An Approach for Parallelizing Legacy CFD Applications

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$99,996.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
W911W6-11-C-0034
Award Id:
n/a
Agency Tracking Number:
A111-001-0160
Solicitation Year:
2011
Solicitation Topic Code:
A11-001
Solicitation Number:
2011.1
Small Business Information
2836 Kincaid Street, Eugene, OR, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
167172308
Principal Investigator:
Ralph Bording
HPC Software Specialist
(541) 913-8797
chris@paratools.com
Business Contact:
Allen Malony
CEO
(541) 913-8797
malony@paratools.com
Research Institution:
Stub




Abstract
The project will develop and evaluate a systematic methodology to evolve legacy CFD wake modeling tools for rotorcraft engineering from sequential to parallel execution on high-performance workstations. The work will focus on sparse-grid elliptic solvers found in packages such as HELIX-IA due to their computational intensity and sequential performance bottleneck. The Phase I approach will be to isolate where and how the solvers are implemented and used, create interfaces that allow solver modules to be more easily invoked, and replace the sequential modules with parallel versions from robust matrix and solver libraries. The approach is founded on an extensive and deep background of expertise, tools, and technologies we have developed in parallel software analysis, parallel performance evaluation, numerical software, and HPC environments. The multi-disciplinary team of experts assembled include the developers of the TAU Performance System and PETSc who bring significant experience working with complex parallel software and computational simulation methods involving integration of sophisticated solver components. Successful completion of our project will create a strategy for code substitution that works well with CFD methods for Eulerian wake analysis, and a robust toolkit that can be refined in Phase II efforts to improve automation, platform porting, and parallel performance.

* information listed above is at the time of submission.

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