1 // Copyright (c) 2017-2022, Lawrence Livermore National Security, LLC and other CEED contributors. 2 // All Rights Reserved. See the top-level LICENSE and NOTICE files for details. 3 // 4 // SPDX-License-Identifier: BSD-2-Clause 5 // 6 // This file is part of CEED: http://github.com/ceed 7 8 #include "ceed-cuda-compile.h" 9 10 #include <ceed.h> 11 #include <ceed/backend.h> 12 #include <ceed/jit-tools.h> 13 #include <cuda_runtime.h> 14 #include <nvrtc.h> 15 #include <stdarg.h> 16 #include <string.h> 17 18 #include <sstream> 19 20 #include "ceed-cuda-common.h" 21 22 #define CeedChk_Nvrtc(ceed, x) \ 23 do { \ 24 nvrtcResult result = static_cast<nvrtcResult>(x); \ 25 if (result != NVRTC_SUCCESS) return CeedError((ceed), CEED_ERROR_BACKEND, nvrtcGetErrorString(result)); \ 26 } while (0) 27 28 #define CeedCallNvrtc(ceed, ...) \ 29 do { \ 30 int ierr_q_ = __VA_ARGS__; \ 31 CeedChk_Nvrtc(ceed, ierr_q_); \ 32 } while (0) 33 34 //------------------------------------------------------------------------------ 35 // Compile CUDA kernel 36 //------------------------------------------------------------------------------ 37 int CeedCompile_Cuda(Ceed ceed, const char *source, CUmodule *module, const CeedInt num_defines, ...) { 38 size_t ptx_size; 39 char *ptx; 40 const char *jit_defs_path, *jit_defs_source; 41 const int num_opts = 3; 42 const char *opts[num_opts]; 43 nvrtcProgram prog; 44 struct cudaDeviceProp prop; 45 Ceed_Cuda *ceed_data; 46 47 cudaFree(0); // Make sure a Context exists for nvrtc 48 49 std::ostringstream code; 50 51 // Get kernel specific options, such as kernel constants 52 if (num_defines > 0) { 53 va_list args; 54 va_start(args, num_defines); 55 char *name; 56 int val; 57 58 for (int i = 0; i < num_defines; i++) { 59 name = va_arg(args, char *); 60 val = va_arg(args, int); 61 code << "#define " << name << " " << val << "\n"; 62 } 63 va_end(args); 64 } 65 66 // Standard libCEED definitions for CUDA backends 67 CeedCallBackend(CeedGetJitAbsolutePath(ceed, "ceed/jit-source/cuda/cuda-jit.h", &jit_defs_path)); 68 { 69 char *source; 70 71 CeedCallBackend(CeedLoadSourceToBuffer(ceed, jit_defs_path, &source)); 72 jit_defs_source = source; 73 } 74 code << jit_defs_source; 75 code << "\n\n"; 76 77 // Non-macro options 78 opts[0] = "-default-device"; 79 CeedCallBackend(CeedGetData(ceed, &ceed_data)); 80 CeedCallCuda(ceed, cudaGetDeviceProperties(&prop, ceed_data->device_id)); 81 std::string arch_arg = "-arch=compute_" + std::to_string(prop.major) + std::to_string(prop.minor); 82 opts[1] = arch_arg.c_str(); 83 opts[2] = "-Dint32_t=int"; 84 85 // Add string source argument provided in call 86 code << source; 87 88 // Create Program 89 CeedCallNvrtc(ceed, nvrtcCreateProgram(&prog, code.str().c_str(), NULL, 0, NULL, NULL)); 90 91 // Compile kernel 92 nvrtcResult result = nvrtcCompileProgram(prog, num_opts, opts); 93 94 if (result != NVRTC_SUCCESS) { 95 char *log; 96 size_t log_size; 97 98 CeedDebug256(ceed, CEED_DEBUG_COLOR_ERROR, "---------- CEED JIT SOURCE FAILED TO COMPILE ----------\n"); 99 CeedDebug(ceed, "File: %s\n", jit_defs_path); 100 CeedDebug(ceed, "Source:\n%s\n", jit_defs_source); 101 CeedDebug256(ceed, CEED_DEBUG_COLOR_ERROR, "---------- CEED JIT SOURCE FAILED TO COMPILE ----------\n"); 102 CeedCallBackend(CeedFree(&jit_defs_path)); 103 CeedCallBackend(CeedFree(&jit_defs_source)); 104 CeedCallNvrtc(ceed, nvrtcGetProgramLogSize(prog, &log_size)); 105 CeedCallBackend(CeedMalloc(log_size, &log)); 106 CeedCallNvrtc(ceed, nvrtcGetProgramLog(prog, log)); 107 return CeedError(ceed, CEED_ERROR_BACKEND, "%s\n%s", nvrtcGetErrorString(result), log); 108 } 109 CeedCallBackend(CeedFree(&jit_defs_path)); 110 CeedCallBackend(CeedFree(&jit_defs_source)); 111 112 CeedCallNvrtc(ceed, nvrtcGetPTXSize(prog, &ptx_size)); 113 CeedCallBackend(CeedMalloc(ptx_size, &ptx)); 114 CeedCallNvrtc(ceed, nvrtcGetPTX(prog, ptx)); 