Projects / dispy

dispy

dispy is a Python framework for parallel execution of computations by distributing them across multiple processors in a single machine (SMP), or among many machines in a cluster or grid. The computations can be standalone programs or Python functions. dispy is well suited for the data parallel (SIMD) paradigm where a computation is evaluated with different (large) datasets independently (similar to Hadoop, MapReduce, Parallel Python). dispy features include automatic distribution of dependencies (files, Python functions, classes, modules), client-side and server-side fault recovery, scheduling of computations to specific nodes, encryption for security, sharing of computation resources if desired, and more.

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Recent releases

  •  24 Oct 2012 13:56

    Release Notes: The asyncoro module (an independent Python framework for asynchronous, concurrent, distributed network programming) has been updated to the latest release, which improves performance of message passing with coroutines.

    •  16 Aug 2012 14:28

      Release Notes: This release changes the license to the MIT license and updates asyncoro to the latest release.

      •  23 Jul 2012 22:15

        Release Notes: This release fixes occasional deadlock/potential crash issues during dispy shutdown and crashes with dispyscheduler (shared scheduler).

        •  08 Jul 2012 14:23

          Release Notes: This release updates asyncoro with support for distributed, fault-tolerant coroutines, and fixes an issue with parsing node selection in dispyscheduler.

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