Issue No. 03 - March (1991 vol. 40)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/12.76413
<p>A precise characterization of the subcube allocation problem and a general methodology to solve it are presented. Subcube allocation and coalescing algorithms that have the goal of minimizing fragmentation are developed. The concept of a maximal set of subcubes (MSS), which is useful in making allocations that result in a tightly packed hypercube, is introduced. The problems of allocating subcubes and of forming an MSS are formulated as decision problems and shown to be NP-hard. It is proved analytically that the buddy strategy is optimal under restricted conditions, and it is shown using simulation that its performance is actually poor under more realistic conditions. A heuristic procedure for efficiently coalescing a released cube with the existing free cubes is suggested. This coalescing approach is coupled with a simple best-fit allocation scheme to form the basis of a class of MSS-based strategies that give a substantial performance (hit ratio) improvement over the buddy strategy. Simulation results comparing several different allocation and coalescing strategies, which show that the MSS-based schemes provide a marked performance improvement over previous techniques, are presented.</p>
subcube allocation algorithms; subcube coalescing algorithms; fragmentation minimisation; hypercube computers; maximal set of subcubes; tightly packed hypercube; decision problems; NP-hard; buddy strategy; heuristic procedure; best-fit allocation; computational complexity; hypercube networks; minimisation; parallel algorithms.
J. Hayes and S. Dutt, "Subcube Allocation in Hypercube Computers," in IEEE Transactions on Computers, vol. 40, no. , pp. 341-352, 1991.