Self-adapting numerical software and automatic tuning of heuristics

Abstract

Self-Adapting Numerical Software (SANS) systems aim to bridge the knowledge gap that exists between the expertise of domain scientists, and the know-how that is needed to fulfill efficiently their computational demands. This know-how extends to algorith choice, computational grid utilization, and use of properly optimized kernels. A SANS system is a piece of meta software that mediates between the application program and the computational platform so that application scientists - with disparate levels of knowledge of algorithmic and programmatic complexities of the underlying numerical software - can easily realize numerical solvers and efficiently solve their problem. The main component of a SANS system is an Intelligent Agent that automates method selection based on data, algorithm and system attributes. The IA uses heuristics to make its decisions. In this paper we explain how the heuristics of the IA can be tuned over time by redundant testing and using the nature of many applications. © Springer-Verlag Berlin Heidelberg 2003.