm (max abs diff): " << linf_error << ", ref "
<< linf_ref_value << ", result " << linf_result_value << std::endl;
std::cout << "Relative Error L-inf Norm (max relative abs diff): " << linf_rel_error << ", ref "
<< linf_rel_ref_value << ", result " << linf_rel_result_value << std::endl;
return linf_error;
}
template <typename T>