xref: /libCEED/backends/cuda/ceed-cuda-compile.cpp (revision 9c25dd66b9687765a7022cc762ccaf201b721845)
1 // Copyright (c) 2017-2024, 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 int             num_opts            = 4;
41   CeedInt               num_jit_source_dirs = 0;
42   const char          **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   code << "#include <ceed/jit-source/cuda/cuda-jit.h>\n\n";
68 
69   // Non-macro options
70   CeedCallBackend(CeedCalloc(num_opts, &opts));
71   opts[0] = "-default-device";
72   CeedCallBackend(CeedGetData(ceed, &ceed_data));
73   CeedCallCuda(ceed, cudaGetDeviceProperties(&prop, ceed_data->device_id));
74   std::string arch_arg =
75 #if CUDA_VERSION >= 11010
76       // NVRTC used to support only virtual architectures through the option
77       // -arch, since it was only emitting PTX. It will now support actual
78       // architectures as well to emit SASS.
79       // https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html#dynamic-code-generation
80       "-arch=sm_"
81 #else
82       "-arch=compute_"
83 #endif
84       + std::to_string(prop.major) + std::to_string(prop.minor);
85   opts[1] = arch_arg.c_str();
86   opts[2] = "-Dint32_t=int";
87   opts[3] = "-DCEED_RUNNING_JIT_PASS=1";
88   {
89     const char **jit_source_dirs;
90 
91     CeedCallBackend(CeedGetJitSourceRoots(ceed, &num_jit_source_dirs, &jit_source_dirs));
92     CeedCallBackend(CeedRealloc(num_opts + num_jit_source_dirs, &opts));
93     for (CeedInt i = 0; i < num_jit_source_dirs; i++) {
94       std::ostringstream include_dirs_arg;
95 
96       include_dirs_arg << "-I" << jit_source_dirs[i];
97       CeedCallBackend(CeedStringAllocCopy(include_dirs_arg.str().c_str(), (char **)&opts[num_opts + i]));
98     }
99     CeedCallBackend(CeedRestoreJitSourceRoots(ceed, &jit_source_dirs));
100   }
101 
102   // Add string source argument provided in call
103   code << source;
104 
105   // Create Program
106   CeedCallNvrtc(ceed, nvrtcCreateProgram(&prog, code.str().c_str(), NULL, 0, NULL, NULL));
107 
108   // Compile kernel
109   nvrtcResult result = nvrtcCompileProgram(prog, num_opts + num_jit_source_dirs, opts);
110 
111   for (CeedInt i = 0; i < num_jit_source_dirs; i++) {
112     CeedCallBackend(CeedFree(&opts[num_opts + i]));
113   }
114   CeedCallBackend(CeedFree(&opts));
115   if (result != NVRTC_SUCCESS) {
116     char  *log;
117     size_t log_size;
118 
119     CeedDebug256(ceed, CEED_DEBUG_COLOR_ERROR, "---------- CEED JIT SOURCE FAILED TO COMPILE ----------\n");
120     CeedDebug(ceed, "Source:\n%s\n", code.str().c_str());
121     CeedDebug256(ceed, CEED_DEBUG_COLOR_ERROR, "---------- CEED JIT SOURCE FAILED TO COMPILE ----------\n");
122     CeedCallNvrtc(ceed, nvrtcGetProgramLogSize(prog, &log_size));
123     CeedCallBackend(CeedMalloc(log_size, &log));
124     CeedCallNvrtc(ceed, nvrtcGetProgramLog(prog, log));
125     return CeedError(ceed, CEED_ERROR_BACKEND, "%s\n%s", nvrtcGetErrorString(result), log);
126   }
127 
128 #if CUDA_VERSION >= 11010
129   CeedCallNvrtc(ceed, nvrtcGetCUBINSize(prog, &ptx_size));
130   CeedCallBackend(CeedMalloc(ptx_size, &ptx));
131   CeedCallNvrtc(ceed, nvrtcGetCUBIN(prog, ptx));
132 #else
133   CeedCallNvrtc(ceed, nvrtcGetPTXSize(prog, &ptx_size));
134   CeedCallBackend(CeedMalloc(ptx_size, &ptx));
135   CeedCallNvrtc(ceed, nvrtcGetPTX(prog, ptx));
136 #endif
137   CeedCallNvrtc(ceed, nvrtcDestroyProgram(&prog));
138 
139   CeedCallCuda(ceed, cuModuleLoadData(module, ptx));
140   CeedCallBackend(CeedFree(&ptx));
141   return CEED_ERROR_SUCCESS;
142 }
143 
144 //------------------------------------------------------------------------------
145 // Get CUDA kernel
