[hpc-announce] [Call for Papers] Programming Model Alternatives to Message Passing (PMAMP)-2017
emani1 at llnl.gov
Mon May 15 12:53:53 CDT 2017
Call for papers
First Annual Workshop on Programming Model Alternatives to Message Passing (PMAMP)-2017
September 25, 2017, Chicago, IL in collaboration with EuroMPI/USA 2017
Message-passing programming models have dominated high-performance computing (HPC) for the past quarter century. With the continued breakdown of the (uniform) communicating sequential processors abstract machine model, many researchers have questioned the continued viability of message passing as a model for direct, application-level interaction. Recent years have seen an explosion of new paradigms in programming models for distributed-memory computing. The move to the next generation of HPC platforms presents a wider variety of challenges than ever before, that include the increased need for asynchrony, increased heterogeneity and performance non-uniformity, decreased hardware reliability and increased failure rates, increased hardware diversity, and the maintainability of increasingly complex scientific code bases.
This workshop proposes to promote a dialogue between researchers who work on extensions or augmentations to message-passing models (the “evolutionary” crowd) to alternative programming models and to expose those who develop fundamentally different programming models (the “revolutionary” crowd) to the recent advances in message-passing programming models. It aims to help understand the relative importance of the concerns these new approaches address. The workshop seeks to garner a better understanding of key motivations for alternative programming models, key insights from advances in message passing (and how they can be applied to alternative models), and key opportunities for collaboration between researchers on both sides.
We solicit preliminary work on programming models that offer extensions or alternatives to message passing, with emphasis on addressing emerging concerns in high performance computing (HPC), including topics relating to (but are not restricted to) the following:
* Performance non-uniformity
* Fault-tolerance and resilience
* Performance portability: a posteriori adaptability (“one code for many machines”) in situ adaptability (reactive and dynamic runtime system solutions)
* Maintainability (particularly in the presence of these other challenges)
* Testability and debuggability (particularly in the presence of these other challenges)
* Experimental comparative results (particularly with emphasis on overall time-to-solution)
* Relevance of alternate programming models to particular scientific kernels
Also, we solicit position papers on analyzing the importance (or lack thereof) of the above topics for the future of HPC, again with emphasis on the need (or lack thereof) to address these concerns at the programming model level (thus, for instance, arguments for why the challenges can be addressed at other levels of the software stack without programming model intervention will also be considered).
* Paper submission: June 15, 2017
* Author Notification: July 10, 2017
* Camera-ready papers due: July 30, 2017
* Workshop Date: September 25, 2017
· David S Hollman, Sandia National Laboratory
· Murali Emani, Lawrence Livermore National Laboratory
Program Committee: (Preliminary)
* Abhinav Bhatele, Lawrence Livermore National Laboratory
* Alex Aiken, Stanford
* Jesper Larsson Träff, TU Wien
* Karl Fuerlinger, LMU Munich
* Ron Brightwell, Sandia National Laboratory
* Zoran Budimlic, Rice University
* Hartmut Kaiser, Louisiana State University
* Sean Treichler, Nvidia
* Bryce Adelstein Lelbach, Lawrence Berkeley National Laboratory
* Martin Schulz, Lawrence Livermore National Laboratory
Interested authors are encouraged to submit full papers (8-10 pages) or short/position papers (4 pages) in "sigconf" style in the ACM 2017 template. This page limit includes figures, tables and appendices but not references. Authors should submit their work at (https://easychair.org/conferences/?conf=pmamp1).
More details of this workshop could be found at https://memani1.github.io/pmamp17/.
Center for Applied Scientific Computing,
Lawrence Livermore National Laboratory, USA
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