Automatic differentiation: Obtaining fast and reliable derivatives -- fast

Conference · Sat Dec 31 00:00:00 EST 1994

OSTI ID:86960

Bischof, C H; Khademi, P M; Pusch, G ^[1]; Carle, A ^[2]

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1. Argonne National Lab., IL (United States). Mathematics and Computer Science Div.
2. Rice Univ., Houston, TX (United States). Center for Research on Parallel Computation

In this paper, the authors introduce automatic differentiation as a method for computing derivatives of large computer codes. After a brief discussion of methods of differentiating codes, they review automatic differentiation and introduce the ADIFOR (Automatic DIfferentiation of FORtran) tool. They highlight some applications of ADIFOR to large industrial and scientific codes (groundwater transport, CFD airfoil design, and sensitivity-enhanced MM5 mesoscale weather model), and discuss the effectiveness and performance of their approach. Finally, they discuss sparsity in automatic differentiation and introduce the SparsLinC library.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States); National Science Foundation, Washington, DC (United States)
• DOE Contract Number: W-31109-ENG-38
• OSTI ID: 86960
• Report Number(s): ANL/MCS/CP-86446; CONF-9407190-1; ON: DE95014244; CNN: Agreement NCCW-0027; Agreement CCR-9120008; TRN: AHC29521%%16
• Resource Relation: Conference: 3. SIAM forum: symposium on control problems in industry, San Diego, CA (United States), 22-23 Jul 1994; Other Information: PBD: [1994]
• Country of Publication: United States
• Language: English

Related Subjects

99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
DIFFERENTIAL EQUATIONS
CALCULATION METHODS
ENVIRONMENTAL TRANSPORT
GROUND WATER
AIRFOILS
COMPUTER-AIDED DESIGN
METEOROLOGY
SPATIAL DISTRIBUTION
USES
COMPUTER CODES
AUTOMATION