CUDA，Compute Unified Device Architecture的简称，是由NVIDIA公司创立的基于他们公司生产的图形处理器GPUs（Graphics Processing Units,可以通俗的理解为显卡）的一个并行计算平台和编程模型。在
自此，关于异步并发执行部分的1.主机与GPU之间的并发执行；2.内核并发执行；3.数据传输和内核执行之间的...
constchar*src){while(*dst++=*src++);}__global__voidkernel(char*A){device_strcpy(A,"Hello, World!");}intmain(){char*d_hello;charhello[32];//cpu側メモリを確保cudaMalloc((void**)&d_hello,32);//gpu側メモリを確保kernel<<<1,1>>>(d_hello);cudaMemcpy(hello,d_hello,32,cudaMemcp...
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cudaMalloc((void**) &data,isize[0]*isize[1]*isize[2]*2*sizeof(float)); cudaMalloc((void**) &data_hat, alloc_max);#endif//accfft_init(nthreads);setup_time=-MPI_Wtime();/* Create FFT plan */#ifdefINPLACEaccfft_plan_gpuf * plan=accfft_plan_dft_3d_c2c_gpuf(n,data,data,c...
3=0x3 E tensorflow/stream_executor/cuda/cuda_driver.cc:1099] could not synchronize on CUDA context: CUDA_ERROR_LAUNCH_TIMEOUT :: No stack trace available E tensorflow/stream_executor/stream.cc:272] Error recording event in stream: error recording CUDA event on stream 0x1efe980: CUDA_ERROR_...
def execute_async(self, batch_size): [ cuda.memcpy_htod_async(inp.device, inp.host[:batch_size], self.stream) for inp in self.inputs if inp.device_input is False ] self.context.execute_async( batch_size=batch_size, bindings=self.bindings, stream_handle=self.stream.handle) [ cuda.mem...
unpackSignedData_kernel<<< blocks, threads >>>(cudaBuffer, &cuda_inp_buf[(windowBlocks-1) * nchan * 2]); cudaThreadSynchronize(); unpackTime += elapsed_time(&thetime); totalTime += elapsed_time(&starttime); fprintf( stderr, "cudaMemcpy time: %g, size: %d MB\n", cudaCopyTime,...
cuda.memcpy_dtoh_async(m.hdata, m.data, scopy) 开发者ID:Aerojspark,项目名称:PyFR,代码行数:10,代码来源:packing.py 示例5: copy ▲点赞 1▼ defcopy(self, fb, dim, pool, stream=None):fmt ='u1'ifself.pix_fmtin('yuv444p10','yuv420p10','yuv444p12'): ...
pmek.reset(newMatrixElementKernelDevice( devMomenta, devGs, devMatrixElements, gpublocks, gputhreads ) ); and madgraph4gpu/epochX/cudacpp/gg_tt.mad/SubProcesses/Bridge.h Line 210 in085f022 m_pmek.reset(newmg5amcGpu::MatrixElementKernelDevice( m_devMomentaC, m_devGsC, m_devMEsC, m_gp...