In this post, I will analyze the CUDA implementation of the N-Body simulation. The implementation that I will be using as a reference for this article is provided with the CUDA GPU Computing SDK 10.2. The source code for this implementation is available in the “%NVCUDASAMPLES_ROOT%\5_Simulations\nbody” in the GPU Computing SDK 10.2 samples base folder.
I assume the reader has a good understanding of the CUDA programming API.
In this article I will provide a brief introduction to OpenCL. OpenCL is a open standard for general purpose parallel programming across CPUs, GPUs, and other programmable parallel devices. I assume that the reader is familiar with the C/C++ programming languages. I will use Microsoft Visual Studio 2008 to show how you can setup a project that is compiled with the OpenCL API.
In this article I will discuss how you can use OpenGL textures and buffers in a CUDA kernel. I will demonstrate a simple post-process effect that can be applied to off-screen textures and then rendered to the screen using a full-screen quad. I will assume the reader has some basic knowledge of C/C++ programming, OpenGL, and CUDA. If you lack OpenGL knowledge, you can refer to my previous article titled Introduction to OpenGL or if you have never done anything with CUDA, you can follow my previous article titled Introduction to CUDA.
In this article, I will give a brief introduction to using NVIDIA’s CUDA programming API to perform General Purpose Graphics Processing Unit Programming (or just GPGPU Programming). I will also show how to setup a project in Visual Studio that uses the CUDA runtime API to create a simple CUDA program. Continue reading →