Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Scalable parallel formulations of depth-first search
Parallel algorithms for machine intelligence and vision
Criticizing solutions to relaxed models yields powerful admissible heuristics
Information Sciences: an International Journal
Disjoint pattern database heuristics
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
A Performance Analysis of Transposition-Table-Driven Work Scheduling in Distributed Search
IEEE Transactions on Parallel and Distributed Systems
Divide-and-Conquer Frontier Search Applied to Optimal Sequence Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Searching with Pattern Databases
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Journal of the ACM (JACM)
Maximizing over multiple pattern databases speeds up heuristic search
Artificial Intelligence
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
The XtreemFS architecture—a case for object-based file systems in Grids
Concurrency and Computation: Practice & Experience - Selection of Best Papers of the VLDB Data Management in Grids Workshop (VLDB DMG 2007)
Structured duplicate detection in external-memory graph search
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Towards Efficient MapReduce Using MPI
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Large-scale parallel breadth-first search
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Very large pattern databases for heuristic search
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
A parallel implementation of iterative-deepening-A
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
STXXL: standard template library for XXL data sets
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Solving the 24 puzzle with instance dependent pattern databases
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Special Issue: MapReduce and its Applications
Concurrency and Computation: Practice & Experience
Forward perimeter search with controlled use of memory
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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MR-Search is a framework for massively parallel heuristic search. Based on the MapReduce paradigm, it efficiently utilizes all available resources: processors, memories, and disks. MR-Search uses OpenMP on shared memory systems, Message Passing Interface on clusters with distributed memory, and a combination of both on clusters with multi-core processors. Large graphs that do not fit into the main memory can be efficiently processed with an out-of-core variant. We implemented two node expansion strategies in MR-Search: breadth-first frontier search and breadth-first iterative deepening A*. With breadth-first frontier search, we computed large and powerful table-driven heuristics, so-called pattern databases that exceed the main memory capacity. These pattern databases were then used to solve random instances of the 24-puzzle with breadth-first iterative deepening A* on systems with up to 4093 processor cores. MR-Search is conceptually simple. It takes care of data partitioning, process scheduling, out-of-core data merging, communication, and synchronization. Application developers benefit from the parallel computational capacity without having the burden of implementing parallel application code. Copyright © 2011 John Wiley & Sons, Ltd.