The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.
Thinknowlogy is grammar-based software designed to utilize the logic contained within grammar in order to create intelligence through a natural language, which is demonstrated by programming in a natural language, reasoning in a natural language (drawing conclusions, making assumptions (with a self-adjusting level of uncertainty), asking questions (about gaps in the knowledge), and detecting conflicts), and intelligent answering of "is" questions, providing alternative answers as well.
Dapper, or "Distributed and Parallel Program Execution Runtime", is a tool for taming the complexities of developing for large-scale cloud and grid computing, enabling the user to create distributed computations from the essentials: the code that will execute, along with a dataflow graph description. It supports rich execution semantics, carefree deployment, a robust control protocol, modification of the dataflow graph at runtime, and an intuitive user interface.
TooN is a very efficient numerics library for C++. The main focus of the library is efficient and safe handling of large numbers of small vector matrices and providing as much compile time checking as is possible. The library also works with large vectors and matrices and integrates easily with existing code. In addition to elementary vector and matrix operations, the library also providers linear solvers, matrix decompositions, optimization, and wrappers around LAPACK.
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.
FFTW++ is a C++ header class for the FFTW Fast Fourier Transform library that automates memory allocation, alignment, planning, and wisdom. In 2D and 3D, implicit dealiasing of convolutions substantially reduces memory usage and computation time. Wrappers for C, Python, and Fortran are included.
PEDSIM is a microscopic pedestrian crowd simulation system. The PEDSIM library allows you to use pedestrian dynamics in your own software. Based on pure C++/STL without additional packages, it runs virtually on every operating system. The PEDSIM Demo Application gives you a quick overview of the capabilities, and is a starting point for your own experiments. PEDSIM is suitable for use in crowd simulations (e.g. indoor evacuation simulation, large scale outdoor simulations), where one is interested in output like pedestrian density or evacuation time. Since the quality of the individual agent's trajectory is high, PEDSIM can be used for creating massive pedestrian crowds in movies.
Sally is a tool for mapping a set of strings to a set of vectors. This mapping is referred to as embedding and allows techniques of machine learning and data mining to be applied for the analysis of string data. It can be used with data such as text documents, DNA sequences, or log files. The vector space model or bag-of-words model is used. Strings are characterized by a set of features, where each feature is associated with one dimension of the vector space. Occurrences of the features in each string are counted. Alternatively, binary or TF-IDF values can be computed. Vectors can be output in plain text, LibSVM, or Matlab format.
Meta.Numerics is a Mono-compatible .NET library for scientific and numerical programming. It includes functionality for matrix algebra (including SVD, non-symmetric eigensystems, and sparse matrices), special functions of real and complex numbers (including Bessel functions and the complex error function), statistics and data analysis (including PCA, logistic and nonlinear regression, statistical tests, and nonuniform random deviates), and signal processing (including arbitrary-length FFTs).
StarCluster is a utility for creating traditional computing clusters used in research labs or for general distributed computing applications on Amazon's Elastic Compute Cloud (EC2). It uses a simple configuration file provided by the user to request cloud resources from Amazon and to automatically configure them with a queuing system, an NFS shared /home directory, passwordless SSH, OpenMPI, and ~140GB scratch disk space. It consists of a Python library and a simple command line interface to the library. For end-users, the command line interface provides simple intuitive options for getting started with distributed computing on EC2 (i.e. starting/stopping clusters, managing AMIs, etc). For developers, the library wraps the EC2 API to provide a simplified interface for launching/terminating nodes, executing commands on the nodes, copying files to/from the nodes, etc.