We consider a simple task: adding up two arrays of the same length (same number of elements). We first write a C++ program add.cpp solving this problem. It can be compiled by using g++ (or cl.exe): g++ add.cpp 1. Running the exe...
nvcc-arch=sm_50-code=sm_50 my_cuda_program.cu-omy_cuda_program 1. 代码示例:计算两个数组的和 以下是一个简单的CUDA代码示例,它计算两个数组的和。我们将在代码中设置GPU架构,以确保代码能够在支持的GPU上高效执行。 #include<iostream>#include<cuda.h>// CUDA kernel to add two arrays__global__vo...
We’ll start with a simple C++ program that adds the elements of two arrays with a million elements each.#include <iostream> #include <math.h> // function to add the elements of two arrays void add(int n, float *x, float *y) { for (int i = 0; i < n; i++) y[i] = x[...
人工智能编程face2ai.com/program-blog/#GPU%E7%BC%96%E7%A8%8B%EF%BC%88CUDA%EF%BC%89 ③...
The device encountered an invalid program counter. This leaves the process in an inconsistent state and any further CUDA work will return the same error. To continue using CUDA, the process must be terminated and relaunched. cudaErrorLaunchFailure = 719 An exception occurred on the device while...
A non-portable cluster size may only function on the specific SKUs the program is tested on. The launch might fail if the program is run on a different hardware platform.CUDA API provides cudaOccupancyMaxActiveClusters to assist with checking whether the desired size can be launched on the ...
下面的program,根据用户的输入,配置了核函数MyKernel的启动项基于占用量 // Device code__global__voidMyKernel(int*array,intarrayCount){intidx=threadIdx.x+blockIdx.x*blockDim.x;if(idx<arrayCount){array[idx]*=array[idx];}}// Host codeintlaunchMyKernel(int*array,intarrayCount){intblockSize;/...
cudaMalloc((void **)&d_C, N * sizeof(float)); // Copy vectors A and B from host to device cudaMemcpy...threads AddTwoVectors>>(d_A, d_B, d_C); // Copy vector C from device to host cudaMemcpy...除此之外,我们还需要通过调用cudaMalloc函数在设备上分配内存,并利用cudaMemcpy函数在...
Add Two Vectors This example extends the previous one to add two vectors together. For simplicity, assume that there are exactly the same number of threads as elements in the vectors and that there is only one thread block. The CU code is slightly different from the last example. Both input...
Bank conflicts are avoidable in most CUDA computations if care is taken when accessing __shared__ memory arrays. We can avoid most bank conflicts in scan by adding a variable amount of padding to each shared memory array index we compute. Specifically, we add to the index the value of the...