Here's an example CUDA program that demonstrates how to use CUDA to accelerate a simple matrix multiplication:
int main() // Allocate memory on the GPU float* A, *B, *C; cudaMalloc((void**)&A, 1024 * 1024 * sizeof(float)); cudaMalloc((void**)&B, 1024 * 1024 * sizeof(float)); cudaMalloc((void**)&C, 1024 * 1024 * sizeof(float)); cudatoolkit 12.6
# Example commands (verify specific URLs on NVIDIA Developer site) wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb sudo dpkg -i cuda-keyring_1.1-1_all.deb sudo apt-get update sudo apt-get install cuda-toolkit-12-6 Here's an example CUDA program that demonstrates how
is a "stability and performance" release. It does not radically change the API surface but solidifies the foundation for the Blackwell era and improves the daily developer experience through faster compilation and better tooling. 1024 * 1024 * sizeof(float))