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finish hw08 #1

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2 changes: 1 addition & 1 deletion CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ if (NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release)
endif()
# 如果需要指定显卡版本号的话:
# set(CMAKE_CUDA_ARCHITECTURES 52)
set(CMAKE_CUDA_ARCHITECTURES 75)

project(hellocmake LANGUAGES CXX CUDA)

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15 changes: 7 additions & 8 deletions main.cu
Original file line number Diff line number Diff line change
Expand Up @@ -8,18 +8,17 @@

// 这是基于“边角料法”的,请把他改成基于“网格跨步循环”的:10 分
__global__ void fill_sin(int *arr, int n) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n) return;
arr[i] = sinf(i);
for (int i = blockDim.x * blockIdx.x + threadIdx.x; i < n; i += blockDim.x * gridDim.x){
arr[i] = sinf(i);
}
}

__global__ void filter_positive(int *counter, int *res, int const *arr, int n) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < n) return;
if (arr[i] >= 0) {
// 这里有什么问题?请改正:10 分
int loc = *counter;
*counter += 1;
atomicAdd(&counter[0], 1);
res[loc] = n;
}
}
Expand All @@ -31,13 +30,13 @@ int main() {
std::vector<int, CudaAllocator<int>> counter(1);

// fill_sin 改成“网格跨步循环”以后,这里三重尖括号里的参数如何调整?10 分
fill_sin<<<n / 1024, 1024>>>(arr.data(), n);
fill_sin<<<1, 1024>>>(arr.data(), n);
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gridDim是不是太小了,可以改成 n / 8192之类的。


// 这里的“边角料法”对于不是 1024 整数倍的 n 会出错,为什么?请修复:10 分
filter_positive<<<n / 1024, 1024>>>(counter.data(), res.data(), arr.data(), n);
filter_positive<<<(n+1023) / 1024, 1024>>>(counter.data(), res.data(), arr.data(), n);

// 这里 CPU 访问数据前漏了一步什么操作?请补上:10 分

checkCudaErrors(cudaDeviceSynchronize());
if (counter[0] <= n / 50) {
printf("Result too short! %d <= %d\n", counter[0], n / 50);
return -1;
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