BioCare: An Energy-Efficient CGRA for Bio-Signal Processing at the Edge

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

Coarse Grained Reconfigurable Architectures (CGRAs) have proved to be viable platforms for health monitoring applications. Targeting energy-efficiency, state-of-the-art (SoA) CGRAs are augmented with approximation techniques, while still maintain acceptable accuracy at final Quality of Result (QoR). However, such CGRAs suffer from overheads of collecting separate Add/Mul/Div units. We propose BioCare as an area- and energy-efficient CGRA for health-monitoring edge devices, which exploits the synergistic effects of multiple approximations across HW/SW stack. BioCare offers different levels of energy-accuracy trade-off through the plasticity of its small PEs, each can support precision-adaptability with a Single Instruction, Multiple Data (SIMD) manner. BioCare demonstrates its superiority over SoAs, by achieving up to 32% and 67% area- and energy-savings, with 3.6 χ higher throughput. In addition to analysis on multiple kernels, evaluations on a multi-kernel ECG application shows that BioCare speed-ups the QRS detection latency by 61%, with 0% loss in accuracy. Our implementations will be available at https://cfaed.tu-dresden.de/pd-downloads.

Details

Original languageEnglish
Title of host publication2021 IEEE International Symposium on Circuits and Systems, ISCAS 2021 - Proceedings
PublisherIEEE Xplore
Pages1-5
Number of pages5
ISBN (print)978-1-7281-9201-7
Publication statusPublished - 2021
Peer-reviewedYes

Publication series

SeriesIEEE International Symposium on Circuits and Systems (ISCAS)
ISSN0271-4302

External IDs

Scopus 85108986160

Keywords

Research priority areas of TU Dresden

Sustainable Development Goals

ASJC Scopus subject areas

Keywords

  • Approximate computing, Bio-signal, CGRA, ECG, Edge computing, EEG, Energy-Efficiency, SIMD