# Understanding Quaternions

Understanding Quaternions

In this article I will attempt to explain the concept of Quaternions in an easy to understand way. I will explain how you might visualize a Quaternion as well as explain the different operations that can be applied to quaternions. I will also compare applications of matrices, euler angles, and quaternions and try to explain when you would want to use quaternions instead of Euler angles or matrices and when you would not.

# Introduction to Shader Programming with Cg 3.1

NVIDIA Cg

In this article I will introduce the reader to shader programming using the Cg shader programming language. I will use OpenGL graphics API to communicate with the Cg shaders. This article does not explain how use OpenGL. If you require an introduction to OpenGL, you can follow my previous article titled Introduction to OpenGL.

# Using OpenGL Vertex Buffer Objects

Vertex Buffer Object

In this article, I will explain how to use the ARB_vertex_buffer_object extension to efficiently render geometry in OpenGL.
If you are not sure how to use extensions in OpenGL, you can refer to my previous article titled OpenGL Extensions. If you have never programmed an OpenGL application before, you can refer to my previous article titled Introduction to OpenGL.

# CUDA Case Study – N-Body Simulation

CUDA N-Body Simulation

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.

# Introduction to OpenCL

OpenCL

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.

# Optimizing CUDA Applications

NVIDIA Logo

In this article I will discuss a few of the best practices items as described in the “CUDA C Best Practices Guide”. This guide mentions about 40 best practices over more than 70 pages of documentation. This might be a bit more information than the average casual programmer will care to understand. In this article, I want to focus on what I feel are the most important best practices that will result in a direct performance increase to your CUDA application. If you are not familiar with CUDA yet, you may want to refer to my previous articles titled Introduction to CUDA, CUDA Thread Execution, and CUDA memory.

# OpenGL Interoperability with CUDA

Postprocess Effect

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.

# CUDA Memory Model

CUDA Memory Model

In this article, I will introduce the different types of memory your CUDA program has access to. I will talk about the pros and cons for using each type of memory and I will also introduce a method to maximize your performance by taking advantage of the different kinds of memory.
I will assume that the reader already knows how to setup a project in Microsoft Visual Studio that takes advantage of the CUDA programming API. If you don’t know how to setup a project in Visual Studio that uses CUDA, I recommend you follow my previous article titled [Introduction to CUDA]