146 //------------------------------------------------------------------------------
147 int CeedGetKernel_Cuda(Ceed ceed, CUmodule module, const char *name, CUfunction *kernel) {
148   CeedCallCuda(ceed, cuModuleGetFunction(kernel, module, name));
149   return CEED_ERROR_SUCCESS;
150 }
151 
152 //------------------------------------------------------------------------------
153 // Run CUDA kernel with block size selected automatically based on the kernel
154 //     (which may use enough registers to require a smaller block size than the
155 //      hardware is capable)
156 //------------------------------------------------------------------------------
157 int CeedRunKernelAutoblockCuda(Ceed ceed, CUfunction kernel, size_t points, void **args) {
158   int min_grid_size, max_block_size;
159 
160   CeedCallCuda(ceed, cuOccupancyMaxPotentialBlockSize(&min_grid_size, &max_block_size, kernel, NULL, 0, 0x10000));
161   CeedCallBackend(CeedRunKernel_Cuda(ceed, kernel, CeedDivUpInt(points, max_block_size), max_block_size, args));
162   return CEED_ERROR_SUCCESS;
163 }
164 
165 //------------------------------------------------------------------------------
166 // Run CUDA kernel
167 //------------------------------------------------------------------------------
168 int CeedRunKernel_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size, void **args) {
169   CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size, 1, 1, 0, args));
170   return CEED_ERROR_SUCCESS;
171 }
172 
173 //------------------------------------------------------------------------------
174 // Run CUDA kernel for spatial dimension
175 //------------------------------------------------------------------------------
176 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,
177                           void **args) {
178   CeedCallBackend(CeedRunKernelDimShared_Cuda(ceed, kernel, grid_size, block_size_x, block_size_y, block_size_z, 0, args));
179   return CEED_ERROR_SUCCESS;
180 }
181 
182 //------------------------------------------------------------------------------
183 // Run CUDA kernel for spatial dimension with shared memory
184 //------------------------------------------------------------------------------
185 int CeedRunKernelDimShared_Cuda(Ceed ceed, CUfunction kernel, const int grid_size, const int block_size_x, const int block_size_y,
186                                 const int block_size_z, const int shared_mem_size, void **args) {
187 #if CUDA_VERSION >= 9000
188   cuFuncSetAttribute(kernel, CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES, shared_mem_size);
189 #endif
190   CUresult result = cuLaunchKernel(kernel, grid_size, 1, 1, block_size_x, block_size_y, block_size_z, shared_mem_size, NULL, args, NULL);
191 
192   if (result == CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES) {
193     int max_threads_per_block, shared_size_bytes, num_regs;
194 
195     cuFuncGetAttribute(&max_threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, kernel);
196     cuFuncGetAttribute(&shared_size_bytes, CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, kernel);
197     cuFuncGetAttribute(&num_regs, CU_FUNC_ATTRIBUTE_NUM_REGS, kernel);
198     return CeedError(ceed, CEED_ERROR_BACKEND,
199                      "CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: max_threads_per_block %d on block size (%d,%d,%d), shared_size %d, num_regs %d",
200                      max_threads_per_block, block_size_x, block_size_y, block_size_z, shared_size_bytes, num_regs);
201   } else CeedChk_Cu(ceed, result);
202   return CEED_ERROR_SUCCESS;
203 }
204 
205 //------------------------------------------------------------------------------
206