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Generation of high-performance code based on a domain-specific language for algorithmic skeletons

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Abstract

Parallel programming can be difficult and error prone, in particular if low-level optimizations are required in order to reach high performance in complex environments such as multi-core clusters using MPI and OpenMP. One approach to overcome these issues is based on algorithmic skeletons. These are predefined patterns which are implemented in parallel and can be composed by application programmers without taking care of low-level programming aspects. Support for algorithmic skeletons is typically provided as a library. However, optimizations are hard to implement in this setting and programming might still be tedious because of required boiler plate code. Thus, we propose a domain-specific language for algorithmic skeletons that performs optimizations and generates low-level C++ code. Our experimental results on four benchmarks show that the models are significantly shorter and that the execution time and speedup of the generated code often outperform equivalent library implementations using the Muenster Skeleton Library.

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Notes

  1. The model-driven software development community prefers the notion DSL model rather than DSL program.

  2. Due to the lack of space, only the overall structure and the main concepts of the language are presented here and an excerpt of the DSL is given in Listing 2. The full DSL specification can be found in our code repository [25].

  3. The Xtext representation of the full DSL is available in our code repository [25].

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Authors and Affiliations

  1. Department of Information Systems, University of Muenster, European Research Center for Information Systems (ERCIS), Leonardo-Campus 3, 48149, Muenster, Germany

    Fabian Wrede, Christoph Rieger & Herbert Kuchen

Authors
  1. Fabian Wrede
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  2. Christoph Rieger
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  3. Herbert Kuchen
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Correspondence to Fabian Wrede.

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Wrede, F., Rieger, C. & Kuchen, H. Generation of high-performance code based on a domain-specific language for algorithmic skeletons. J Supercomput 76, 5098–5116 (2020). https://doi.org/10.1007/s11227-019-02825-6

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