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36 #ifndef GMX_GPU_UTILS_CUDAUTILS_CUH
37 #define GMX_GPU_UTILS_CUDAUTILS_CUH
44 #include "gromacs/gpu_utils/gputraits.cuh"
45 #include "gromacs/math/vec.h"
46 #include "gromacs/math/vectypes.h"
47 #include "gromacs/utility/exceptions.h"
48 #include "gromacs/utility/fatalerror.h"
49 #include "gromacs/utility/gmxassert.h"
50 #include "gromacs/utility/stringutil.h"
57 /*! \brief Helper function to ensure no pending error silently
58 * disrupts error handling.
60 * Asserts in a debug build if an unhandled error is present. Issues a
61 * warning at run time otherwise.
63 * \todo This is similar to CU_CHECK_PREV_ERR, which should be
66 static inline void ensureNoPendingCudaError(const char* errorMessage)
68 // Ensure there is no pending error that would otherwise affect
69 // the behaviour of future error handling.
70 cudaError_t stat = cudaGetLastError();
71 if (stat == cudaSuccess)
76 // If we would find an error in a release build, we do not know
77 // what is appropriate to do about it, so assert only for debug
79 auto fullMessage = formatString(
80 "%s An unhandled error from a previous CUDA operation was detected. %s: %s",
81 errorMessage, cudaGetErrorName(stat), cudaGetErrorString(stat));
82 GMX_ASSERT(stat == cudaSuccess, fullMessage.c_str());
83 // TODO When we evolve a better logging framework, use that
84 // for release-build error reporting.
85 gmx_warning("%s", fullMessage.c_str());
91 enum class GpuApiCallBehavior;
93 /* TODO error checking needs to be rewritten. We have 2 types of error checks needed
94 based on where they occur in the code:
95 - non performance-critical: these errors are unsafe to be ignored and must be
96 _always_ checked for, e.g. initializations
97 - performance critical: handling errors might hurt performance so care need to be taken
98 when/if we should check for them at all, e.g. in cu_upload_X. However, we should be
99 able to turn the check for these errors on!
101 Probably we'll need two sets of the macros below...
104 #define CHECK_CUDA_ERRORS
106 #ifdef CHECK_CUDA_ERRORS
108 /*! Check for CUDA error on the return status of a CUDA RT API call. */
109 # define CU_RET_ERR(status, msg) \
112 if (status != cudaSuccess) \
114 gmx_fatal(FARGS, "%s: %s\n", msg, cudaGetErrorString(status)); \
118 /*! Check for any previously occurred uncaught CUDA error. */
119 # define CU_CHECK_PREV_ERR() \
122 cudaError_t _CU_CHECK_PREV_ERR_status = cudaGetLastError(); \
123 if (_CU_CHECK_PREV_ERR_status != cudaSuccess) \
126 "Just caught a previously occurred CUDA error (%s), will try to " \
128 cudaGetErrorString(_CU_CHECK_PREV_ERR_status)); \
132 #else /* CHECK_CUDA_ERRORS */
134 # define CU_RET_ERR(status, msg) \
138 # define CU_CHECK_PREV_ERR() \
143 #endif /* CHECK_CUDA_ERRORS */
145 /*! \brief CUDA device information.
147 * The CUDA device information is queried and set at detection and contains
148 * both information about the device/hardware returned by the runtime as well
149 * as additional data like support status.
151 struct gmx_device_info_t
153 int id; /* id of the CUDA device */
154 cudaDeviceProp prop; /* CUDA device properties */
155 int stat; /* result of the device check */
158 /*! Launches synchronous or asynchronous device to host memory copy.
160 * The copy is launched in stream s or if not specified, in stream 0.
162 int cu_copy_D2H(void* h_dest, void* d_src, size_t bytes, GpuApiCallBehavior transferKind, cudaStream_t /*s = nullptr*/);
164 /*! Launches synchronous host to device memory copy in stream 0. */
165 int cu_copy_D2H_sync(void* /*h_dest*/, void* /*d_src*/, size_t /*bytes*/);
167 /*! Launches asynchronous host to device memory copy in stream s. */
168 int cu_copy_D2H_async(void* /*h_dest*/, void* /*d_src*/, size_t /*bytes*/, cudaStream_t /*s = nullptr*/);
170 /*! Launches synchronous or asynchronous host to device memory copy.
