Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems

Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasicek, Lukas Sekanina, Muhammad Shafique

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Generation and exploration of approximate circuits and accelerators has been a prominent research domain to achieve energy-efficiency and/or performance improvements. This research has predominantly focused on ASICs, while not achieving similar gains when deployed for FPGA-based accelerator systems, due to the inherent architectural differences between the two. In this work, we propose a novel framework, Xel-FPGAs, which leverages statistical or machine learning models to effectively explore the architecture-space of state-of-the-art ASIC-based approximate circuits to cater them for FPGA-based systems given a simple RTL description of the target application. We have also evaluated the scalability of our framework on a multi-stage application using a hierarchical search strategy. The Xel-FPGAs framework is capable of reducing the exploration time by up to 95%, when compared to the default synthesis, place, and route approaches, while identifying an improved set of Pareto-optimal designs for a given application, when compared to the state-of-the-art. The complete framework is open-source and available online at https://github.com/ehw-fit/xel-fpgas.

Original languageEnglish (US)
Title of host publication2023 42nd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350315592
DOIs
StatePublished - 2023
Event42nd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2023 - San Francisco, United States
Duration: Oct 28 2023Nov 2 2023

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)1092-3152

Conference

Conference42nd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2023
Country/TerritoryUnited States
CitySan Francisco
Period10/28/2311/2/23

Keywords

  • Accelerator
  • Approximate Computing
  • Arithmetic Units
  • ASIC
  • FPGA
  • Models
  • Regression
  • Synthesis

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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