基于SONOS的神经形态计算模拟存储器可靠性研究

K. Ramkumar, V. Prabhakar, V. Agrawal, L. Hinh, S. Saha, S. Samanta, R. Kapre
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引用次数: 1

摘要

对40nm SONOS (si - oxide -氮化物- oxide - si)非易失性存储器(NVM)电池的可靠性进行了评估,用于模拟存储器来执行神经形态计算。开发了流程和智能写入算法,以调整该应用程序的关键可靠性参数,如保留和噪声性能。并对其优化以满足产品可靠性要求进行了讨论。在小型测试阵列和实际存储阵列上对SONOS的性能进行了评估,并对所获得的保留数据进行了讨论
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Reliability Aspects of SONOS Based Analog Memory for Neuromorphic Computing
Reliability of 40nm SONOS (Si-Oxide-Nitride-Oxide-Si) based non-volatile memory (NVM) cell has been evaluated for analog memory to perform neuromorphic computing. Process flow and smart-write algorithms were developed to tune key reliability parameters like retention and noise performance for this application. Their optimization to meet the product reliability requirements are also discussed. The performance of SONOS was evaluated on mini test arrays as well as actual memory arrays and the retention data obtained are discussed
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