An excessive number of remote accesses or a non-uniform distribution of remote accesses can cause even well-designed multiprocessors to exhibit severe memory and network contention. Producer/consumer data generates a particularly common sharing pattern that results in a non-uniform distribution of references. In this paper we quantify the performance impact of producer/consumer sharing as a function of memory and network bandwidth, and argue that the contention caused by this form of sharing severely impacts performance on large-scale machines. We propose a new coherency protocol, called eager combining, which is designed to alleviate this contention. We use execution-driven simulation of parallel programs on a large-scale multiprocessor to show that eager combining can improve the performance of programs with producer/consumer data by a factor of 4 or more.
|Original language||English (US)|
|Number of pages||10|
|Journal||IEEE Symposium on Parallel and Distributed Processing - Proceedings|
|State||Published - Dec 1 1994|
|Event||Proceeedings of the 6th IEEE Symposium on Parallel and Distributed Processing - Dallas, TX, USA|
Duration: Oct 26 1994 → Oct 29 1994
ASJC Scopus subject areas