Jul 20, 2023

Distributed and Parallel Computing with/for Python

dispy is a comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine SMP, among many machines in a cluster, grid or cloud. dispy is well suited for data parallel SIMD paradigm where a computation Python function or standalone program is evaluated with different large datasets independently with no communication among computation tasks except for computation tasks sending Provisional/Intermediate Results or Transferring Files to the client. If communication/cooperation among tasks is needed, Distributed Communicating Processes module of pycos framework could be used.

Checkout these related ports:
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  • Zthread - Platform-independent object-oriented C++ threading library
  • Zookeeper - Coordination Service for Distributed Applications
  • Zls - Zig LSP implementation + Zig Language Server
  • Zfp - High throughput library for compressed floating-point arrays
  • Zeal - Offline documentation browser
  • Zapcc - C++ caching compiler based on clang
  • Zanata-platform - Web-based translation platform
  • Zanata-cli - Zanata Java command line client
  • Z88dk - Complete Z80/Z180 development kit
  • Z80ex - ZiLOG Z80 CPU emulator library
  • Z80asm - Assembler for the Z80 microprocessor
  • Z80-asm - Z80 assembly code assembler and disassembler