CellSort: high performance sorting on the cell processor

  • Authors:
  • Buǧra Gedik;Rajesh R. Bordawekar;Philip S. Yu

  • Affiliations:
  • Thomas J. Watson Research Center, IBM Research, Hawthorne, NY;Thomas J. Watson Research Center, IBM Research, Hawthorne, NY;Thomas J. Watson Research Center, IBM Research, Hawthorne, NY

  • Venue:
  • VLDB '07 Proceedings of the 33rd international conference on Very large data bases
  • Year:
  • 2007

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Abstract

In this paper we describe the design and implementation of CellSort - a high performance distributed sort algorithm for the Cell processor. We design CellSort as a distributed bitonic merge with a data-parallel bitonic sorting kernel. In order to best exploit the architecture of the Cell processor and make use of all available forms of parallelism to achieve good scalability, we structure CellSort as a three-tiered sort. The first tier is a SIMD (single-instruction multiple data) optimized bitonic sort, which sorts up to 128KB of items that cat fit into one SPE's (a co-processor on Cell) local store. We design a comprehensive SIMDization scheme that employs data parallelism even for the most fine-grained steps of the bitonic sorting kernel. Our results show that, SIMDized bitonic sorting kernel is vastly superior to other alternatives on the SPE and performs up to 1.7 times faster compared to quick sort on 3.2GHz Intel Xeon. The second tier is an in-core bitonic merge optimized for cross-SPE data transfers via asynchronous DMAs, and sorts enough number of items that can fit into the cumulative space available on the local stores of the participating SPEs. We design data transfer and synchronization patters that minimize serial sections of the code by taking advantage of the high aggregate cross-SPE bandwidth available on Cell. Results show that, in-core bitonic sort scales well on the Cell processor with increasing number of SPEs, and performs up to 10 times faster with 16 SPEs compared to parallel quick sort on dual-3.2 GHz Intel Xeon. The third tier is an out-of-core bitonic merge which sorts large number of items stored in the main memory. Results show that, when properly implemented, distributed out-of-core bitonic sort on Cell can significantly outperform the asymptotically (average case) superior quick sort for large number of memory resident items (up to 4 times faster when sorting 0.5GB of data with 16 SPEs, compared to dual-3.2GHz Intel Xeon).