ARCHER News
Tuesday 2nd May 2017
- Webinar : Performance analysis on ARCHER using CrayPAT
- ARCHER Champions : Save the date
- PAW17- The 2nd Annual PGAS Applications Workshop : Call for papers
- Training : Upcoming ARCHER Training Opportunities
Webinar : Performance analysis on ARCHER using CrayPAT - a case study with live demos : Wednesday 10th May 3pm
Gordon Gibb, EPCC.
Profiling tools are extremely useful in understanding where a program is spending its time, which is an essential part of any performance optimisation exercise. In this webinar we will explain how profilers work, and look in detail at CrayPat which is the tool designed specifically for Cray systems such as ARCHER. How to use CrayPat in practice will be explained using live demos on a representative parallel program.
More information and connection details...
ARCHER Champions : Save the date
The next meeting of ARCHER Champions will be held from lunchtime on Monday 26th June to lunchtime on Tuesday 27th June at STFC, Daresbury.
Save the date in your diary and watch out for full details to be announced soon.
PAW17- The 2nd Annual PGAS Applications Workshop: Call for papers
http://sourceryinstitute.github.io/PAW/
Held in conjunction with SC 17: The International Conference for High Performance Computing, Networking, Storage and Analysis http://sc17.supercomputing.org
In cooperation with SIGHPC
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.
Significant improvements in the availability of PGAS compilers and support software have been achieved in the last few years; these open up more opportunities than ever for researchers and developers to test new strategies and port applications to more demanding requirements.
Following on the success of PAW16, we invite you to take part in the second PGAS Application Workshop, and to join its vibrant and diverse community of researchers and developers.
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.
We also specifically encourage submissions covering big data analytics, deep learning, and other novel and emerging application areas, beyond traditional scientific HPC domains.
Topics include, but are not limited to:
- Novel application development using the PGAS model.
- Real-world examples demonstrating performance, compiler optimization, error checking, and/or reduced software complexity.
- Applications from big data analytics, bioinformatics, and other novel areas.
- 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.
IMPORTANT DATES:
- Submission Deadline: July 31, 2017
- Author Notification: September 1, 2017
- Camera Ready: October 1, 2017
- Workshop Date: November 13, 2017
SUBMISSIONS
Submissions are solicited in two categories:
- Full-length papers presenting novel research results:
Full-length papers will be published in the workshop proceedings in cooperation with SIGHPC. Submitted papers must be original work that has not appeared in, and is not under consideration for, another conference or a journal. Papers shall not exceed eight (8) pages including text, appendices, and figures. References are not included. - Extended abstracts summarizing published/preliminary results:
Extended abstracts will be evaluated separately and will not be included in the published proceedings; they are intended for timely communications of novel work that is going to be formally submitted elsewhere at a later stage, and/or of already published work that is nonetheless deemed appropriate for dissemination in this venue. Extended abstracts shall not exceed four (4) pages.
Submissions shall be submitted through EasyChair (https://easychair.org/conferences/?conf=paw17); they must conform to ACM Guidelines (http://www.acm.org/publications/proceedings-template). Accepted full-length papers will be given longer presentation slots at the workshop; extended abstracts will be given shorter time slots.
WORKSHOP CHAIR
Karla Morris - Sandia National Laboratories
ORGANIZING COMMITTEE
- Bradford L. Chamberlain - Cray Inc.
- Salvatore Filippone - Cranfield University
- Costin Iancu - Lawrence Berkeley National Laboratory
- Bill Long - Cray Inc.
PROGRAM COMMITTEE CHAIR and CO-CHAIR
- Francesco Rizzi - Sandia National Laboratories (Chair)
- Bill Long - Cray Inc. (Co-Chair)
PROGRAM COMMITTEE
- Bradford L. Chamberlain - Cray Inc.
- Bert de Jong - Lawrence Berkeley National Laboratory
- James Dinan - Intel
- Salvatore Filippone - Cranfield University, UK
- Jeff Hammond - Intel
- Costin Iancu - Lawrence Berkeley National Laboratory
- Karla Morris - Sandia National Laboratories
- Nicholas Park - U.S. Department of Defense
- Anton Shterenlikht - University of Bristol
- Min Si - Argonne National Laboratory
- Lauren L. Smith - U.S. Department of Defense
- Yili Zheng - Google
ADVISORY COMMITTEE
- Katherine A. Yelick - Lawrence Berkeley National Laboratory
- Damian W. I. Rouson - Sourcery Institute
In case of questions please email us at: paw17@cranfield.ac.uk
Upcoming Training Opportunities
- Scientific Computing 31st May, 7th, 14th & 21st June 2017 Edinburgh and Online
- ARCHER Summer School 2017
- Hands-on Introduction to HPC 10-11 July 2017 Edinburgh
- Message-passing Programming with MPI 12-14 July 2017 Edinburgh
- Shared-Memory Programming with OpenMP 1-2 Aug 2017 Oxford
