ANTLR: a predicated-LL(k) parser generator
Software—Practice & Experience
Techniques for the translation of MATLAB programs into Fortran 90
ACM Transactions on Programming Languages and Systems (TOPLAS)
A case for source-level transformations in MATLAB
Proceedings of the 2nd conference on Domain-specific languages
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
Adifor 2.0: Automatic Differentiation of Fortran 77 Programs
IEEE Computational Science & Engineering
SCAM '02 Proceedings of the Second IEEE International Workshop on Source Code Analysis and Manipulation
Proceedings of the 2nd international conference on Generative programming and component engineering
An efficient overloaded implementation of forward mode automatic differentiation in MATLAB
ACM Transactions on Mathematical Software (TOMS)
An efficient overloaded implementation of forward mode automatic differentiation in MATLAB
ACM Transactions on Mathematical Software (TOMS)
Accurate numerical derivatives in MATLAB
ACM Transactions on Mathematical Software (TOMS)
Automatic Fréchet Differentiation for the Numerical Solution of Boundary-Value Problems
ACM Transactions on Mathematical Software (TOMS)
An efficient overloaded method for computing derivatives of mathematical functions in MATLAB
ACM Transactions on Mathematical Software (TOMS)
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We present MSAD, a source transformation implementation of forward mode automatic differentiation for MATLAB. MSAD specialises and inlines operations from the fmad and derivvec classes of the MAD package. The operator overloading overheads inherent in MAD are eliminated while preserving the derivvec class’s optimised derivative combination operations. Compared to MAD, results from several test cases demonstrate significant improvement in efficiency across all problem sizes.