Jug is a task-based parallelism framework. Jug allows you to write code that is broken up into tasks and run different tasks on different processors. It uses the filesystem to communicate between processes and works correctly over NFS, so you can coordinate processes on different machines. Jug is a pure Python implementation and should work on any platform that can run Python.
libjmmcg is a basic, low-level library with pretensions to implementing features above and beyond (but not necessarily better than!) those implemented within the Standard C++ Library and the Boost Library. It features a library for multi-core or multi-chip SMP parallelism, a suite of hashing algorithms, functions for raising numbers to integer powers, a generic factory wrapper and a generic, multi-threaded, read-only cache (which uses PPD), arguably the world's worst sorting technique, trace output, exceptions that have the file, line, revision, function, and argument details, string utilities, logging, simple command line processing, and much more.
YML is a research project that aims to provide tools for using global computing middleware such as GRID, peer to peer, and metacomputing environments. The YML software architecture enables the definition of parallel applications, independently of the underlying middleware used. Parallel applications are defined using a workflow language called YvetteML.