// Copyright (c) Advanced Micro Devices, Inc., or its affiliates. // SPDX-License-Identifier: MIT #include #include #include #include "ck/ck.hpp" #include "ck/tensor_operation/gpu/device/impl/device_elementwise_dynamic_vector_dims_impl.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/library/tensor_operation_instance/gpu/transpose_3d.hpp" using F16 = ck::half_t; using F32 = float; using ADataType = F16; using BDataType = F16; using PassThrough = ck::tensor_operation::element_wise::PassThrough; struct SimpleDeviceMem { SimpleDeviceMem() = delete; SimpleDeviceMem(std::size_t mem_size) : p_mem_{} { (void)hipMalloc(static_cast(&p_mem_), mem_size); } void* GetDeviceBuffer() { return p_mem_; } ~SimpleDeviceMem() { (void)hipFree(p_mem_); } void* p_mem_; }; int main() { const int N = 16; const int C = 8; const int D = 8; const int H = 8; const int W = 8; std::vector ncdhw = {N, C, D, H, W}; std::vector nchwd = {N, C, H, W, D}; auto size = N * C * D * H * W; std::array ab_lengths{N, C, H, W, D}; std::array a_strides = {C * D * H * W, H * W, W, 1, D * H * W}; // N, C, D, H, W std::array b_strides = {C * H * W * D, H * W * D, W * D, D, 1}; // N, C, H, W, D SimpleDeviceMem a_dev_buf(sizeof(ADataType) * size); SimpleDeviceMem b_dev_buf(sizeof(BDataType) * size); std::array input = {a_dev_buf.GetDeviceBuffer()}; std::array output = {b_dev_buf.GetDeviceBuffer()}; using DeviceElementwisePermuteInstance = ck::tensor_operation::device:: DeviceElementwise, ck::Tuple, PassThrough, 5>; // get device op instances const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory< DeviceElementwisePermuteInstance>::GetInstances(); std::cout << "found " << op_ptrs.size() << " instances" << std::endl; std::string best_op_name; bool found = false; int best_op_id = -1; float best_ave_time = std::numeric_limits::max(); float best_gb_per_sec = 0; // profile device operation instances std::cout << "Run all instances and do timing" << std::endl; for(int i = 0; i < op_ptrs.size(); ++i) { auto& op_ptr = op_ptrs[i]; auto argument_ptr = op_ptr->MakeArgumentPointer( ab_lengths, {a_strides}, {b_strides}, input, output, PassThrough{}); auto invoker_ptr = op_ptr->MakeInvokerPointer(); std::string op_name = op_ptr->GetTypeString(); if(op_ptr->IsSupportedArgument(argument_ptr.get())) { float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true}); std::size_t num_byte = sizeof(ADataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]) + sizeof(BDataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]); float gb_per_sec = num_byte / 1.E6 / ave_time; std::cout << "Perf: " << std::setw(10) << ave_time << " ms, " << gb_per_sec << " GB/s, " << op_name << std::endl; if(ave_time < best_ave_time) { found = true; best_op_id = i; best_op_name = op_name; best_ave_time = ave_time; best_gb_per_sec = gb_per_sec; } } else { std::cout << op_name << " does not support this problem" << std::endl; } } std::cout << "Best Perf: " << best_ave_time << " ms, " << best_gb_per_sec << " GB/s, " << best_op_name << std::endl; // run the best intance if(found) { auto& op_ptr = op_ptrs[best_op_id]; std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString() << std::endl; auto argument_ptr = op_ptr->MakeArgumentPointer( ab_lengths, {a_strides}, {b_strides}, input, output, PassThrough{}); auto invoker_ptr = op_ptr->MakeInvokerPointer(); if(op_ptr->IsSupportedArgument(argument_ptr.get())) { invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false}); } std::cout << "Done" << std::endl; } return 0; }