copy_to_host() if __name__ == "__main__": main() 进行Shared Memory优化后,计算部分的耗时减少了近一半: 代码语言:javascript 代码运行次数:0 复制Cloud Studio 代码运行 matmul time :1.4370720386505127 matmul with shared memory time :0.7994928359985352 补充说明 声明Shared Memory。这里使用了cuda....
int item = (blockIdx.x * blockDim.x) + threadIdx.x; if ( item < size ) { C[item] = A[item] + B[item]; } } 向量A、 B 和 C 存储在全局内存中。 上面这段代码很明显就是直接从host,copy过来的数据,这个就是全局内存。 默认情况下,在host上分配并作为参数传递给kernel的内存是在全局内...
intfilter(int*dst,constint*src,intn){intnres=0;for(inti=0;i<n;i++)if(src[i]>0)dst[nres++]=src[i];// return the number of elements copiedreturnnres;} 过滤,也称为流压缩(stream compaction),是一种常见的操作,它是许多编程语言标准库的一部分,它有多种名称,包括 grep、copy_if、select ...
Copy __global__ void calculate_forces(void *devX, void *devA) { extern __shared__ float4[] shPosition; float4 *globalX = (float4 *)devX; float4 *globalA = (float4 *)devA; float4 myPosition; int i, tile; float3 acc = {0.0f, 0.0f, 0.0f}; int gtid = blockIdx...
if (threadIdx.x == 0) { child_launch<<< 1, 256 >>>(data); cudaDeviceSynchronize(); } __syncthreads(); } void host_launch(int *data) { parent_launch<<< 1, 256 >>>(data); } D.2.2.1.2. Zero Copy Memory 零拷贝系统内存与全局内存具有相同的一致性和一致性保证,并遵循上面详述的语...
This is useful if the user is interested in the life range of any particular register, or register usage in general. Here’s a sample output (output is pruned for brevity): // +---+---+ // | GPR | PRED | // | | | // | | | // | 000000000011 | | // | # 012345678901 ...
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(i+1)*segment_size]=z_streams_device[i*segment_size:(i+1)*segment_size].copy_to_host(stream=stream_list[i])cuda.synchronize()print("gpu streams vector add time "+str(time()-start))if(np.array_equal(default_stream_result,streams_result)):print("result correct")if__name__=="__...
intmain(){printf("run_on_cpu_or_gpu CPU: %d\n",run_on_cpu_or_gpu());{int ret=run_on_gpu<<<1,1>>>();// error!!!even if run_on_gpu return int!!}printf("will end\n");return0;} 还有人会问,上面main函数怎么没有用修饰符修饰?cuda编程规定如果没有使用修饰符修饰的默认就是__...
//Copy result back to host memory from device memory cudaMemcpy(h_c, d_c, N * sizeof(int), cudaMemcpyDeviceToHost); cudaDeviceSynchronize(); int Correct = 1; printf("Vector addition on GPU \n"); //Printing result on console for (int i = 0; i < N; i++) { if ((h_a[i...