Scalable and retargetable simulation techniquesfor multiprocessor systems

  • Authors:
  • Heekyung Kim;Dukyoung Yun;Soonhoi Ha

  • Affiliations:
  • Seoul National University, Seoul, South Korea;Seoul National University, Seoul, South Korea;Seoul National University, Seoul, South Korea

  • Venue:
  • CODES+ISSS '09 Proceedings of the 7th IEEE/ACM international conference on Hardware/software codesign and system synthesis
  • Year:
  • 2009

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Abstract

For design space exploration of embedded systems, a virtual prototyping system is commonly used to verify the expected performance as well as functionality before a hardware prototype is built. For accurate performance estimation, a virtual prototyping system is constructed by replacing real processing components with component simulators running concurrently. In such a distributed simulation system, the overhead of communication and synchronization between the component simulators increases in proportion to the number of simulators in case the lock-step synchronization is used. As a result the simulation performance is degraded significantly as the number of processors integrated in a chip increases. To overcome this problem, we propose a scalable and retargetable simulation technique that boosts the simulation performance significantly, by attaching a simulator wrapper to each component simulator. The simulator wrapper performs synchronization on behalf of the associated simulator itself between the simulators and the simulation backplane. Use of the simulator wrapper also makes the proposed simulation platform retargetable since a third-party simulator like ARMulator can be integrated into the simulation environment through a wrapper without modification. In addition, it enables parallel simulation that achieves almost linear speed-up as the number of processor cores increases in the simulation host. Through experiments with multimedia CODEC application and other applications varying the number of processor simulators from 1 to 16, it is proved that the simulation performance remains constant. And scalable performance from parallel simulation is also confirmed by experiments.