Xevolver: A code transformation framework for separation of system-awareness from application codes

Kazuhiko Komatsu, Ayumu Gomi, Ryusuke Egawa, Daisuke Takahashi, Reiji Suda, Hiroyuki Takizawa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


This paper introduces the Xevolver code transformation framework to separate system-aware code optimizations from HPC application codes. System-aware code optimizations often make it difficult for programmers to maintain HPC application codes. On the other side, system-aware code optimizations are mandatory to exploit the performance of target HPC systems. To achieve both high maintainability and high performance, the Xevolver framework provides an easy way to express system-aware code optimizations as user-defined code transformation rules. Those rules can be defined separately from HPC application codes. As a result, an HPC application code is converted into its optimized version for a particular target system just before the compilation, and standard HPC programmers do not usually need to maintain the optimized version that could be complicated and difficult-to-maintain. In this paper, three important components of the Xevolver framework are described, and then their practicality and benefits are demonstrated through six case studies. Accordingly, the user-defined code transformation approach behind the Xevolver framework is promising to express system-awareness for extracting the performance of an HPC system, and also for sharing expert knowledge and experiences about code optimizations. As the complexity and diversity of HPC system architectures are increasing in an extreme-scale computing era, system-aware code optimization without overcomplicating the code as discussed in this paper will become more and more important in the future.

Original languageEnglish
Article numbere5577
JournalConcurrency Computation Practice and Experience
Issue number7
Publication statusPublished - 2020 Apr 10


  • high-performance computing
  • performance optimization
  • separation of concern
  • system-awareness
  • user-defined code transformation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics


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