172 * The copy is launched in stream s or if not specified, in stream 0.
174 int cu_copy_H2D(void* d_dest, const void* h_src, size_t bytes, GpuApiCallBehavior transferKind, cudaStream_t /*s = nullptr*/);
176 /*! Launches synchronous host to device memory copy. */
177 int cu_copy_H2D_sync(void* /*d_dest*/, const void* /*h_src*/, size_t /*bytes*/);
179 /*! Launches asynchronous host to device memory copy in stream s. */
180 int cu_copy_H2D_async(void* /*d_dest*/, const void* /*h_src*/, size_t /*bytes*/, cudaStream_t /*s = nullptr*/);
182 // TODO: the 2 functions below are pretty much a constructor/destructor of a simple
183 // GPU table object. There is also almost self-contained fetchFromParamLookupTable()
184 // in cuda_kernel_utils.cuh. They could all live in a separate class/struct file.
186 /*! \brief Initialize parameter lookup table.
188 * Initializes device memory, copies data from host and binds
189 * a texture to allocated device memory to be used for parameter lookup.
191 * \tparam[in] T Raw data type
192 * \param[out] d_ptr device pointer to the memory to be allocated
193 * \param[out] texObj texture object to be initialized
194 * \param[in] h_ptr pointer to the host memory to be uploaded to the device
195 * \param[in] numElem number of elements in the h_ptr
198 void initParamLookupTable(T*& d_ptr, cudaTextureObject_t& texObj, const T* h_ptr, int numElem);
200 // Add extern declarations so each translation unit understands that
201 // there will be a definition provided.
202 extern template void initParamLookupTable<int>(int*&, cudaTextureObject_t&, const int*, int);
203 extern template void initParamLookupTable<float>(float*&, cudaTextureObject_t&, const float*, int);
205 /*! \brief Destroy parameter lookup table.
207 * Unbinds texture object, deallocates device memory.
209 * \tparam[in] T Raw data type
210 * \param[in] d_ptr Device pointer to the memory to be deallocated
211 * \param[in] texObj Texture object to be deinitialized
214 void destroyParamLookupTable(T* d_ptr, cudaTextureObject_t texObj);
216 // Add extern declarations so each translation unit understands that
217 // there will be a definition provided.
218 extern template void destroyParamLookupTable<int>(int*, cudaTextureObject_t);
219 extern template void destroyParamLookupTable<float>(float*, cudaTextureObject_t);
221 /*! \brief Add a triplets stored in a float3 to an rvec variable.
223 * \param[out] a Rvec to increment
224 * \param[in] b Float triplet to increment with.
226 static inline void rvec_inc(rvec a, const float3 b)
228 rvec tmp = { b.x, b.y, b.z };
232 /*! \brief Wait for all taks in stream \p s to complete.
234 * \param[in] s stream to synchronize with
236 static inline void gpuStreamSynchronize(cudaStream_t s)
238 cudaError_t stat = cudaStreamSynchronize(s);
239 CU_RET_ERR(stat, "cudaStreamSynchronize failed");
242 /*! \brief Returns true if all tasks in \p s have completed.
244 * \param[in] s stream to check
246 * \returns True if all tasks enqueued in the stream \p s (at the time of this call) have completed.
248 static inline bool haveStreamTasksCompleted(cudaStream_t s)
250 cudaError_t stat = cudaStreamQuery(s);
252 if (stat == cudaErrorNotReady)
254 // work is still in progress in the stream
258 GMX_ASSERT(stat != cudaErrorInvalidResourceHandle, "Stream idnetifier not valid");
260 // cudaSuccess and cudaErrorNotReady are the expected return values
261 CU_RET_ERR(stat, "Unexpected cudaStreamQuery failure");
263 GMX_ASSERT(stat == cudaSuccess,
264 "Values other than cudaSuccess should have been explicitly handled");
269 /* Kernel launch helpers */
272 * A function for setting up a single CUDA kernel argument.
273 * This is the tail of the compile-time recursive function below.
274 * It has to be seen by the compiler first.
