The source code and dockerfile for the GSW2024 AI Lab.
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#include <iostream> #include <chrono>
__global__ void cuda_kernel_kernelSwitchTest(int const * const A, int * const B) { *B = *A; }
void kernelSwitchTest(size_t N) { int* deviceIntA; int* deviceIntB;
if (cudaMalloc((void**)&deviceIntA, sizeof(int)) != cudaSuccess) { std::cout << "Error in cudaMalloc while allocating " << sizeof(int) << " Bytes!" << std::endl; return; } if (cudaMalloc((void**)&deviceIntB, sizeof(int)) != cudaSuccess) { std::cout << "Error in cudaMalloc while allocating " << sizeof(int) << " Bytes!" << std::endl; return; }
// Allocate space on the device auto start_time = std::chrono::high_resolution_clock::now(); for (int i = 0; i < N; ++i) { cuda_kernel_kernelSwitchTest<<<1,1>>>(deviceIntA, deviceIntB); } auto end_time = std::chrono::high_resolution_clock::now(); std::cout << "Switching the Kernel " << N << " times took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl; std::cout << "Resulting in " << (std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() / ((double)(N))) << "Microseconds per Kernel Switch" << std::endl;
// Free memory on device if (cudaFree(deviceIntA) != cudaSuccess) { std::cout << "Error in cudaFree!" << std::endl; return; } if (cudaFree(deviceIntB) != cudaSuccess) { std::cout << "Error in cudaFree!" << std::endl; return; } }
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