Distributed Computing with Python. Francesco Pierfederici

Distributed Computing with Python


Distributed.Computing.with.Python.pdf
ISBN: 9781785889691 | 156 pages | 4 Mb


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Distributed Computing with Python Francesco Pierfederici
Publisher: Packt Publishing, Limited



A workflow is created from user-written Python functions (nodes) connected by ' pipes' (edges) into a directed acyclic graph. We describe a general purpose master-worker parallel computation Python module called PyMW. Pydra provides an easy to use framework for writing, running and managingdistributed computing jobs in python. RPyC (pronounced as are-pie-see), or Remote Python Call, is a transparent for symmetrical remote procedure calls, clustering and distributed-computing. But also facilities for interactive distributed and par- allel computing, as well as a comprehensive set of tools for building special-purpose interactive envi-. Rossant C, Fontaine B, Goodman DFM. Hosted at PyPI [http://pythonhosted.org/mpi4py/]: A. This article looks at the advantages or drawbacks RPyC has over otherdistributed Python frameworks such as XML-RPC and Pyro. A short introduction and tutorial to distributed memory computing with Python. Playdoh: a lightweight Python package for distributed computing and optimisation.





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