Welcome to the PAW-ATM Workshop.

Program

Important dates

Summary

Architectural hierarchy and heterogeneity makes programming supercomputers challenging. In practice, HPC applications tend to be written using a mix of programming models—like C++, MPI, CUDA, and/or OpenMP—each of which is becoming more complex over time. This negatively impacts the costs of developing, maintaining, and porting HPC applications.

Meanwhile, alternative HPC programming models strive to improve things by raising the level of abstraction; incorporating modern features; and/or leveraging the respective strengths of programmers, compilers, and runtimes. These alternatives take the form of new languages (e.g., Chapel, Regent, XcalableMP), frameworks for large-scale data science (e.g., Arkouda, Dask, Spark), or extensions to existing languages (e.g., Charm++, COMPSs, Fortran, Legion, UPC++).

PAW-ATM is a forum for discussing HPC applications written in alternatives to MPI+X. Its goal is to bring together application experts and proponents of high-level languages to present concrete example uses of such alternatives, describing their benefits and challenges.

Scope and Aims

The PAW-ATM workshop aims to serve as a forum for exhibiting parallel applications developed using high-level parallel programming models that serve as alternatives to MPI+X-based programming. We encourage the submission of papers and talks from the community detailing practical distributed-memory applications written using alternatives to MPI+X, including characterizations of scalability and performance, expressiveness and programmability, as well as any downsides or areas for improvement in such models. In doing so, our hope is to create a setting in which application authors, language designers, and architects can present and discuss the state of the art in alternative scalable programming models while also wrestling with how to increase their effectiveness and adoption. Beyond well-established HPC scientific simulations, we also encourage submissions exploring artificial intelligence, big data analytics, machine learning, and other emerging application areas.

Topics

Topics of interest include, but are not limited to:

Papers that include description of applications that demonstrate the use of alternative programming models will be given higher priority.

Submissions

Submissions are solicited in two categories:

  • Full-length papers presenting novel research results:

  • Extended abstracts summarizing preliminary/published results:

    • When deciding between submissions with similar merit, submissions whose focus relates more directly to the key themes of the workshop (application studies, computing at scale, high-level alternatives to MPI+X) will be given priority over those that don't. In addition, full-length paper submissions will be given preference over extended abstracts.

    Submissions shall be submitted through Linklings using 10pt font in the IEEE format.

    PAW-ATM follows the reproducibility initiative of SC21. AD/AE sample form is available.

    Organization

    Workshop Chair

    Organizing Committee

    Program Committee Chairs

    Program Committee

    Advisory Committee

    Previous Instances of PAW-ATM