Cuda Toolkit Exclusive 【Must Try】

clean: rm -f $(TARGET)

.PHONY: all run clean | Operation | Function | |-----------|----------| | Allocate GPU memory | cudaMalloc(&ptr, size) | | Free GPU memory | cudaFree(ptr) | | Copy to GPU | cudaMemcpy(dst, src, size, cudaMemcpyHostToDevice) | | Copy to CPU | cudaMemcpy(dst, src, size, cudaMemcpyDeviceToHost) | | Get GPU count | cudaGetDeviceCount(&count) | | Set active GPU | cudaSetDevice(device_id) | | Synchronize | cudaDeviceSynchronize() | | Error checking | cudaGetLastError() | Installation Check # Check CUDA version nvcc --version Check GPU driver & CUDA capability nvidia-smi Check available GPUs nvidia-smi -L This gives you a working starting point. Need a specific CUDA library example (cuBLAS for matrix multiplication, cuFFT for FFTs, or multi-GPU programming)?

all: $(TARGET)

// Allocate device memory float *d_a, *d_b, *d_c; cudaMalloc(&d_a, bytes); cudaMalloc(&d_b, bytes); cudaMalloc(&d_c, bytes);

// Cleanup cudaFree(d_a); cudaFree(d_b); cudaFree(d_c); delete[] h_a; delete[] h_b; delete[] h_c; cuda toolkit

// Initialize input vectors for (int i = 0; i < n; i++) h_a[i] = rand() / (float)RAND_MAX; h_b[i] = rand() / (float)RAND_MAX;

std::cout << (correct ? "SUCCESS" : "FAILURE") << std::endl; clean: rm -f $(TARGET)

Here’s a overview and a practical example to get you started. What is CUDA Toolkit? CUDA (Compute Unified Device Architecture) Toolkit is NVIDIA's parallel computing platform and programming model that enables dramatic speedups by leveraging GPU power for general-purpose processing.