1. APPLYING AUTOMATED MEMORY ALALYSIS TO IMPROVE ITERATIVE ALGORITHMS.
- Author
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Dennis, J. M. and Jessup, E. R.
- Subjects
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SPARSE matrices , *LINEAR algebra , *ALGORITHMS , *ACCESS to information , *INFORMATION retrieval , *ECONOMICS - Abstract
In this paper, we describe automated memory analysis, a technique to improve the memory efficiency of a sparse linear iterative solver. Our automated memory analysis uses a language processor to predict the data movement required for an iterative algorithm based upon a MATLAB implementation. We demonstrate how automated memory analysis is used to reduce the execution time of a component of a global parallel ocean model. In particular, code modifications identified or evaluated through automated memory analysis enable a significant reduction in execution time for the conjugate gradient solver on a small serial problem. Further, we achieve a 9% reduction in total execution time for the full model on 64 processors. The predictive capabilities of our automated memory analysis can be used to simplify the development of memory-efficient numerical algorithms or software. [ABSTRACT FROM AUTHOR]
- Published
- 2007
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