Very Large Scale Integration (VLSI) based
neuromorphic circuits also known as Silicon Neurons (SiNs) emulate the
electrophysiological behavior of biological neurons. With the advancement in
technology, neuromorphic systems also lead to various reliability issues and
hence making their study important. Bias Temperature Instability (BTI) and Hot
Carrier Injection (HCI) are the two major reliability issues present in VLSI
circuits. In this work, we have investigated the combined effect of BTI and HCI
on the two types of integrate-and-fire based SiNs namely (a) Axon-Hillock and
(b) Simplified Leaky integrate-and-fire circuits using their key performance
parameters. Novel reliability-aware AH and SLIF circuits are proposed to
mitigate the reliability issues. Proposed reliability-aware designs show
negligible deviation in performance parameters after aging. The time-zero
process variability analysis is also carried out for proposed reliability-aware
SiNs. The power consumption of existing and proposed reliability-aware neuron circuits
is analyzed and compared.<br>
Reliability aspects such as bias temperature instability (BTI) and hot carrier injection (HCI) affecting devices in advanced CMOS-based technology have been the subject of active research in recent decades. Due to these reliability issues, various digital and analog circuits were investigated for degradation.However, circuit blocks like the neuron circuits of neuromorphic systems are not fully explored. This work is inclined toward examining the collective degradation impact of BTI and HCI due to aging in an adaptive exponential "integrate and fire" (I&F) model-based, neuromorphic neuron circuit. Detailed degradation analysis of the stimulated neuron circuit aided in identifying possible mismatches/faults associated with neuron spikes. These factors could reduce the efficiency of the neuronal circuit by potentially affecting the transmission of information in a neuromorphic system. Various performance parameters were then derived to quantify the extent of circuit deterioration. The proposed reliability-aware design aims to improve the circuit degradation through its effectiveness in alleviating the overall reliability impact. It demonstrates enhanced circuit operation in spike generation even after aging. The circuit performance is validated through simulations at "Time0" (pre-degradation) and "Aged" (post-degradation) neuron netlists, which is then compared with the proposed reliability-aware circuit.
Very Large Scale Integration (VLSI) based
neuromorphic circuits also known as Silicon Neurons (SiNs) emulate the
electrophysiological behavior of biological neurons. With the advancement in
technology, neuromorphic systems also lead to various reliability issues and
hence making their study important. Bias Temperature Instability (BTI) and Hot
Carrier Injection (HCI) are the two major reliability issues present in VLSI
circuits. In this work, we have investigated the combined effect of BTI and HCI
on the two types of integrate-and-fire based SiNs namely (a) Axon-Hillock and
(b) Simplified Leaky integrate-and-fire circuits using their key performance
parameters. Novel reliability-aware AH and SLIF circuits are proposed to
mitigate the reliability issues. Proposed reliability-aware designs show
negligible deviation in performance parameters after aging. The time-zero
process variability analysis is also carried out for proposed reliability-aware
SiNs. The power consumption of existing and proposed reliability-aware neuron circuits
is analyzed and compared.<br>
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