115 CeedCallNvrtc(ceed, nvrtcDestroyProgram(&prog)); 116 117 CeedCallCuda(ceed, cuModuleLoadData(module, ptx)); 118 CeedCallBackend(CeedFree(&ptx)); 119 return CEED_ERROR_SUCCESS; 120 } 121 122 //------------------------------------------------------------------------------ 123 // Get CUDA kernel 124 //------------------------------------------------------------------------------ 125 int CeedGetKernel_Cuda(Ceed ceed, CUmodule module, const char *name, CUfunction *kernel) { 126 CeedCallCuda(ceed, cuModuleGetFunction(kernel, module, name)); 127 return CEED_ERROR_SUCCESS; 128 } 129 130 //------------------------------------------------------------------------------ 131 // Run CUDA kernel with block size selected automatically based on the kernel 132 // (which may use enough registers to require a smaller block size than the 133 // hardware is capable) 134 //------------------------------------------------------------------------------ 135 int CeedRunKernelAutoblockCuda(Ceed ceed, CUfunction kernel, size_t points, void **args) { 136 int min_grid_size, max_block_size; 137 138 CeedCallCuda(ceed, cuOccupancyMaxPotentialBlockSize(&min_grid_size, &max_block_size, kernel, NULL, 0, 0x10000)); 139 CeedCallBackend(CeedRunKernel_Cuda(ceed, kernel, CeedDivUpInt(points, max_block_size), max_block_size, args)); 140 return CEED_ERROR_SUCCESS; 141 } 142 143 //------------------------------------------------------------------------------ 144 // Run CUDA kernel 145 //------------------------------------------------------------------------------ 146 int CeedRunKernel_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size, void **args) { 147 CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size, 1, 1, 0, args)); 148 return CEED_ERROR_SUCCESS; 149 } 150 151 //------------------------------------------------------------------------------ 152 // Run CUDA kernel for spatial dimension 153 //------------------------------------------------------------------------------ 154 int CeedRunKernelDim_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size_x, const int block_size_y, const int block_size_z, 155 void **args) { 156 CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size_x, block_size_y, block_size_z, 0, args)); 157 return CEED_ERROR_SUCCESS; 158 } 159 160 //------------------------------------------------------------------------------ 161 // Run CUDA kernel for spatial dimension with shared memory 162 //------------------------------------------------------------------------------ 163 int CeedRunKernelDimShared_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size_x, const int block_size_y, 164 const int block_size_z, const int shared_mem_size, void **args) { 165 #if CUDA_VERSION >= 9000 166 cuFuncSetAttribute(kernel, CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES, shared_mem_size); 167 #endif 168 CUresult result = cuLaunchKernel(kernel, grid_size, 1, 1, block_size_x, block_size_y, block_size_z, shared_mem_size, NULL, args, NULL); 169 170 if (result == CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES) { 171 int max_threads_per_block, shared_size_bytes, num_regs; 172 173 cuFuncGetAttribute(&max_threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, kernel); 174 cuFuncGetAttribute(&shared_size_bytes, CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, kernel); 175 cuFuncGetAttribute(&num_regs, CU_FUNC_ATTRIBUTE_NUM_REGS, kernel); 176 return CeedError(ceed, CEED_ERROR_BACKEND, 177 "CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: max_threads_per_block %d on block size (%d,%d,%d), shared_size %d, num_regs %d", 178 max_threads_per_block, block_size_x, block_size_y, block_size_z, shared_size_bytes, num_regs); 179 } else CeedChk_Cu(ceed, result); 180 return CEED_ERROR_SUCCESS; 181 } 182 183 //------------------------------------------------------------------------------ 184