Suboptimal and Anytime Heuristic Search on Multi-core Machines

41 Pages·2009·0.55 MB·English

Suboptimal and Anytime Heuristic Search
on Multi-core Machines
1 1 1 2
Ethan Burns , Seth Lemons , Wheeler Ruml and Rong Zhou
1
2
[Many thanks to NSF grant IIS-0812141]
Ethan Burns (UNH) Heuristic Search for Multi-core – 1 / 38
Overview
n
Background
Introduction
n Overview u Parallel Retracting A* (PRA*, Evett et al., 1995)
n Parallel Search u
Parallel Best NBlock First Search (PBNF, Burns et al., IJCAI 2009)
PRA*
n
New: Parallel bounded-suboptimal search.
PBNF
u
Optimal Search Two pruning rules for approximate best-first suboptimal search
Suboptimal Search n
New: Parallel anytime search.
Anytime Search
Conclusion
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Naive Parallel Search
Introduction
n Overview
n Parallel Search
PRA*
PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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Naive Parallel Search
Introduction
n Overview
n Parallel Search
PRA*
PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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Naive Parallel Search
Introduction
n Overview
n Parallel Search
PRA*
PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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Parallel Retracting A* (PRA*, Evett et al., 1995)
n Distribute nodes among threads using a hash function.
Introduction
u
PRA* Each node has a home thread.
n Hashing Nodes
u
Duplicate detection can be performed locally at each
n Communication
thread.
PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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Parallel Retracting A* (PRA*, Evett et al., 1995)
n May need to communicate nodes between threads at each
Introduction
generation.
PRA*
n Hashing Nodes n Non-blocking: HDA* (Kishimoto et al., best paper award
n Communication
ICAPS 2009)
PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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N
Parallel Best block First (PBNF, Burns et al., 2009)
n Work is divided among threads using a special hash function
Introduction
based on abstraction. (Zhou and Hansen, 2007)
PRA*
PBNF u Few possible destinations for children.
n Abstraction
n Nblocks
n Detection Scope
n Disjoint Scopes
n PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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N
Parallel Best block First (PBNF, Burns et al., IJCAI 2009)
n Work is divided among threads using a special hash function
Introduction
based on abstraction.
PRA*
PBNF u Threads search groups of nodes called nblocks.
n Abstraction
n Nblocks
n Detection Scope
n Disjoint Scopes
n PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
Ethan Burns (UNH) Heuristic Search for Multi-core – 7 / 38
N
Parallel Best block First (PBNF, Burns et al., IJCAI 2009)
n Work is divided among threads using a special hash function
Introduction
based on abstraction.
PRA*
PBNF u nblocks have an open and closed list.
n Abstraction
n Nblocks
n Detection Scope
n Disjoint Scopes
n PBNF
Optimal Search
Suboptimal Search
Anytime Search
Conclusion
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