Affiliation:
1. Cornell Univ., Ithaca, NY
Abstract
ADMIT-1 enables the computation of
sparse
Jacobian and Hessian matrices, using automatic differentiation technology, from a MATLAB environment. Given a function to be differentiated, ADMIT-1 will exploit sparsity if present to yield sparse derivative matrices (in sparse MATLAB form). A generic automatic differentiation tool, subject to some functionality requirements, can be plugged into ADMIT-1; examples include ADOL-C (C/C++ target functions)and ADMAT (MATLAB target funcitons). ADMIT-1 also allows for the calculation of gradients and has several other related functions. This article provides an introduction to the design and usage of ADMIT-1.
Publisher
Association for Computing Machinery (ACM)
Subject
Applied Mathematics,Software
Reference22 articles.
1. Computing Large Sparse Jacobian Matrices Using Automatic Differentiation
2. BERZ M. BISCHOF C. CORLISS G. AND GRIEWANK A. Eds. 1996. Computational Differentiation: Techniques Applications and Tools. SIAM Philadelphia PA. BERZ M. BISCHOF C. CORLISS G. AND GRIEWANK A. Eds. 1996. Computational Differentiation: Techniques Applications and Tools. SIAM Philadelphia PA.
3. Computing Gradients in Large-Scale Optimization Using Automatic Differentiation
4. The Cyclic Coloring Problem and Estimation of Sparse Hessian Matrices
5. The Efficient Computation of Structured Gradients using Automatic Differentiation
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