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Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations
| Content Provider | ACM Digital Library |
|---|---|
| Author | Dorier, Matthieu Antoniu, Gabriel Sisneros, Robert Snir, Marc Ibrahim, Shadi Cappello, Franck Peterka, Tom Orf, Leigh Yildiz, Orcun |
| Copyright Year | 2016 |
| Description | Author Affiliation: Inria, Rennes - Bretagne Atlantique Research Centre, France(University of illinois at urbana champaign, IL (Sisneros, Robert; Peterka, Tom); Snir, Marc; Cappello, Franck; Argonne national laboratory, IL, USA (Dorier, Matthieu; University of wisconsin - madison, WI (Orf, Leigh); Ibrahim, Shadi); Yildiz, Orcun; Antoniu, Gabriel) |
| Abstract | With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. This variability significantly impacts the overall application performance at scale and its predictability over time. In this article, we present Damaris, a system that leverages dedicated cores in multicore nodes to offload data management tasks, including I/O, data compression, scheduling of data movements, in situ analysis, and visualization. We evaluate Damaris with the CM1 atmospheric simulation and the Nek5000 computational fluid dynamic simulation on four platforms, including NICS’s Kraken and NCSA’s Blue Waters. Our results show that (1) Damaris fully hides the I/O variability as well as all I/O-related costs, thus making simulation performance predictable; (2) it increases the sustained write throughput by a factor of up to 15 compared with standard I/O approaches; (3) it allows almost perfect scalability of the simulation up to over 9,000 cores, as opposed to state-of-the-art approaches that fail to scale; and (4) it enables a seamless connection to the VisIt visualization software to perform in situ analysis and visualization in a way that impacts neither the performance of the simulation nor its variability. In addition, we extended our implementation of Damaris to also support the use of dedicated nodes and conducted a thorough comparison of the two approaches—dedicated cores and dedicated nodes—for I/O tasks with the aforementioned applications. |
| Starting Page | 1 |
| Ending Page | 43 |
| Page Count | 43 |
| File Format | |
| ISSN | 23294949 |
| e-ISSN | 23294957 |
| DOI | 10.1145/2987371 |
| Volume Number | 3 |
| Issue Number | 3 |
| Journal | ACM Transactions on Parallel Computing (TOPC) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-10-25 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Damaris Exascale computing I/O Dedicated cores Dedicated nodes In situ visualization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Hardware and Architecture Modeling and Simulation Computer Science Applications Software Computational Theory and Mathematics |
