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Mapping Correlation Matrix Memory Applications onto a Beowulf Cluster

2001; Springer Science+Business Media; Linguagem: Inglês

10.1007/3-540-44668-0_22

1611-3349

Michael Weeks, Jim Austin, Anthony Moulds, Aaron Turner, Zygmunt Ulanowski, J Peter Young,

Blind Source Separation Techniques

The aim of the research reported in this paper was to assess the scalability of a binary correlation Matrix Memory (CMM) based on the PRESENCE (PaRallEl StructurEd Neural Computing Engine) architecture. A single PRESENCE card has a finite memory capacity, and this paper describes how multiple PCI-based PRESENCE cards are utilised in order to scale up memory capacity and performance. A Beowulf class cluster, called Cortex-1, provides the scalable I/O capacity needed for multiple cards, and techniques for mapping applications onto the system are described. The main aims of the work are to prove the scalability of the AURA architecture, and to demonstrate the capabilities of the architecture for commercial pattern matching problems.