CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) model created by NVIDIA. It allows software developers to use a CUDA-enabled graphics processing unit (GPU) for general purpose processing.

Overview

  • What is CUDA? CUDA is a parallel computing platform and programming model that enables dramatic increases in computing performance by using the power of graphics processing units (GPUs).

  • Why use CUDA? GPUs are highly parallel processors, and CUDA allows developers to leverage this parallelism to accelerate applications that are compute-intensive.

Key Concepts

  • CUDA Kernels CUDA kernels are the functions that run on the GPU. They are written in a C-like language and can be executed in parallel by thousands of GPU cores.

  • Memory Hierarchy CUDA has a memory hierarchy that includes global memory, shared memory, and registers. Each type of memory has its own characteristics and is used for different purposes.

Getting Started

  • NVIDIA CUDA Toolkit The NVIDIA CUDA Toolkit provides the necessary tools to develop CUDA applications. It includes a compiler, a debugger, and various libraries.

  • CUDA C/C++ CUDA applications are typically written in CUDA C/C++. They can access both the GPU and CPU resources, allowing for efficient computation.

Example

Here's a simple CUDA kernel that computes the sum of an array:

__global__ void sumArray(int *a, int *b, int *c) {
    int tid = threadIdx.x;
    c[tid] = a[tid] + b[tid];
}

Learn More

For more information on CUDA, please visit the NVIDIA CUDA Developer website.

[center] CUDA Kernel [center]