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Instruction Generation and Regularity Extraction



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Instruction Generation and Regularity Extraction For Reconfigurable Processors Philip Brisk Adam Kaplan Ryan Kastner Majid Sarrafzadeh Computer Science Department University of California Los Angeles Los Angeles CA 90095 philip kaplan kastner majid cs ucla edu ABSTRACT The increasing demand for complex and specialized embedded hardware must be met by processors which are optimized for performance yet are also extremely flexible In our work we explore the tradeoff between flexibility and performance in the domain of reconfigurable processor design Specifically we seek to identify regularly occurring computation heavy patterns in an application or set of applications These patterns become candidates for hard logic implementation potentially embedded in the flexible reconfigurable fabric as special optimized instructions In this work we present an extension to previous work in instruction generation an algorithm that identifies parallel templates We discuss the advantages of parallel templates and prove the correctness of our algorithm We introduce an All Pairs Common Slack Graph APCSG as an effective tool for parallel template generation Finally we demonstrate the effectiveness of our algorithm on several applications dataflow graphs reducing latency on average by 51 98 without unreasonably increasing chip area Category 1 Compilers and Operating Systems General Terms Algorithms Performance Theory Keywords Hardware Compiler Template Slack Control Data flow Graph 1 INTRODUCTION The complexity of modern computing systems combined with the creation of faster smaller circuitry has fueled the genesis of extremely small and powerful embedded systems With the increasing design trend toward smaller and more intimate Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on



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