Abstract
ALPS is a framework for implementing and parallelizing tree search algorithms. It employs a number of features to improve scalability and is designed specifically to support the implementation of data intensive algorithms, in which large amounts of knowledge are generated and must be maintained and shared during the search. Implementing such algorithms in a scalable manner is challenging both because of storage requirements and because of communications overhead incurred in the sharing of data. In this abstract, we describe the design of ALPS and how the design addresses these challenges. We present two sample applications built with ALPS and preliminary computational results.
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Xu, Y., Ralphs, T.K., Ladányi, L., Saltzman, M.J. (2005). Alps: A Framework for Implementing Parallel Tree Search Algorithms. In: Golden, B., Raghavan, S., Wasil, E. (eds) The Next Wave in Computing, Optimization, and Decision Technologies. Operations Research/Computer Science Interfaces Series, vol 29. Springer, Boston, MA . https://doi.org/10.1007/0-387-23529-9_21
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DOI: https://doi.org/10.1007/0-387-23529-9_21
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