کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
432583 688961 2006 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Stack splitting: A technique for efficient exploitation of search parallelism on share-nothing platforms
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Stack splitting: A technique for efficient exploitation of search parallelism on share-nothing platforms
چکیده انگلیسی

We study the problem of exploiting parallelism from search-based AI systems on share-nothing platforms, i.e., platforms where different machines do not have access to any form of shared memory. We propose a novel environment representation technique, called stack-splitting, which is a modification of the well-known stack-copying technique, that enables the efficient exploitation of or-parallelism from AI systems on distributed-memory machines. Stack-splitting, coupled with appropriate scheduling strategies, leads to reduced communication during distributed execution and effective distribution of larger grain-sized work to processors. The novel technique can also be implemented on shared-memory machines and it is quite competitive. In this paper we present a distributed implementation of or-parallelism based on stack-splitting including results. Our results suggest that stack-splitting is an effective technique for obtaining high performance parallel AI systems on shared-memory as well as distributed-memory multiprocessors.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 66, Issue 10, October 2006, Pages 1267-1293