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Missile Plume Simulation Improvements Using GPU Chemical Kinetics Coprocessors
Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: W9113M-05-P-0085
Agency Tracking Number: 05-0104T
Amount:
$99,965.00
Phase:
Phase I
Program:
STTR
Solicitation Topic Code:
MDA05-T018
Solicitation Number:
N/A
Timeline
Solicitation Year:
2005
Award Year:
2005
Award Start Date (Proposal Award Date):
2005-09-19
Award End Date (Contract End Date):
2006-03-18
Small Business Information
6210 Keller's Church Road, Pipersville, PA, 18947
DUNS:
929950012
HUBZone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Principal Investigator
Name: Donald Kenzakowski
Title: Senior Research Scientist
Phone: (215) 766-1520
Email: kenzakow@craft-tech.com
Title: Senior Research Scientist
Phone: (215) 766-1520
Email: kenzakow@craft-tech.com
Business Contact
Name: Sanford Dash
Title: President & Chief Scientist
Phone: (215) 766-1520
Email: dash@craft-tech.com
Title: President & Chief Scientist
Phone: (215) 766-1520
Email: dash@craft-tech.com
Research Institution
Name: UNIV. OF NORTH CAROLINA
Contact: Dinesh Manocha
Address: CB #3175, Department of Computer Science
Chapel Hill, NC, 27599
Phone: (919) 962-1749
Type: Nonprofit college or university
Contact: Dinesh Manocha
Address: CB #3175, Department of Computer Science
Chapel Hill, NC, 27599
Phone: (919) 962-1749
Type: Nonprofit college or university
Abstract
High-fidelity missile plume flowfield simulations of MDA interest require use of detailed chemical kinetic mechanisms, which significantly improve IR/UV/RCS/visible signature prediction but entail long solution runtimes for completion. These long runtimes result from the required iterative solution of large systems of stiff, non-linear chemical source terms at each CFD mesh point; this curtails their routine use for practical systems-level studies. The standard approach for improving runtime performance, using distributed massively parallel clusters, has limited speed-up capability since it relies on very fine-grained domain decompositions, which increase inter-processor communication overhead and introduce numerical boundary stiffness issues. Alternatively, Graphical Processor Units (GPUs) have several hardware features conducive to scientific computing applications and are better suited to directly solving chemical kinetics problems using innovative data parallel algorithms. In this manner, GPUs can be effectively programmed as "chemical reaction co-processors." Time involved with GPU data transfer and computation can coincide with tasks remaining on the CPU to effectively minimize wall-clock time dedicated to chemical specie source term evaluation and hence remove a major plume simulation bottlenecking issue. * Information listed above is at the time of submission. *