𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Data structure and algorithms for fast automatic differentiation

✍ Scribed by I. Tsukanov; M. Hall

Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
425 KB
Volume
56
Category
Article
ISSN
0029-5981

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

In this paper we discuss the data structure and algorithms for the direct application of generalized Leibnitz rules to the numerical computation of partial derivatives in forward mode. The proposed data structure provides constant time access to the partial derivatives, which accelerates the automatic differentiation computations. The interaction among elements of the data structure is explained by several numerical examples. The paper contains analysis of the developed data structure and algorithms. Copyright Β© 2003 John Wiley & Sons, Ltd.

πŸ“œ SIMILAR VOLUMES

MDSIMAID: Automatic parameter optimizati
MDSIMAID: Automatic parameter optimization in fast electrostatic algorithms
✍ Michael S. Crocker; Scott S. Hampton; Thierry Matthey; JesΓΊs A. Izaguirre πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 206 KB

## Abstract MDSIMAID is a recommender system that optimizes parallel Particle Mesh Ewald (PME) and both sequential and parallel multigrid (MG) summation fast electrostatic solvers. MDSIMAID optimizes the running time or parallel scalability of these methods within a given error tolerance. MDSIMAID

Fast 1H–13C correlation data for use in
Fast 1H–13C correlation data for use in automatic structure confirmation of small organic compounds
✍ Adrian J. Dunn; Philip J. Sidebottom πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 141 KB

A method of speeding up the acquisition of 1H-13C correlation data has been developed. It is applicable in situations where the experiment time is determined by the need to sample the second dimension adequately rather than by signal-to-noise ratio requirements. Two spectra with different, reduced,

Sensitivity Derivatives for Advanced CFD
Sensitivity Derivatives for Advanced CFD Algorithm and Viscous Modeling Parameters via Automatic Differentiation
✍ Lawrence L Green; Perry A Newman; Kara J Haigler πŸ“‚ Article πŸ“… 1996 πŸ› Elsevier Science 🌐 English βš– 337 KB

The computational technique of automatic differentiation (AD) is applied to a complicated computer program to illustrate the simplicto achieve some optimal or constrained condition. Numerity, efficiency, and versatility of AD with complex algorithms for ous examples with SA used in such a context ca

Derived data structure algorithms for un
Derived data structure algorithms for unstructured finite element meshes
✍ Jacob Waltz πŸ“‚ Article πŸ“… 2002 πŸ› John Wiley and Sons 🌐 English βš– 107 KB

## Abstract A set of derived data structure algorithms for unstructured finite element meshes is presented. Both serial and parallel algorithms are described for each data structure. Colouring groups for the elements are used to facilitate parallelization on shared memory architectures. Scaling stu

Hierarchical hybrid grids: data structur
Hierarchical hybrid grids: data structures and core algorithms for multigrid
✍ Benjamin Karl Bergen; Frank HΓΌlsemann πŸ“‚ Article πŸ“… 2004 πŸ› John Wiley and Sons 🌐 English βš– 316 KB

## Abstract For many scientific and engineering applications, it is often desirable to use unstructured grids to represent complex geometries. Unfortunately, the data structures required to represent discretizations on such grids typically result in extremely inefficient performance on current high