TY - JOUR
T1 - An Energy-Efficient One-Shot Time-Based Neural Network Accelerator Employing Dynamic Threshold Error Correction in 65 nm
AU - Everson, Luke R.
AU - Liu, Muqing
AU - Pande, Nakul
AU - Kim, Chris H.
N1 - Publisher Copyright:
© 1966-2012 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - As neural networks continue to infiltrate diverse application domains, computing will begin to move out of the cloud and onto edge devices necessitating fast, reliable, and low-power (LP) solutions. To meet these requirements, we propose a time-domain core using one-shot delay measurements and a lightweight post-processing technique, dynamic threshold error correction (DTEC). This design differs from traditional digital implementations in that it uses the delay accumulated through a simple inverter chain distributed through an SRAM array to intrinsically compute resource intensive multiply-accumulate (MAC) operations. Implemented in 65-nm LP CMOS, we achieve an energy efficiency of 104.8 TOp/s/W at 0.7-V with 3b resolution for 19.1 fJ/MAC.
AB - As neural networks continue to infiltrate diverse application domains, computing will begin to move out of the cloud and onto edge devices necessitating fast, reliable, and low-power (LP) solutions. To meet these requirements, we propose a time-domain core using one-shot delay measurements and a lightweight post-processing technique, dynamic threshold error correction (DTEC). This design differs from traditional digital implementations in that it uses the delay accumulated through a simple inverter chain distributed through an SRAM array to intrinsically compute resource intensive multiply-accumulate (MAC) operations. Implemented in 65-nm LP CMOS, we achieve an energy efficiency of 104.8 TOp/s/W at 0.7-V with 3b resolution for 19.1 fJ/MAC.
KW - Machine learning (ML)
KW - neuromorphic computing
KW - time-domain computing
KW - time-to-digital converter (TDC)
UR - http://www.scopus.com/inward/record.url?scp=85072777898&partnerID=8YFLogxK
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U2 - 10.1109/JSSC.2019.2914361
DO - 10.1109/JSSC.2019.2914361
M3 - Article
AN - SCOPUS:85072777898
SN - 0018-9200
VL - 54
SP - 2777
EP - 2785
JO - IEEE Journal of Solid-State Circuits
JF - IEEE Journal of Solid-State Circuits
IS - 10
M1 - 8718342
ER -