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.
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.
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.
The Pegasus Workflow Management System encompasses a set of technologies which help workflow-based applications execute in a number of different environments, including desktops, campus clusters, grids, and clouds. It bridges the scientific domain and the execution environment by automatically mapping high-level workflow descriptions onto distributed resources. It automatically locates the necessary input data and computational resources necessary for workflow execution. It enables scientists to construct workflows in abstract terms without worrying about the details of the underlying execution environment or the particulars of the low-level specifications required by the middleware (Condor, Globus, or Amazon EC2). It bridges the current cyberinfrastructure by effectively coordinating multiple distributed resources.