Libfairydust is a small wrapper library intended for use with GPU clusters that 'hijacks' CUDA and OpenCL calls. It can be used to 're-route' calls to a certain GPU, so a process requesting GPU#0 might end up running on GPU#4 without knowing (or caring) about it. This works completely transparently and does not need any sort of 'cooperation' from the application, changes to code, or relinking.
Moscrack is a WPA cracker for use on clusters. It supports MOSIX, SSH, and RSH connectivity and works by reading a word list from STDIN or a file, breaking it into chunks, and passing those chunks off to separate processes that run in parallel. The parallel processes are then executed on different nodes in your cluster. All results are checked and recorded on your master node. Logging and error handling are taken care of. It is capable of running reliably for long periods of time, without the risk of losing data or having to restart. Moscrack uses aircrack-ng by default. Pyrit for WPA cracking and Dehasher for Unix password hashes are supported via plugins.
CLOGS is a library for higher-level operations on top of the OpenCL C++ API. It is designed to integrate with other OpenCL code, including synchronization using OpenCL events. Currently only two operations are supported: radix sorting and exclusive scan. Radix sort supports all the unsigned integral types as keys, and all the built-in scalar and vector types suitable for storage in buffers as values. Scan supports all the integral types. It also supports vector types, which allows limited multi-scan capabilities.
GPUMarkerTracker is a tracking software library for AR (augmented reality) markers. It utilizes GPGPU for fast and accurate tracking. It is intended for detecting markers from an HD resolution image so that small markers placed far from the camera can be detected. Each marker has a 12-bit payload with 9-bit CRC. The library does not produce false-positive detection errors of markers, practically.
PyParticles is a particle simulation toolbox entirely written in Python. It simulates a particle-by-particle model with the most popular integrations methods, including Euler, Runge Kutta, and Midpoint. It represents the results on an OpenGL or Matplotlib plot, and offers an easy-to-use API.