ASC ATDM Level 2 Milestone #5325: Asynchronous Many-Task Runtime System Analysis and Assessment for Next Generation Platforms

Technical Report · Tue Sep 01 00:00:00 EDT 2015

DOI:https://doi.org/10.2172/1432926· OSTI ID:1432926

Baker, Gavin Matthew ^[1]; Bettencourt, Matthew Tyler ^[1]; Bova, Steven W. ^[1]; Franko, Ken ^[1]; Gamell, Marc ^[1]; Grant, Ryan ^[1]; Hammond, Simon David ^[1]; Hollman, David S. ^[1]; Knight, Samuel ^[1]; Kolla, Hemanth ^[1]; Lin, Paul ^[1]; Olivier, Stephen Lecler ^[1]; Sjaardema, Gregory D. ^[1]; Slattengren, Nicole Lemaster ^[1]; Teranishi, Keita ^[1]; Wilke, Jeremiah J. ^[1]; Bennett, Janine Camille ^[1]; Clay, Robert L. ^[1]; Kale, Laxkimant ^[2]; Jain, Nikhil ^[2] ; Mikida, Eric ^[2]; Aiken, Alex ^[3]; Bauer, Michael ^[3]; Lee, Wonchan ^[3]; Slaughter, Elliott ^[3]; Treichler, Sean ^[3]; Berzins, Martin ^[4]; Harman, Todd ^[4]; Humphreys, Alan ^[4]; Schmidt, John ^[4]; Sunderland, Dan ^[4]; Mccormick, Pat ^[5]; Gutierrez, Samuel ^[5]; Shulz, Martin ^[6]; Gamblin, Todd ^[6]; Bremer, Peer -Timo ^[6]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Univ. of Illinois, Urbana Champaign, IL (United States)
3. Stanford Univ., Stanford, CA (United States)
4. Univ. of Utah, Salt Lake City, UT (United States)
5. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
6. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

This report provides in-depth information and analysis to help create a technical road map for developing next-generation programming models and runtime systems that support Advanced Simulation and Computing (ASC) work- load requirements. The focus herein is on asynchronous many-task (AMT) model and runtime systems, which are of great interest in the context of "Oriascale7 computing, as they hold the promise to address key issues associated with future extreme-scale computer architectures. This report includes a thorough qualitative and quantitative examination of three best-of-class AIM] runtime systems – Charm-++, Legion, and Uintah, all of which are in use as part of the Centers. The studies focus on each of the runtimes' programmability, performance, and mutability. Through the experiments and analysis presented, several overarching Predictive Science Academic Alliance Program II (PSAAP-II) Asc findings emerge. From a performance perspective, AIV runtimes show tremendous potential for addressing extreme- scale challenges. Empirical studies show an AM runtime can mitigate performance heterogeneity inherent to the machine itself and that Message Passing Interface (MP1) and AM11runtimes perform comparably under balanced conditions. From a programmability and mutability perspective however, none of the runtimes in this study are currently ready for use in developing production-ready Sandia ASC applications. The report concludes by recommending a co- design path forward, wherein application, programming model, and runtime system developers work together to define requirements and solutions. Such a requirements-driven co-design approach benefits the community as a whole, with widespread community engagement mitigating risk for both application developers developers. and high-performance computing runtime systein

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1432926
• Report Number(s): SAND-2015-8312; 662088
• Country of Publication: United States
• Language: English