I/O-Optimal Distribution Sweeping on Private-Cache Chip Multiprocessors
|Title:||I/O-Optimal Distribution Sweeping on Private-Cache Chip Multiprocessors||Authors:||Ajwani, Deepak
|Permanent link:||http://hdl.handle.net/10197/9898||Date:||8-Sep-2011||Online since:||2019-04-10T12:10:34Z||Abstract:||The parallel external memory (PEM) model has been used as a basis for the design and analysis of a wide range of algorithms for private-cache multi-core architectures. As a tool for developing geometric algorithms in this model, a parallel version of the I/O-efficient distribution sweeping framework was introduced recently, and a number of algorithms for problems on axis-aligned objects were obtained using this framework. The obtained algorithms were efficient but not optimal. In this paper, we improve the framework to obtain algorithms with the optimal I/O complexity of O(sort P(N) + K/PB) for a number of problems on axis-aligned objects, P denotes the number of cores/processors, B denotes the number of elements that fit in a cache line, N and K denote the sizes of the input and output, respectively, and sort P(N) denotes the I/O complexity of sorting N items using P processors in the PEM model. To obtain the above improvement, we present a new one-dimensional batched range counting algorithm on a sorted list of ranges and points that achieves an I/O complexity of O((N + K)/PB), where K is the sum of the counts of all the ranges. The key to achieving efficient load balancing among the processors in this algorithm is a new method to count the output without enumerating it, which might be of independent interest.||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2011 IEEE||Keywords:||Parallel external memory; PEM; Multicore algorithms; Computational geometry; Parallel distribution sweeping; Computational modeling||DOI:||10.1109/IPDPS.2011.106||Language:||en||Status of Item:||Not peer reviewed||Is part of:||2011 IEEE International Parallel & Distributed Processing Symposium (IPDPS): 16-20 May 2011, Anchorage, Alaska, USA||Conference Details:||The 2011 IEEE International Parallel & Distributed Processing Symposium (IPDPS), Anchorage, Alaska, 16-20 May 2011||ISBN:||9780769543857|
|Appears in Collections:||Computer Science Research Collection|
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