Cuda Toolkit Today

$(TARGET): $(SOURCES) $(NVCC) $(NVCC_FLAGS) -o $@ $^

.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)? cuda toolkit

// Verify result bool correct = true; for (int i = 0; i < n; i++) if (abs(h_c[i] - (h_a[i] + h_b[i])) > 1e-5) correct = false; break; $(TARGET): $(SOURCES) $(NVCC) $(NVCC_FLAGS) -o $@ $^

return 0; # Compile nvcc -o vector_add vector_add.cu Run ./vector_add Makefile for larger projects CUDA_PATH ?= /usr/local/cuda NVCC = $(CUDA_PATH)/bin/nvcc NVCC_FLAGS = -arch=sm_75 -O3 -std=c++17 TARGET = vector_add SOURCES = vector_add.cu "SUCCESS" : "FAILURE") &lt;&lt; std::endl;

std::cout << (correct ? "SUCCESS" : "FAILURE") << std::endl;