An efficient retargetable framework for instruction-set simulation

  • Authors:

  • Mehrdad Reshadi;Nikhil Bansal;Prabhat Mishra;Nikil Dutt

  • Affiliations:

  • University of California, Irvine, CA;University of California, Irvine, CA;University of California, Irvine, CA;University of California, Irvine, CA

  • Venue:
  • Proceedings of the 1st IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
  • Year:
  • 2003

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Abstract

Instruction-set architecture (ISA) simulators are an integral part of today's processor and software design process. While increasing complexity of the architectures demands high performance simulation, the increasing variety of available architectures makes retargetability a critical feature of an instruction-set simulator. Retargetability requires generic models while high performance demands target specific customizations. To address these contradictory requirements, we have developed a generic instruction model and a generic decode algorithm that facilitates easy and efficient retargetability of the ISA-simulator for a wide range of processor architectures such as RISC, CISC, VLIW and variable length instruction set processors. The instruction model is used to generate compact and easy to debug instruction descriptions that are very similar to that of architecture manual. These descriptions are used to generate high performance simulators. The generation of the simulator is completely separate from the simulation engine. Hence, we can incorporate any fast simulation technique in our retargetable framework without loosing performance. We illustrate the retargetability of our approach using two popular, yet different realistic architectures: the Sparc and the ARM.