COMBA: A comprehensive model-based analysis framework for high level synthesis of real applications.
ICCAD(2017)
摘要
High Level Synthesis (HLS) relies on the use of synthesis pragmas to generate digital designs meeting a set of specifications. However, the selection of a set of pragmas depends largely on designer experience and knowledge of the target architecture and digital design. Existing automated methods of pragma selection are very limited in scope and capability to analyze complex design descriptions in high-level languages to be synthesized using HLS. In this paper, we propose COMBA, a comprehensive model-based analysis framework capable of analyzing the effects of a multitude of pragmas related to functions, loops and arrays in the design description using pluggable analytical models, a recursive data collector (RDC) and a metric-guided design space exploration algorithm (MGDSE). When compared with HLS tools like Vivado HLS, COMBA reports an average error of around 1% in estimating performance, while taking only a few seconds for analysis of Polybench benchmark applications and a few minutes for real-life applications like JPEG, Seidel and Rician. The synthesis pragmas recommended by COMBA result in an average 100x speed-up in performance for the analyzed applications, which establishes COMBA as a superior alternative to current state-of-the-art approaches.
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关键词
high level synthesis,synthesis pragmas,digital design,complex design descriptions,high-level languages,design description,pluggable analytical models,metric-guided design space exploration algorithm,HLS tools,Vivado HLS,Polybench benchmark applications,real-life applications,COMBA,comprehensive model-based analysis framework,recursive data collector,RDC,JPEG,Seidel,Rician
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