Optimizing memory hierarchy allocation with loop transformations for high-level synthesis

  • Authors:
  • Jason Cong;Peng Zhang;Yi Zou

  • Affiliations:
  • University of California, Los Angeles, CA;University of California, Los Angeles, CA;University of California, Los Angeles, CA

  • Venue:
  • Proceedings of the 49th Annual Design Automation Conference
  • Year:
  • 2012

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Abstract

For the majority of computation-intensive application systems, off-chip memory bandwidth is a critical bottleneck for both performance and power consumption. The efficient utilization of limited on-chip memory resources plays a vital role in reducing the off-chip memory accesses. This paper presents an efficient approach for optimizing the on-chip memory allocation by loop transformations in the imperfectly nested loops. We analytically model the on-chip buffer size and off-chip bandwidth after affine loop transformation, loop fusion/distribution and code motion. Branch-and-bound and knapsack reuse techniques are proposed to reduce the computation complexity in finding optimal solutions. Experimental results show that our scheme can save 40% of on-chip memory size with the same bandwidth consumption compared to the previous approaches.