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A Theory for Co-Scheduling Hardware and Software Pipelines in ASIPs and Embedded Processors

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Abstract

Exploiting instruction-level parallelism (ILP) is extremely important for achieving high performance in application specific instruction set processors (ASIPs) and embedded processors. Unlike conventional general purpose processors, ASIPs and embedded processors typically run a single application and hence must be optimized extensively for this in order to extract maximum performance. Further, low power and low cost requirements of ASIPs may demand reuse of pipeline stages causing pipelines with complex structural hazards. In such architectures, exploiting higher ILP is a major challenge to the designer.

Existing techniques deal with either scheduling hardware pipelines to obtain higher throughput or software pipelining—an instruction scheduling technique for iterative computation—for exploiting greater ILP. We integrate these techniques to co-schedule hardware and software pipelines to achieve greater instruction throughput. In this paper, we develop the underlying theory of Co-Scheduling, called the Modulo-Scheduled Pipeline (or MS-Pipeline) theory. More specifically, we establish the necessary and sufficient condition for achieving the maximum throughput in a given pipeline operating under modulo scheduling. Further, we establish a sufficient condition to achieve a specified throughput, based on which we also develop a methodology for designing the hardware pipelines that achieve such a throughput. Further, we present initial experimental results which help to establish the usefulness of MS-pipeline theory in software pipelining. As the proposed theory helps to analyze and improve the throughput of Modulo-Scheduled Pipelines (MS-pipelines), it is especially useful in designing ASIPs and embedded processors.

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Authors and Affiliations

  1. Supercomputer Edn. and Res. Centre, Indian Institute of Science, Bangalore, 560 012, India

    R. Govindarajan

  2. IBM T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY, 10598, U.S.A.

    Erik R. Altman

  3. Electrical & Computer Engineering, University of Delaware, Newark, DE, 19716, U.S.A.

    Guang R. Gao

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  1. R. Govindarajan
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  2. Erik R. Altman
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  3. Guang R. Gao
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Govindarajan, R., Altman, E.R. & Gao, G.R. A Theory for Co-Scheduling Hardware and Software Pipelines in ASIPs and Embedded Processors. Design Automation for Embedded Systems 6, 243–275 (2002). https://doi.org/10.1023/A:1014050303852

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