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Dataflow parallel programminglanguage for clusters
PARUS is a data-flow parallel programminglanguage that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library.
Also there are available tools for benchmarking cluster interconnect and visualize it.
Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programminglanguage. Primarily targeted at evolutionary computing and similar master-slave configurations.
Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster