A task-level hierarchical memory model for system synthesis of multiprocessors

  • Authors:
  • Yanbing Li;Wayne Wolf

  • Affiliations:
  • Dept. of EE, Princeton University, Princeton, NJ;Dept. of EE, Princeton University, Princeton, NJ

  • Venue:
  • DAC '97 Proceedings of the 34th annual Design Automation Conference
  • Year:
  • 1997

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Abstract

This paper introduces the first high-level (task-level)model of hierarchical memories and describes a scheduling andallocation algorithm for system-level synthesis of heterogeneousmultiprocessors. Caches are essential for modern RISC embeddedcores to obtain sustained high performance. However, caches havereceived limited use in priority-driven preemptive real-time systemsdue to the unpredictability of caches-average-case improvementsare of no use in systems with hard deadlines. Program-levelcache models do not take into account preemptions between multipletasks running at multiple rates on embedded cores. Our task-levelmodel of performance in the presence of memory hierarchiesprovides an efficient means to bound the guaranteed memory performanceof tasks running in a multi-rate, multi-tasking environment.Our system synthesis algorithm uses software-based cachepartitioning and reservation techniques to guarantee cache hitsfor some tasks and therefore improve task schedulability. Experimentalresults show that our model significantly improves schedulabilityof real-time tasks and can be evaluated efficiently duringsystem-level synthesis.