xref: /libCEED/backends/cuda/ceed-cuda-compile.cpp (revision e64bb3f3ed2986a0c10dec3b47522d734c6e367d)
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   cudaFree(0);  // Make sure a Context exists for nvrtc
39   nvrtcProgram prog;
40 
41   std::ostringstream code;
42 
43   // Get kernel specific options, such as kernel constants
44   if (num_defines > 0) {
45     va_list args;
46     va_start(args, num_defines);
47     char *name;
48     int   val;
49     for (int i = 0; i < num_defines; i++) {
50       name = va_arg(args, char *);
51       val  = va_arg(args, int);
52       code << "#define " << name << " " << val << "\n";
53     }
54     va_end(args);
55   }
56 
57   // Standard libCEED definitions for CUDA backends
58   char *jit_defs_path, *jit_defs_source;
59   CeedCallBackend(CeedGetJitAbsolutePath(ceed, "ceed/jit-source/cuda/cuda-jit.h", &jit_defs_path));
60   CeedCallBackend(CeedLoadSourceToBuffer(ceed, jit_defs_path, &jit_defs_source));
61   code << jit_defs_source;
62   code << "\n\n";
63   CeedCallBackend(CeedFree(&jit_defs_path));
64   CeedCallBackend(CeedFree(&jit_defs_source));
65 
66   // Non-macro options
67   const int   num_opts = 3;
68   const char *opts[num_opts];
69   opts[0] = "-default-device";
70   struct cudaDeviceProp prop;
71   Ceed_Cuda            *ceed_data;
72   CeedCallBackend(CeedGetData(ceed, &ceed_data));
73   CeedCallCuda(ceed, cudaGetDeviceProperties(&prop, ceed_data->device_id));
74   std::string arch_arg = "-arch=compute_" + std::to_string(prop.major) + std::to_string(prop.minor);
75   opts[1]              = arch_arg.c_str();
76   opts[2]              = "-Dint32_t=int";
77 
78   // Add string source argument provided in call
79   code << source;
80 
81   // Create Program
82   CeedCallNvrtc(ceed, nvrtcCreateProgram(&prog, code.str().c_str(), NULL, 0, NULL, NULL));
83 
84   // Compile kernel
85   nvrtcResult result = nvrtcCompileProgram(prog, num_opts, opts);
86   if (result != NVRTC_SUCCESS) {
87     size_t log_size;
88     CeedCallNvrtc(ceed, nvrtcGetProgramLogSize(prog, &log_size));
89     char *log;
90     CeedCallBackend(CeedMalloc(log_size, &log));
91     CeedCallNvrtc(ceed, nvrtcGetProgramLog(prog, log));
92     return CeedError(ceed, CEED_ERROR_BACKEND, "%s\n%s", nvrtcGetErrorString(result), log);
93   }
94 
95   size_t ptx_size;
96   CeedCallNvrtc(ceed, nvrtcGetPTXSize(prog, &ptx_size));
97   char *ptx;
98   CeedCallBackend(CeedMalloc(ptx_size, &ptx));
99   CeedCallNvrtc(ceed, nvrtcGetPTX(prog, ptx));
100   CeedCallNvrtc(ceed, nvrtcDestroyProgram(&prog));
101 
102   CeedCallCuda(ceed, cuModuleLoadData(module, ptx));
103   CeedCallBackend(CeedFree(&ptx));
104   return CEED_ERROR_SUCCESS;
105 }
106 
107 //------------------------------------------------------------------------------
108 // Get CUDA kernel
109 //------------------------------------------------------------------------------
110 int CeedGetKernel_Cuda(Ceed ceed, CUmodule module, const char *name, CUfunction *kernel) {
111   CeedCallCuda(ceed, cuModuleGetFunction(kernel, module, name));
112   return CEED_ERROR_SUCCESS;
113 }
114 
115 //------------------------------------------------------------------------------
116 // Run CUDA kernel with block size selected automatically based on the kernel
117 //     (which may use enough registers to require a smaller block size than the
118 //      hardware is capable)
119 //------------------------------------------------------------------------------
120 int CeedRunKernelAutoblockCuda(Ceed ceed, CUfunction kernel, size_t points, void **args) {
121   int min_grid_size, max_block_size;
122   CeedCallCuda(ceed, cuOccupancyMaxPotentialBlockSize(&min_grid_size, &max_block_size, kernel, NULL, 0, 0x10000));
123   CeedCallBackend(CeedRunKernel_Cuda(ceed, kernel, CeedDivUpInt(points, max_block_size), max_block_size, args));
124   return 0;
125 }
126 
127 //------------------------------------------------------------------------------
128 // Run CUDA kernel
129 //------------------------------------------------------------------------------
130 int CeedRunKernel_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size, void **args) {
131   CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size, 1, 1, 0, args));
132   return CEED_ERROR_SUCCESS;
133 }
134 
135 //------------------------------------------------------------------------------
136 // Run CUDA kernel for spatial dimension
137 //------------------------------------------------------------------------------
138 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,
139                           void **args) {
140   CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size_x, block_size_y, block_size_z, 0, args));
141   return CEED_ERROR_SUCCESS;
142 }
143 
144 //------------------------------------------------------------------------------
145 // Run CUDA kernel for spatial dimension with shared memory
146 //------------------------------------------------------------------------------
147 int CeedRunKernelDimShared_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size_x, const int block_size_y,
148                                 const int block_size_z, const int shared_mem_size, void **args) {
149 #if CUDA_VERSION >= 9000
150   cuFuncSetAttribute(kernel, CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES, shared_mem_size);
151 #endif
152   CUresult result = cuLaunchKernel(kernel, grid_size, 1, 1, block_size_x, block_size_y, block_size_z, shared_mem_size, NULL, args, NULL);
153   if (result == CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES) {
154     int max_threads_per_block, shared_size_bytes, num_regs;
155     cuFuncGetAttribute(&max_threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, kernel);
156     cuFuncGetAttribute(&shared_size_bytes, CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, kernel);
157     cuFuncGetAttribute(&num_regs, CU_FUNC_ATTRIBUTE_NUM_REGS, kernel);
158     return CeedError(ceed, CEED_ERROR_BACKEND,
159                      "CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: max_threads_per_block %d on block size (%d,%d,%d), shared_size %d, num_regs %d",
160                      max_threads_per_block, block_size_x, block_size_y, block_size_z, shared_size_bytes, num_regs);
161   } else CeedChk_Cu(ceed, result);
162   return CEED_ERROR_SUCCESS;
163 }
164 
165 //------------------------------------------------------------------------------
166