Cell-SWat: modeling and scheduling wavefront computations on the cell broadband engine

  • Authors:

  • Ashwin M. Aji;Wu-chun Feng;Filip Blagojevic;Dimitrios S. Nikolopoulos

  • Affiliations:

  • Virginia Tech, Blacksburg, VA, USA;Virginia Tech, Blacksburg, VA, USA;Virginia Tech, Blacksburg, VA, USA;Virginia Tech, Blacksburg, VA, USA

  • Venue:
  • Proceedings of the 5th conference on Computing frontiers
  • Year:
  • 2008

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Abstract

This paper presents and evaluates a model and a methodology for implementing parallel wavefront algorithms on the Cell Broadband Engine. Wavefront algorithms are vital in several application areas such as computational biology, particle physics, and systems of linear equations. The model uses blocked data decomposition with pipelined execution of blocks across the synergistic processing elements (SPEs) of the Cell. To evaluate the model, we implement the Smith-Waterman sequence alignment algorithm as a wavefront algorithm and present key optimization techniques that complement the vector processing capabilities of the SPE. Our results show perfect linear speedup for up to 16 SPEs on the QS20 dual-Cell blades, and our model shows that our implementation is highly scalable for more cores, if available. Furthermore, the accuracy of our model is within 3% of the measured values on average. Lastly, we also test our model in a throughput-oriented experimental setting, where we couple the model with scheduling techniques that exploit parallelism across the simultaneous execution of multiple sequence alignments. Using our model, we improved the throughput of realistic multisequence alignment workloads by up to 8% compared to FCFS (first-come, first-serve), by trading off parallelism within alignments with parallelism across alignments.