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Award Abstract #1149784

CAREER: Scalable Algorithms for Extreme Computing on Heterogeneous Hardware, with Applications in Fluids and Biology

NSF Org: ACI
Div Of Advanced Cyberinfrastructure
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Initial Amendment Date: March 5, 2012
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Latest Amendment Date: March 5, 2012
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Award Number: 1149784
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Award Instrument: Standard Grant
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Program Manager: Daniel Katz
ACI Div Of Advanced Cyberinfrastructure
CSE Direct For Computer & Info Scie & Enginr
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Start Date: March 1, 2012
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End Date: October 31, 2014 (Estimated)
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Awarded Amount to Date: $550,627.00
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Investigator(s): Lorena Barba labarba@gwu.edu (Principal Investigator)
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Sponsor: Trustees of Boston University
881 COMMONWEALTH AVE
BOSTON, MA 02215-1300 (617)353-4365
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NSF Program(s): CAREER: FACULTY EARLY CAR DEV
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Program Reference Code(s): 1045
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Program Element Code(s): 1045

ABSTRACT

There is currently a world-wide quest to achieve exascale computing by the end of the decade, with vigorous efforts in the US as well as China and Japan, in particular. In the US, the President's Strategy for American Innovation (2009) explicitly lists among its goals to dramatically increase our simulations capacity via an exascale computer. The challenges to achieve this goal are unprecedented: power constraints, microchip fabrication reaching physical limits, the growing imbalance between compute capacity and interconnect bandwidth, and the ever increasing number of cores in a system.

Among the matters of highest priority are development of scalable algorithms that can exploit the enormous parallelism of new systems, and educating the next generation of computational scientists. The first of these is at the center of the scientific part of this CAREER project. A potentially transformative combination is emerging where a class of hierarchical algorithms, offering ideal scaling linear with problem size, maps with excellent performance to many-core hardware (such as GPUs). Algorithmic improvements will be undertaken, such as combining elements of treecodes and fast multipole methods, communication and synchronization avoidance, dynamic error control and auto-tuning of the computation. The research program is vertically integrated across disciplines, including applications at extreme scales in fluid dynamics and biological systems.

This project will produce highly scalable scientific software, reformulating the algorithms to achieve maximum performance in many-core hardware. Disseminated and curated via the open-source model, the computational infrastructure delivered will offer maximum impact, beyond the application areas of focus. Community software that is able to scale to millions of processors will be crucial to exploit post-petascale systems, and this project aims to provide that. The educational part of this program, on the other hand, builds on the PI's track record of success both in the use of technology to support learning, and in catalyzing international collaboration and outreach. The program includes enhancing educational environments using technology for both curricular instruction and contributing to the nation's science literacy (via open courseware). The goals of fostering the next generation of computational scientists will be pursued via extra-mural advanced training events, and online learning media.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Barba, L.~A.. "The Gathering Storm: Flipping the Classroom," SHPE Magazine, v.26, 2014, p. 28--30.

Barba, L.~A. and Yokota, Rio. "How will the fast multipole method fare in the exascale era?," SIAM News, v.46, 2013, p. 1.

Rio Yokota, L. A. Barba. "Hierarchical N-body simulations with auto-tuning for heterogeneous systems," Computing in Science and Engineering (CiSE), v.14, 2012, p. 30?39. 

Yokota, Rio and Barba, L.~A.. "{FMM}-based vortex method for simulation of isotropic turbulence on {GPUs}, compared with a spectral method," Computers \& Fluids, v.80, 2013, p. 17--27. 

Yokota, Rio and Barba, L.~A.. "Hierarchical {$N$}-body simulations with auto-tuning for heterogeneous systems," Computing in Science and Engineering, v.14, 2012, p. 30--39. 

Rio Yokota, L. A. Barba. "A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems," Int. J. High-Perf. Comput., v.26, 2012, p. 337?346. 

Yokota, Rio and Barba, L.~A.. "A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems," Int.\ J. High-perf.\ Comput.\ Appl., v.26, 2012, p. 337--346. 

Rio Yokota, L. A. Barba. "FMM-based vortex method for simulation of isotropic turbulence on GPUs, compared with a spectral method," Computers & Fluids, v.80, 2013, p. 17?27. 

Rio Yokota, L. A. Barba, Tetsu Narumi, Kenji Yasuoka. "Petascale turbulence simulation using a highly parallel fast multipole method," Comput. Phys. Comm., v.184, 2012, p. 445?455. 

Yokota, Rio and Barba, L.~A. and Narumi, Tetsu and Yasuoka, Kenji. "Petascale turbulence simulation using a highly parallel fast multipole method," Comp.\ Phys.\ Comm., v.184, 2013, p. 445--455. 


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