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GPU Programming

GPU Programming includes frameworks and languages such as OpenCL that allow developers to write programs that execute across different platforms. It can provide programs with the ability to access the GPU on a graphics card for non-graphics applications.

Great Reads

by Ryan S White
CudaPAD is a PTX/SASS viewer for NVIDIA Cuda kernels and provides an on-the-fly view of your Cuda code.
by Chris Boss
With mobile computing taking hold, programmers are looking for ways to produce smaller and faster applications. Soon with the so called “Internet of Things” concept bringing possibly even smaller mobile devices into all areas of life, the need for smaller and faster software capable of r
by Debdatta Basu
Examine the various approaches to implementing radix sort on the GPU.
by Alesiani Marco
A Wave PDE simulation using GPGPU capabilities

Latest Articles

by Ryan S White
an assembler/compiler for AMD’s GCN (Generation Core Next Architecture) Assembly Language
by Shao Voon Wong
Finding lexicographical permutations on GPU
by Ryan S White
CudaPAD is a PTX/SASS viewer for NVIDIA Cuda kernels and provides an on-the-fly view of your Cuda code.
by John Michael Hauck
It has never been easier for C# desktop developers to write code that takes advantage of the amazing computing performance of modern graphics cards. In this post I will share some ad hoc performance test results for a simple program written in C# as obtained from my current desktop computer, a Dell

Discussions

by Member 12729838 on article "CPU Computing Using CUDA, Eclipse,...
by Tomas HomeCat on article "GCN Assembler for AMD GPUs"
by Val Kool on Article "Install Cuda and Use Managed Code...

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