FLENS is short for Flexible Library for Efficient Numerical Solutions. This C++ can be used as a builing block for the implementation of other (higher-level) numerical libraries or numerical applications. It is a C++ library (requires a C++11 conform compiler). Easy install, as FLENS is headers only. It gives you Matrix/vector types for dense linear algebra; a generic (i.e. templated) implementation of BLAS; and a generic reimplementation of LAPACK. If high performance BLAS libraries like ATLAS, GotoBLAS, etc. are available, you simply can link against them and boost performance.
GHCN Processor is a command-line tool that reads temperature data from the Global Historical Climatic Network (GHCN) database and produces an annual or monthly temperature series in CSV format for an arbitrary set of stations. Stations are filtered based on a simple EL expression passed to the tool. For example, you can select only stations that are in the Northern Hemisphere, in hilly and rural locations. You can also select stations that started reporting in a given year, and so on. The tool supports more than one method of grid partitioning, station combination, and can use both the adjusted data and raw unadjusted data.
GRALE is a set of tools - a library and a number of accompanying applications - to study gravitational lenses. Gravitational lenses are astronomical objects so massive that their gravitational pull even deflects light rays. This can cause multiple copies of the same background object to be visible, like a cosmic mirage. The locations and shapes of these copies can provide information about the mass distribution of the gravitational lens, which GRALE can help recover using a genetic algorithm-based method. Apart from these so-called lens inversions, it's also possible to simulate gravitational lenses.
Global Paths Matching is an implementation of the global paths graph matching algorithm proposed by Maue and Sanders in "Engineering Algorithms for Approximate Weighted Matching" (WEA'07). Given a graph G=(V,E), a matching M is a set of edges without common vertices, i.e. the graph G=(V,M) has a degree of at most one. The algorithm scans the edges in order of decreasing weight (or rating), constructing a collection of paths and even length cycles. These paths initially contain no edges. While scanning the edges, the set is extended by successively adding applicable edges, which are those connecting two endpoints of different paths or two endpoints of an odd length path. Optimal solutions/matchings are computed for each path and cycle using dynamic programming.
GraphInsight is visualization software that lets you explore graph data through high quality interactive representations. Data exploration and knowledge extraction from graphs is of great interest nowadays: knowledge is disseminated in social networks, and services are powered by cloud computing platforms. Data miners deal with graphs every day. Humans are extremely good at identifying patterns and outliers. Interacting visually with your data can give you better intuition and higher confidence in what you are looking for.
GriF is a collaborative grid framework to support computational chemistry applications. It is meant to be used as a tool to facilitate massive grid calculations and also to improve scientific collaboration. Accordingly, GriF facilitates profiling the users of grid communities in order to systematically evaluate the work carried out in a grid and to foster its sustainability.
HEALPix is a set of scientific tools implementing the Hierarchical Equal Area isoLatitude Pixelation of the sphere. As suggested in the name, this pixelation produces a subdivision of a spherical surface in which every single pixel covers the same surface area. HEALPix provides various programs and libraries in C, C++, Fortran, GDL/IDL, Java, and Python which facilitate discretization, simulation, processing, analysis, and visualization of data on the sphere up to very high resolution. It is the state-of-the-art program used in astronomy and cosmology to deal with massive full-sky data sets.
KaHIP - Karlsruhe High Quality Partitioning - is a family of graph partitioning programs that tackle the balanced graph partitioning problem. It focuses on solution quality and implements flow-based methods, more-localized local searches, and several parallel and sequential meta-heuristics.