Optimizing the Use of Static Buffers for DMA on a CELL Chip

  • Tong Chen
  • Zehra Sura
  • Kathryn O’Brien
  • John K. O’Brien
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4382)


The CELL architecture has one Power Processor Element (PPE) core, and eight Synergistic Processor Element (SPE) cores that have a distinct instruction set architecture of their own. The PPE core accesses memory via a traditional caching mechanism, but each SPE core can only access memory via a small 256K software-controlled local store. The PPE cache and SPE local stores are connected to each other and main memory via a high bandwidth bus. Software is responsible for all data transfers to and from the SPE local stores. To hide the high latency of DMA transfers, data may be prefetched into SPE local stores using loop blocking transformations and static buffers. We find that the performance of an application can vary depending on the size of the buffers used, and whether a single-, double-, or triple-buffer scheme is used. Constrained by the limited space available for data buffers in the SPE local store, we want to choose the optimal buffering scheme for a given space budget. Also, we want to be able to determine the optimal buffer size for a given scheme, such that using a larger buffer size results in negligible performance improvement. We develop a model to automatically infer these parameters for static buffering, taking into account the DMA latency and transfer rates, and the amount of computation in the application loop being targeted. We test the accuracy of our prediction model using a research prototype compiler developed on top of the IBM XL compiler infrastructure.


Main Memory Execution Sequence Block Factor Cell Architecture Entire Loop 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Tong Chen
    • 1
  • Zehra Sura
    • 1
  • Kathryn O’Brien
    • 1
  • John K. O’Brien
    • 1
  1. 1.IBM T.J. Watson Research Center, Yorktown Heights, NY 10598 

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