Date: 18 Aug 2000

On the Predictive Quality of BSP-like Cost Functions for NOWs

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Abstract

The Bulk-Synchronous Parallel (BSP) model [16] provides a simple and portable programming discipline that is particularly suitable for coarse-grained parallel systems such as Networks of Workstations (NOWs). In this work we examine the issue of predictability of the BSP cost function for a NOW consisting of SUN workstations connected through a 10Mbps Ethernet network. In particular, we compare the original BSP cost function with a number of newly proposed variants, with the intent of improving predictability by having the cost function encompass those parameters of the hardware/software system which have the largest impact on performance.

This research was supported, in part, by the Italian CNR, and by MURST under Project Algorithms for Large Data Sets: Science and Engineering.