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 …

Large-scale, parallel clusters composed of commodity processors are increasingly
available, enabling the use of vast processing capabilities and distributed RAM to solve hard …

The commercial success of Cloud computing and recent developments in Grid computing
have brought platform virtualization technology into the field of high performance computing …

A* search is a best-first search algorithm that is widely used in pathfinding and graph
traversal. To meet the ever-increasing demand of performance, various high-performance …

Large-scale, parallel clusters composed of commodity processors are increasingly
available, enabling the use of vast processing capabilities and distributed RAM to solve hard …

Many search algorithms are limited by the amount of memory available. Magnetic disk
storage is over two orders of magnitude cheaper than semiconductor memory, and …

Planners need to become faster as we seek to tackle increasingly complicated problems.
Much of the recent improvements in computer speed is due to multi-core processors. For …

Optimal heuristic searches such as A* search are commonly used for low-dimensional
planning such as 2D path finding. These algorithms however, typically do not scale well to …

Dynamic programming (DP) is a framework used in multiple disciplines to solve decision-
making problems. In particular, in computer science and operations research (OR), DP …

A* suffers from limited parallelism. The maximum level of traditional parallelism in A* is the
same as the degree of the search graph nodes, which is too small in many applications. As …