Welcome to the PGAS Applications Workshop.

• Proceedings
• Program
• Important dates
• Summary
• Scope and Aims
• Topics
• Submissions
• Organization
  • Workshop Chair
  • Organizing Committee
  • Program Committee Chair
  • Program Committee
• Contact

Program

• 2:00 - 2:05 Opening
• 2:05 - 2:50 Katherine Yelick
         Keynote Speaker
         PGAS: What, Where, and Why?
(Presentation)


• 2:50 - 3:00 Jacob Hemstad, Ulf Hanebutte, Ben Harshbarger and Brad Chamberlain
       A Study of the Bucket-Exchange Pattern in the PGAS Model Using the
       ISx Integer Sort Mini-Application
(Presentation, Extended Abstract)
      

• 3:00 - 3:30 Break


• 3:30 - 3:50 Anton Shterenlikht, Lee Margetts, Luis Cebamanos and Jose David Arregui-Mena
       Multi-scale CAFE framework for simulating fracture in heterogeneous materials
      implemented in Fortran coarrays and MPI
(Presentation)
• 3:50 - 4:10 Khaled Hamidouche, Jie Zhang, Karen Tomko and Dhabaleswar K. Panda
       OpenSHMEM NonBlocking Data Movement Operations with MVAPICH2-X: Early
      Experiences
(Presentation)
• 4:10 - 4:30 Hongzhang Shan, Weiqun Zhang, Yili Zheng, Samuel Williams, Stephane Ethier,
         Bei Wang and Zhengji Zhao
       Experiences of Applying One-Sided Communication to Nearest-Neighbor
      Communication
(Presentation)
• 4:30 - 4:50 Riyaz Haque and David Richards
       Optimizing PGAS overhead in a multi-locale Chapel implementation of CoMD
(Presentation)
• 4:50 - 5:00 Bruce Palmer
       Application of PGAS Programming to Power Grid Simulation
(Presentation)
• 5:00 - 5:30 Brad Chamberlain
       Panel Chair
       Panel Discussion
       Panelists:       
• William Carlson - IDA Center for Computing Sciences
• Evangelos Georganas - University of California Berkeley
• Bert de Jong - Lawrence Berkeley National Laboratory
• Damian Rouson - Sourcery Institute
• Min Si - Argonne National Laboratory

Important dates

• Submission Deadline: July 31, 2016 August 13, 2016 (final extension)
• Author Notification: September 9, 2016
• Camera Ready: October 1, 2016
• Workshop Date: November 14, 2016 (Room 251-B)

Summary

The race towards Exascale computing is on, and a lot of stress is put on researchers to break the boundaries of productivity and efficiency imposed by traditional programming models. Partitioned Global Address Space (PGAS) languages are an effective alternative, and the most promising path towards sustainable programming environments for exascale machines. Languages such as UPC, Fortran, Chapel, and X10 are now more widely available than ever, thanks to increased support from vendors and open-source communities. PGAS models also take the form of meta-languages and libraries, such as Unified Parallel C++ (UPC++), Co-Array C++, OpenSHMEM, MPI-3 and Global Arrays. These have the benefit of being integrated with existing languages, simplifying the learning curve for existing programmers.

The increasing availability of PGAS compilers and support software opens up more opportunities than ever for researchers and developers to test new strategies and port applications to more demanding requirements.

Scope and Aims

The scope of the PAW workshop is to provide a forum for exhibiting case studies of PGAS programming models in the context of real-world applications as a means of better understanding practical applications of PGAS technologies. We encourage the submission of papers and talks detailing practical PGAS applications, including characterizations of scalability and performance, of expressiveness and programmability, as well as any downsides or areas for improvement in existing PGAS models. In addition to informing other application programmers about the potential that is available through PGAS programming, the workshop is designed to communicate these experiences to compiler vendors, library developers, and system architects in order to achieve broader support for PGAS programming across the community.

Topics

Topics include, but are not limited to:

• Novel application development using the PGAS model
• Real-world examples demonstrating performance, compiler optimization, error checking, and reduced software complexity.
• Performance evaluation of applications running under PGAS
• Algorithmic models enabled by PGAS model
• Compiler and runtime environments
• Libraries using/supporting PGAS and applications
• Benefits of hardware abstraction and data locality on algorithm implementation.

Submissions

Submissions are solicited in two categories: