Mitigating the Effect of Reliability Soft-errors of RRAM Devices on the Performance of RRAM-based Neuromorphic Systems
| Autor: | Shimeng Yu, Mohab Anis, Amr M. S. Tosson, Lan Wei |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
010302 applied physics
Engineering business.industry 020208 electrical & electronic engineering Spice 02 engineering and technology Energy consumption 01 natural sciences Bottleneck Resistive random-access memory Non-volatile memory symbols.namesake Reliability (semiconductor) Neuromorphic engineering 0103 physical sciences 0202 electrical engineering electronic engineering information engineering symbols Electronic engineering business Von Neumann architecture |
| Zdroj: | ACM Great Lakes Symposium on VLSI |
| DOI: | 10.1145/3060403.3060431 |
| Popis: | With the speed and power bottleneck in the conventional Von Neumann architecture, the interest in the neuromorphic systems has greatly increased in recent years. To create a highly dense communication network between the pre- and post-neurons, RRAM devices are used as synapses in the neuromorphic systems due to many advantages including their small sizes and low-power operations. However, due to RRAM reliability issues, in particular soft-errors, the performance of the RRAM-based neuromorphic systems are significantly degraded. In this article, we propose a novel framework for detecting and resolving the degradation in the system performance due to the RRAM reliability soft-errors. The read and write circuits modifications to implement the framework, and their impact on the delay and energy consumption of the neuromorphic system are also discussed in this article. Using a combination of BRIAN and SPICE simulations, we demonstrate that the proposed framework can restore the accuracy of the example RRAM-based neuromorphic system from 43% back to its target value of 91.6% with a minimal impact on the read ( |
| Databáze: | OpenAIRE |
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