OSCATS (Open-Source Computerized Adaptive Testing System) implements Item Response Theory (IRT) and cognitively diagnostic (latent classification) models and item selection algorithms used in Computerized Adaptive Testing (CAT). OSCATS facilitates the development of CATs and simulations of CATs by providing ready-to-use code for running the CAT item selection and ability/classification estimation in an extensible, modular framework. The library is written in object-oriented C using GObject, and has bindings to Python, Perl, PHP, and Java.
Chebfun is a collection of algorithms and a software system in object-oriented MATLAB that extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD, and solves ordinary differential equations. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, recursive zerofinding, and automatic differentiation.
The Jacket platform consists of a runtime and language processing system that automatically optimizes existing applications or new algorithms for GPU computing. Jacket currently supports the MATLAB language as a frontend to the platform. Jacket's language processing system automatically translates MATLAB code to high performance primitives required for best utilization of Nvidia, CUDA capable GPUs. Working in concert with the translation system, Jacket's runtime system optimizes memory transfers, compiles code on-the-fly for realtime tuned performance, and launches GPU kernels efficiently for maximal performance. All GPU-specific programming details are handled by Jacket, freeing the user to focus on science, engineering, and analytics.