276 * \tparam totalArgsCount Number of the kernel arguments
277 * \tparam KernelPtr Kernel function handle type
278 * \param[in] argIndex Index of the current argument
280 template<size_t totalArgsCount, typename KernelPtr>
281 void prepareGpuKernelArgument(KernelPtr /*kernel*/,
282 std::array<void*, totalArgsCount>* /* kernelArgsPtr */,
283 size_t gmx_used_in_debug argIndex)
285 GMX_ASSERT(argIndex == totalArgsCount, "Tail expansion");
289 * Compile-time recursive function for setting up a single CUDA kernel argument.
290 * This function copies a kernel argument pointer \p argPtr into \p kernelArgsPtr,
291 * and calls itself on the next argument, eventually calling the tail function above.
293 * \tparam CurrentArg Type of the current argument
294 * \tparam RemainingArgs Types of remaining arguments after the current one
295 * \tparam totalArgsCount Number of the kernel arguments
296 * \tparam KernelPtr Kernel function handle type
297 * \param[in] kernel Kernel function handle
298 * \param[in,out] kernelArgsPtr Pointer to the argument array to be filled in
299 * \param[in] argIndex Index of the current argument
300 * \param[in] argPtr Pointer to the current argument
301 * \param[in] otherArgsPtrs Pack of pointers to arguments remaining to process after the current one
303 template<typename CurrentArg, typename... RemainingArgs, size_t totalArgsCount, typename KernelPtr>
304 void prepareGpuKernelArgument(KernelPtr kernel,
305 std::array<void*, totalArgsCount>* kernelArgsPtr,
307 const CurrentArg* argPtr,
308 const RemainingArgs*... otherArgsPtrs)
310 (*kernelArgsPtr)[argIndex] = (void*)argPtr;
311 prepareGpuKernelArgument(kernel, kernelArgsPtr, argIndex + 1, otherArgsPtrs...);
315 * A wrapper function for setting up all the CUDA kernel arguments.
316 * Calls the recursive functions above.
318 * \tparam KernelPtr Kernel function handle type
319 * \tparam Args Types of all the kernel arguments
320 * \param[in] kernel Kernel function handle
321 * \param[in] argsPtrs Pointers to all the kernel arguments
322 * \returns A prepared parameter pack to be used with launchGpuKernel() as the last argument.
324 template<typename KernelPtr, typename... Args>
325 std::array<void*, sizeof...(Args)> prepareGpuKernelArguments(KernelPtr kernel,
326 const KernelLaunchConfig& /*config */,
327 const Args*... argsPtrs)
329 std::array<void*, sizeof...(Args)> kernelArgs;
330 prepareGpuKernelArgument(kernel, &kernelArgs, 0, argsPtrs...);
334 /*! \brief Launches the CUDA kernel and handles the errors.
336 * \tparam Args Types of all the kernel arguments
337 * \param[in] kernel Kernel function handle
338 * \param[in] config Kernel configuration for launching
339 * \param[in] kernelName Human readable kernel description, for error handling only
340 * \param[in] kernelArgs Array of the pointers to the kernel arguments, prepared by
341 * prepareGpuKernelArguments() \throws gmx::InternalError on kernel launch failure
343 template<typename... Args>
344 void launchGpuKernel(void (*kernel)(Args...),
345 const KernelLaunchConfig& config,
346 CommandEvent* /*timingEvent */,
347 const char* kernelName,
348 const std::array<void*, sizeof...(Args)>& kernelArgs)
350 dim3 blockSize(config.blockSize[0], config.blockSize[1], config.blockSize[2]);
351 dim3 gridSize(config.gridSize[0], config.gridSize[1], config.gridSize[2]);
352 cudaLaunchKernel((void*)kernel, gridSize, blockSize, const_cast<void**>(kernelArgs.data()),
353 config.sharedMemorySize, config.stream);
355 cudaError_t status = cudaGetLastError();
356 if (cudaSuccess != status)
358 const std::string errorMessage =
359 "GPU kernel (" + std::string(kernelName)
360 + ") failed to launch: " + std::string(cudaGetErrorString(status));
361 GMX_THROW(gmx::InternalError(errorMessage));