cuMemcpyHtoDAsync和cuMemcpyDtoHAsync是CUDA编程中的两个异步内存拷贝函数。它们用于在主机和设备之间进行数据传输。具体解释如下: cuMemcpyHtoDAsync:这个函数用于将主机内存中的数据异步地拷贝到设备内存中。它接受源主机内存指针、目标设备内存指针、要拷贝的数据大小以及一个CUDA流作为参数。该函数将数据拷贝操作放...
void py_memcpy_dtoh_async(py::object dest, CUdeviceptr src, py::object stream_py) { py_buffer_wrapper buf_wrapper; buf_wrapper.get(dest.ptr(), PyBUF_ANY_CONTIGUOUS | PyBUF_WRITABLE); PYCUDA_PARSE_STREAM_PY; CUDAPP_CALL_GUARDED_THREADED(cuMemcpyDtoHAsync, (buf_wrapper.m_buf.buf, ...
@@ -183,6 +256,18 @@ CUresult cuMemcpyDtoHAsync (void *, CUdeviceptr, size_t, CUstream); CUresult cuMemcpyHtoD (CUdeviceptr, const void *, size_t); #define cuMemcpyHtoDAsync cuMemcpyHtoDAsync_v2 CUresult cuMemcpyHtoDAsync (CUdeviceptr, const void *, size_t, CUstream); #de...
memcpy_htod_async( self.cuda_inputs[0], self.host_inputs[0], self.stream) self.context.execute_async( batch_size=1, bindings=self.bindings, stream_handle=self.stream.handle) cuda.memcpy_dtoh_async( self.host_outputs[1], self.cuda_outputs[1], self.stream) cuda.memcpy_dtoh_async( ...
context.execute_async(batch_size=batch_size,bindings=bindings,stream_handle=stream.handle) # Transfer predictions back from the GPU. [cuda.memcpy_dtoh_async(out.host,out.device,stream)foroutinoutputs] # Synchronize the stream stream.synchronize() ...
context.execute_async(batch_size=batch_size,bindings=bindings,stream_handle=stream.handle) # Transfer predictions back from the GPU. [cuda.memcpy_dtoh_async(out.host,out.device,stream)foroutinoutputs] # Synchronize the stream stream.synchronize() ...
python 为什么Torch计算操作调用DtoH memcpy？https://pytorch.org/docs/stable/generated/torch.nonzero....