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Static Analysis for Automatic Differentiation

Award Information

Agency:
National Aeronautics and Space Administration
Branch:
N/A
Award ID:
56632
Program Year/Program:
2002 / SBIR
Agency Tracking Number:
013668
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
GrammaTech, Inc.
531 Esty Street Ithaca, NY 14850-4201
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2002
Title: Static Analysis for Automatic Differentiation
Agency: NASA
Contract: NAS2-02020
Award Amount: $69,941.00
 

Abstract:

Differentiation is the single most important numerical operation inscientific computing. Creating derivative functions manually or byusing finite differencing is error-prone, time-consuming andpotentially inaccurate. Automatic differentiation (AD) holds great promisefor overcoming these problems, but it has not caught on beyond ahandful of research laboratories because the naive approaches used areinefficient. Sophisticated static analysis of source code is requiredto overcome these inefficiencies. Such tools are difficult andexpensive to produce. GrammaTech has a fifteen-year investment inadvanced general-purpose static analysis tools which can be targetedtowards this problem. Our dependence-graph technology is capable ofproviding exactly the right kinds of analysis needed to help createefficient derivatives. We propose to build a system for AD that willuse our dependence-graph technology to provide exactly the right kindsof analysis needed to help create efficient derivatives.

Principal Investigator:

Paul Anderson
Principal Investigator
6072737340
paul@grammatech.com

Business Contact:

Ray Teitelbaum
Chairman
6072737340
tt@grammatech.com
Small Business Information at Submission:

GrammaTech, Inc.
317 North Aurora Street Ithaca, NY 14850

EIN/Tax ID: 161338879
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No