6 projects tagged "Scientific Computing"
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.
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.
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.
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.
DAC (Dynamic Agent Computations) is a novel software framework designed for implementing multi-agent systems that describe parallel computations. The whole system is easy to configure and extend, but also very efficient and scalable. Moreover, the technology that is used (JMS, Cajo, JMX) ensures high reliability of the framework, which can be used in a production environment.
GarlicSim is a platform for writing, running, and analyzing simulations. It is general enough to handle any kind of simulation: physics, game theory, epidemic spread, electronics, etc. GarlicSim aims to eliminate the need to write any boilerplate code that isn't directly related to the phenomenon you're simulating. GarlicSim defines a new format for simulations, called a simulation package and often abbreviated as simpack. The simpack contains all the code that define the simulated system, and is simply a Python package which defines a few special functions according to the GarlicSim simpack API. Simpack code may also be written in C. All of the tools that GarlicSim provides can be used to run simulations of all kinds of different domains.