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.
LibBi is used for state-space modelling and Bayesian inference on high-performance computer hardware, including multi-core CPUs, many-core GPUs (graphics processing units), and distributed-memory clusters. The staple methods of LibBi are based on sequential Monte Carlo (SMC), also known as particle filtering. These methods include particle Markov chain Monte Carlo (PMCMC) and SMC2. Other methods include the extended Kalman filter and some parameter optimization routines. LibBi consists of a C++ template library and a parser and compiler, written in Perl, for its own modelling language.
Pyrit takes a step ahead in attacking WPA-PSK and WPA2-PSK, the protocols that protect today's public WiFi-airspace. Pyrit's implementation allows you to create massive databases, pre-computing part of the WPA/WPA2-PSK authentication phase in a space-time-tradeoff. The performance gain for real-world-attacks is in the range of three orders of magnitude, which urges for re-consideration of the protocol's security. It exploits the computational power of multiple cores and other platforms through ATI-Stream, Nvidia CUDA, OpenCL, and VIA Padlock. It is a powerful attack against one of the world's most used security-protocols.
Wisecracker is a high performance distributed cryptanalysis framework that leverages GPUs and multiple CPUs. It allows security researchers to write their own cryptanalysis tools that can distribute brute-force cryptanalysis work across multiple systems with multiple multi-core processors and GPUs. Security researchers can also use the sample tools provided out-of-the-box. The differentiating aspect of Wisecracker is that it uses OpenCL and MPI together to distribute the work across multiple systems, each having multiple CPUs and/or GPUs.