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Summary
This summary is machine-generated.

This article introduces the Bulk Synchronous Farm (BSF) skeleton, a C++ tool for developing scalable parallel applications. It simplifies complex computations by managing parallelization and supporting iterative numerical algorithms.

Keywords:
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Area of Science:

  • Computer Science
  • Parallel Computing

Background:

  • The Bulk Synchronous Farm (BSF) model provides a framework for parallel computations using a master/slave paradigm.
  • Estimating parallel algorithm scalability before implementation is a key advantage of the BSF model.
  • Representing problem data as lists simplifies application logic in parallel computing.

Purpose of the Study:

  • To describe a method for creating applications for cluster computing systems.
  • To introduce the parallel BSF-skeleton for C++ development using the MPI library.
  • To facilitate the development of iterative numerical algorithms with high computational complexity.

Main Methods:

  • Utilizing the parallel BSF-skeleton based on the original BSF model.
  • Developing parallel programs in C++ with the Message Passing Interface (MPI) library.
  • Applying the master/slave paradigm for parallel computation management.

Main Results:

  • The BSF-skeleton encapsulates parallelization aspects, simplifying application development.
  • The skeleton enables error-free compilation throughout the application development lifecycle.
  • Support for the OpenMP programming model and workflows is integrated within the BSF-skeleton.

Conclusions:

  • The BSF-skeleton offers a robust method for building scalable parallel applications.
  • It simplifies the development of complex, iterative numerical algorithms for cluster computing.
  • The tool enhances development efficiency through encapsulated parallelization and error-free compilation.