Daniel Kunkle
ABSTRACT
There are numerous examples of problems in symbolic algebra in which the required storage grows far beyond the limitations even of the distributed RAM of a cluster. Often this limitation determines how large a problem one can solve in practice. Roomy provides a minimally invasive system to modify the code for such a computation, in order to use the local disks of a cluster or a SAN as a transparent extension of RAM.
Roomy is implemented as a C/C++ library. It provides some simple data structures (arrays, unordered lists, and hash tables). Some typical programming constructs that one might employ in Roomy are: map, reduce, duplicate elimination, chain reduction, pair reduction, and breadth-first search. All aspects of parallelism and remote I/O are hidden within the Roomy library.
- Daniel Kunkle. Roomy: A C/C++ library for parallel disk-based computation, 2010. http://roomy.sourceforge.net/.Google Scholar
- Daniel Kunkle and Gene Cooperman. Harnessing parallel disks to solve Rubik's cube. Journal of Symbolic Computation, 44(7):872--890, 2009. Google ScholarDigital Library
- Daniel Kunkle, Vlad Slavici, and Gene Cooperman. Parallel disk-based computation for large, monolithic binary decision diagrams. In Parallel Symbolic Computation (PASCO '10). ACM Press, 2010. Google ScholarDigital Library
- Eric Robinson. Large Implicit State Space Enumeration: Overcoming Memory and Disk Limitations. PhD thesis, Northeastern University, Boston, MA, 2008. Google ScholarDigital Library
- Eric Robinson, Daniel Kunkle, and Gene Cooperman. A comparative analysis of parallel disk-based methods for enumerating implicit graphs. In Parallel Symbolic Computation (PASCO '07), pages 78--87. ACM Press, 2007. Google ScholarDigital Library
Index Terms
- Roomy: a system for space limited computations
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