dev_a = cuda.to_device(a) dev_b = cuda.to_device(b) dev_c = cuda.device_array((1,), dtype=a.dtype) dev_partial_c = cuda.device_array((blocks_per_grid,), dtype=a.dtype) dev_mutex = cuda.device_array((1,), dtype=np.int32) dot_partial[blocks_per_grid, threads_per_block]...
int dev = 0; // 定义device cudaDeviceProp deviceProp; // 定义deviceProp结构体 // CHECK(cudaGetDeviceProperties(&deviceProp, dev)); // 获取deviceProp结构体 cudaGetDeviceProperties(&deviceProp, dev); // 获取deviceProp结构体 printf("Using Device %d: %s\n", dev, deviceProp.name); // CHEC...
Cloud Studio代码运行 classLLTM(torch.nn.Module):def__init__(self,input_features,state_size):super(LLTM,self).__init__()self.input_features=input_features self.state_size=state_size #3*state_sizeforinput gate,output gate and candidate cell gate.# input_features+state_size because we will...
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importtorchimporttorch.nnasnn# 检查是否有GPU可用,并设置设备device = torch.device("cuda"iftorch.cuda.is_available()else"cpu")print(f"Using device:{device}")# 定义一个简单的卷积层classSimpleConvLayer(nn.Module):def__init__(self):super(SimpleConvLayer, self).__init__() ...
解析:__host__ int foo(int a){}表示由CPU调用的函数。__device__ int foo(int a){}表示由GPU调用的函数。__host__和__device__关键字可以连用,比如__host__ __device__ int foo(int a){}会被编译成两个版本,分别可以由CPU和GPU调用。
A technology introduced in Kepler-class GPUs and CUDA 5.0, enabling a direct path for communication between the GPU and a third-party peer device on the PCI Express bus when the devices share the same upstream root complex using standard features of PCI Express. This document introduces the tec...
The CUDA Toolkit targets a class of applications whose control part runs as a process on a general purpose computing device, and which use one or more NVIDIA GPUs as coprocessors for accelerating single program, multiple data (SPMD) parallel jobs. Such jobs are self-contained, in the sense ...
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//CudaKernel.cuh#include"cudaApi.h"#include"cuda_runtime.h"#include"device_launch_parameters.h"__global__voidaddKernel(int* c,constint* a,constint* b);CUDADD_APIintarrayAdd(int* a,int* b,int* c,intsize); CUDA核心实现代码[1][1]: ...