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.
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.
NVIDIA Logo
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
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]
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Grid of Thread Blocks
NVIDIA 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.
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Dynamic Linking Library
Google Analytics
In this article I will briefly summarize my own experiences while trying to maximize my website’s search engine presence. I will discuss my experience with choosing a good hosting provider, and getting a website started quickly.
I will also show how you can leverage the power of social media tools like Facebook and Twitter to further your website’s exposure.
If you decide to manage your own website then you will want to know how you can help search engines find and index your site. I will introduce a few tools that you can use on your own sites to ensure you can maximize your page rating so your website comes to the top of the search results.
If you can’t see how much interest your website is generating, then you won’t know if your hard work is paying off. I will also talk about Google’s solution to help you track your web site using Google Analytics.