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DTSTART;TZID=America/Los_Angeles:20250623T170000
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UID:dac_DAC 2025_sess122_RESEARCH1903@linklings.com
SUMMARY:PreDAC: An Efficient Framework of Pre-Refining Enhanced Design Spa
 ce Exploration for Approximate Computing
DESCRIPTION:Ziying Cui, Ke Chen, Bi Wu, Yu Gong, Chenggang Yan, and Weiqia
 ng Liu (Nanjing University of Aeronautics and Astronautics)\n\nApproximate
  computing has emerged as a promising solution in energy-efficiency applic
 ations. Recently, attention has shifted from approximate components to Des
 ign Space Exploration (DSE) algorithms. However, traditional DSE algorithm
 s face challenges in efficiently obtaining optimal solutions within large 
 and complex design spaces. This paper introduces a pre-refining enhanced d
 esign space exploration framework that provides customized design space an
 d cost-performance formula for applications. Experimental results demonstr
 ate that integrating this pre-refining step into various DSE algorithms le
 ads to substantial performance gains, including up to 87× speedup and a 23
 % improvement in hardware overhead. Moreover, the innovative cost-performa
 nce-based DSE algorithm attains a 7.7× acceleration and further optimizes 
 hardware metrics by an additional 8.8% compared to advanced frameworks emp
 loying the same pre-refinement.\n\nTopics: Design\n\nTracks: DES3: Emergin
 g Models of ComputatioN\n\nSession Chairs: Cheng Wang (Iowa State Universi
 ty) and Jun Shiomi (The University of Osaka)\n\n
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