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Production quality Ecosystem for Programming and Executing eXtreme-scale Applications (EPEXA)	default

EPEXA is an NSF-supported R&D project that will create a production-quality, general-purpose, community-supported, open-source software ecosystem that attacks the twin challenges of programmer productivity and portable performance for advanced scientific applications on modern high-performance computers. Of special interest are irregular and sparse applications that are poorly served by current programming and execution models.

The project addresses central challenges from modern computational science:

• Advances in predictive, high-fidelity simulation are characterized by increasingly irregular and dynamic computation (block sparse, low-rank, mixed representations, etc.).
• Ongoing technology trend in heterogeneous architectures with dynamically changing performance, and the need to increase concurrency at all scales.

EPEXA builds upon prior work performed by the TESSE (Task-based Environment for Scientific Simulation at Extreme Scale) project, and in particular aims to complete the design and provide robust implementation of TESSE's main C++ API, the Template Task Graph (TTG) that provides a powerful data-flow programming model. Specific project aims include:

• To extend, complete, and harden the successful TESSE research prototype providing its first production quality implementation using a community-based, science-driven approach.
• To grow and support the user community, associated applications, and research use cases.
• To create a community to design, maintain, support and to grow EPEXA in the future.
• To transform the scalability of key parts of new and existing numerical simulation codes, including enabling the development of new DSLs by utilizing the API of the EPEXA runtime, and by migration paths for both applications and application programmers to follow.

Our community and their driving applications: {#community}

• Robert Harrison

  • IACS, Stony Brook University
  • multiresolution numerical analysis (MADNESS) with applications to chemistry, material science, nuclear physics, and others.
  • dynamic programming algorithms

• Edward Valeev

  • Department of Chemistry, Virginia Tech
  • block-sparse tensor algebra (TiledArray)

• George Bosilca and Thomas Herault

  • ICL, The University of Tennessee, Knoxville
  • parallel programming and runtime (PaRSEC)

• Scott Thornton

  • Gerber Technology
  • geospatial AI

• Florian Bischoff

  • Humboldt University, Berlin
  • computational chemistry

• Wolfgang Bangerth

  • Department of Mathematics, Colorado State University
  • deal.II open-source finite-element engineering and physics

• Mohammad Mahdi Javanmard

  • Facebook Research

• Poornima Nookala

  • IACS, Stony Brook University

EPEXA Software Ecosystem {#ecosystem}

Presentations and other resources

NSF CSSI 2020 PI meeting poster

Funding {#funding}

The EPEXA project is supported by the National Science Foundation under grants OAC-1931387 at Stony Brook University, OAC1931347 at Virginia Tech, and ACI-1450300 at the University of Tennesse, Knoxville.

The TESSE project was supported by the National Science Foundation under grants ACI-1450344 at Stony Brook University, ACI-1450262 at Virginia Tech, and OAC-1931384 at the University of Tennesse, Knoxville.