Accession Number : ADA536972


Title :   Best-First Heuristic Search for Multicore Machines


Descriptive Note : Journal article


Corporate Author : NEW HAMPSHIRE UNIV DURHAM DEPT OF COMPUTER SCIENCE


Personal Author(s) : Burns, Ethan ; Lemons, Sofia ; Ruml, Wheeler ; Zhou, Rong


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a536972.pdf


Report Date : Jan 2010


Pagination or Media Count : 56


Abstract : To harness modern multicore processors, it is imperative to develop parallel versions of fundamental algorithms. In this paper, we compare different approaches to parallel best-first search in a shared-memory setting. We present a new method, PBNF, that uses abstraction to partition the state space and to detect duplicate states without requiring frequent locking. PBNF allows speculative expansions when necessary to keep threads busy. We identify and fix potential livelock conditions in our approach, proving its correctness using temporal logic. Our approach is general, allowing it to extend easily to suboptimal and anytime heuristic search. In an empirical comparison on STRIPS planning, grid pathfinding, and sliding tile puzzle problems using 8-core machines, we show that A*, weighted A* and Anytime weighted A* implemented using PBNF yield faster search than improved versions of previous parallel search proposals.


Descriptors :   *HEURISTIC METHODS , REPRINTS , SEARCHING , ALGORITHMS , COMPARISON


Subject Categories : Operations Research


Distribution Statement : APPROVED FOR PUBLIC RELEASE