Abstract
A growing disparity between supercomputer computation speeds and I/O rates makes it increasingly infeasible for applications to save all results for offline analysis. Instead, applications must analyze and reduce data online so as to output only those results needed to answer target scientific question(s). This change in focus complicates application and experiment design and introduces algorithmic, implementation, and programming model challenges that are unfamiliar to many scientists and that have major implications for the design of various elements of supercomputer systems. We review these challenges and describe methods and tools that we are developing to enable experimental exploration of algorithmic, software, and system design alternatives.
Original language | English |
---|---|
Title of host publication | Euro-Par 2017 |
Subtitle of host publication | Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Proceedings |
Editors | Francisco F. Rivera, Tomas F. Pena, Jose C. Cabaleiro |
Publisher | Springer Verlag |
Pages | 3-19 |
Number of pages | 17 |
ISBN (Print) | 9783319642024 |
DOIs | |
State | Published - 2017 |
Event | 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2017 - Santiago de Compostela, Spain Duration: Aug 28 2017 → Sep 1 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 10417 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2017 |
---|---|
Country/Territory | Spain |
City | Santiago de Compostela |
Period | 08/28/17 → 09/1/17 |
Funding
Acknowledgments. This research was supported in part by the Exascale Computing Project (17-SC-20-SC) of the U.S. Department of Energy (DOE), and by DOE’s Advanced Scientific Research Office (ASCR) under contract DE-AC02-06CH11357.