The input/output complexity of sorting and related problems
Communications of the ACM
External-memory graph algorithms
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Communications of the ACM
External memory algorithms and data structures: dealing with massive data
ACM Computing Surveys (CSUR)
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
I/O-efficient topological sorting of planar DAGs
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
External memory data structures
Handbook of massive data sets
Improved Algorithms and Data Structures for Solving Graph Problems in External Memory
SPDP '96 Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing (SPDP '96)
I/O-Efficient Algorithms for Problems on Grid-Based Terrains
Journal of Experimental Algorithmics (JEA)
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Acceleration of shortest path and constrained shortest path computation
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Partitioning graphs to speed up dijkstra's algorithm
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Algorithms and data structures for external memory
Foundations and Trends® in Theoretical Computer Science
Short note: Least cost distance analysis for spatial interpolation
Computers & Geosciences
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This paper addresses the problem of computing least-cost-path surfaces for massive grid-based terrains. Our approach follows a modular design, enabling the algorithm to make efficient use of memory, disk, and grid computing environments. We have implemented the algorithm in the context of the GRASS open source GIS system and---using our cluster management tool---in a distributed environment. We report experimental results demonstrating that the algorithm is not only of theoretical and conceptual interest but also performs well in practice. Our implementation outperforms standard solutions as dataset size increases relative to available memory and our distributed solver obtains near-linear speedup when preprocessing large terrains for multiple queries.