Scientific Application Requirements for Leadership Computing at the Exascale

Technical Report · Sat Dec 01 04:00:00 EST 2007

DOI:https://doi.org/10.2172/1081802· OSTI ID:1081802

Ahern, Sean ^[1]; Alam, Sadaf R. ^[1]; Fahey, Mark R. ^[1]; Hartman-Baker, Rebecca J. ^[1]; Barrett, Richard F. ^[1]; Kendall, Ricky A. ^[1]; Kothe, Douglas B. ^[1]; Mills, Richard T. ^[1]; Sankaran, Ramanan ^[1]; Tharrington, Arnold N. ^[1]; White III, James B. ^[1]

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1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

The Department of Energy’s Leadership Computing Facility, located at Oak Ridge National Laboratory’s National Center for Computational Sciences, recently polled scientific teams that had large allocations at the center in 2007, asking them to identify computational science requirements for future exascale systems (capable of an exaflop, or 10¹⁸ floating point operations per second). These requirements are necessarily speculative, since an exascale system will not be realized until the 2015–2020 timeframe, and are expressed where possible relative to a recent petascale requirements analysis of similar science applications. Our initial findings, which beg further data collection, validation, and analysis, did in fact align with many of our expectations and existing petascale requirements, yet they also contained some surprises, complete with new challenges and opportunities. First and foremost, the breadth and depth of science prospects and benefits on an exascale computing system are striking. Without a doubt, they justify a large investment, even with its inherent risks. The possibilities for return on investment (by any measure) are too large to let us ignore this opportunity. The software opportunities and challenges are enormous. In fact, as one notable computational scientist put it, the scale of questions being asked at the exascale is tremendous and the hardware has gotten way ahead of the software. We are in grave danger of failing because of a software crisis unless concerted investments and coordinating activities are undertaken to reduce and close this hardware-software gap over the next decade. Key to success will be a rigorous requirement for natural mapping of algorithms to hardware in a way that complements (rather than competes with) compilers and runtime systems. The level of abstraction must be raised, and more attention must be paid to functionalities and capabilities that incorporate intent into data structures, are aware of memory hierarchy, possess fault tolerance, exploit asynchronism, and are power-consumption aware. On the other hand, we must also provide application scientists with the ability to develop software without having to become experts in the computer science components.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1081802
• Report Number(s): ORNL/TM--2011/250
• Country of Publication: United States
• Language: English