Abstract

This paper deals with data management for parallel and distributed systems. We present the DIVA (Distributed Variables ) library that provides direct access to shared data objects from each node in a network. The current implementations are based on mesh-connected massively parallel computers. Our algorithms dynamically create and discard copies of the data objects in order to reduce the communication overhead. We use a non-standard approach based on a randomized but locality preserving embedding of ``access trees'' into the network.

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