University of Oulu

M. Safarpour, R. Inanlou and O. Silvén, "Algorithm Level Error Detection in Low Voltage Systolic Array," in IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 2, pp. 569-573, Feb. 2022, doi: 10.1109/TCSII.2021.3094923

Algorithm level error detection in low voltage systolic array

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Author: Safarpour, Mehdi1; Inanlou, Reza2; Silvén, Olli1
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
2School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.8 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2021-08-03


In this brief an approach is proposed to achieve energy savings from reduced voltage operation. The solution detects timing-errors by integrating Algorithm Based Fault Tolerance (ABFT) into a digital architecture. The approach has been studied with a systolic array matrix multiplier operating at reduced voltages, detecting errors on-the-fly to avoid energy demanding memory round-trips. The analysis of the solution has been done using analog-digital co-simulation to extract the transient behavior under different voltages and clock frequencies. HSPICE simulations using 90nm CMOS transistor models, and experiments by reducing operation voltage of an FPGA device were carried out. HSPICE simulations, showed possibility of 10x increase in energy-efficiency by approaching near-threshold region.

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Series: IEEE transactions on circuits and systems. II, Express briefs
ISSN: 1549-7747
ISSN-E: 1558-3791
ISSN-L: 1549-7747
Volume: 69
Issue: 2
Pages: 569 - 573
DOI: 10.1109/TCSII.2021.3094923
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: This work was supported by 6G Flagship research programme under Academy of Finland Grant 318927.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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