Call for Papers: Workshop on Data Analytics and Numerical Simulation with Partitioned Global Address Space Models (DANS-PGAS)

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Call for Papers

Workshop on Data Analytics and Numerical Simulation

with Partitioned Global Address Space Models (DANS-PGAS)

13 June 2017, Chicago, Illinois, USA

to be held in conjunction with

International Conference on Supercomputing

13-16 June 2017, Chicago, Illinois, USA

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Partitioned Global Address Space (PGAS) programming models have entered mainstream high-performance computing (HPC) in the form of open standards (MPI-3, OpenSHMEM and Fortran 2008) and are used across a wide range of application domains from quantum chemistry to graph analytics.  This workshop focuses on the application and implementation of programming models based upon the PGAS concept targeting all application domains and implementation approaches.

Topics of interest include, but are not limited to:

- Applications of PGAS models in data analytics and numerical simulation.

- Extensions of existing PGAS models to support threads and accelerators as well as non-SPMD PGAS models.

- Formal and empirical analysis of application and implementation performance.

- Development of PGAS programming environments, including performance tools, debuggers and reused libraries.

- Software and hardware implementations of PGAS, both for traditional HPC environments and new ones (e.g. cloud computing).

# Important Dates

Papers due:        7 May, 2017

Notification:     17 May, 2017

Event:            13 June 2017

# Websites

Submissions: https://easychair.org/conferences/?conf=danspgas2017

Information: https://press3.mcs.anl.gov/ics2017/dans-pgas/

# Submission Guidelines

ACM sigconf format (same as ICS), with a limit of 10 pages (including references).  Additional details will be available from the website.

# Organizers

Jeff Hammond, Intel (general co-chair)

Sameer Shende, University of Oregon (general co-chair)

Siddhartha Jana, Intel (proceedings chair)

# Program Committee

Lydia Duncan, Cray

Tarek El-Ghazawi, George Washington University

Fernanda Foertter, Oak Ridge National Laboratory

Kathryn Mohror, Lawrence Livermore National Laboratory

Stephen Poole, Open Source Software Solutions

Sreeram Potluri, NVIDIA

Wasi Rahman, Intel

Damian Rouson, Sourcery Institute

Andreas Schäfer, Google

Pavel Shamis, ARM

Sameer Shende, University of Oregon

Xin Zhao, Mellanox

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