To compensate for the lower bandwidth of disks, Roomy uses many disks in parallel. This can be multiple disks attached to a single shared-memory system, a cluster, or a storage area network (SAN). To compensate for the significantly higher latency of disks, Roomy delays random access operations and performs them efficiently in batch.
Roomy is implemented as a C/C++ library. It provides a small number of simple data structures (arrays, unordered lists, and hash tables) and associated operations. Roomy data structures are transparently distributed across many disks, and the operations on these data structures are transparently parallelized across the many compute nodes of a cluster. All aspects of parallelism and remote I/O are hidden within the Roomy library.
The most recent revision (possibly unstable) can be retrieved from the source
code repository using:
svn co https://roomy.svn.sourceforge.net/svnroot/roomy/trunk roomy
Example Roomy Application Pancake Sorting: The example demonstrates the Roomy library using several solutions to the pancake sorting problem. In particular, it calculates the integer sequences given in the Wikipedia article on pancake sorting. The solutions are calculated with three different implementations of breadth-first search, using the RoomyList, RoomyArray, or RoomyHashTable.
Roomy API : The programming interface for the Roomy library.
Parallel Disk-Based Computation for Large, Monolithic Binary Decision Diagrams
D. Kunkle, V. Slavici and G. Cooperman.
International Workshop on Parallel Symbolic Computation (PASCO '10)
Grenoble, France, 2010.