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ISCA2023顶会

On Endurance of Processing in (Nonvolatile) Memory

Salonik Resch, M. Hüsrev Cilasun, Zamshed I. Chowdhury, Masoud Zabihi, Zhengyang Zhao, Jian-Ping Wang, Sachin S. Sapatnekar, Ulya R. Karpuzcu

2023年份
15被引次数

摘要

Processing-in-Memory (PIM) architectures have gained popularity due to their ability to alleviate the memory wall by performing large numbers of operations within the memory itself. On top of this, nonvolatile memory (NVM) technologies offer highly energy-efficient operations, rendering processing in NVM especially promising. Unfortunately, a major drawback is that NVM has limited endurance. Even when used for standard memory, nonvolatile technologies face limited lifetimes, which is exacerbated by imbalanced usage of memory cells. PIM significantly increases the number of operations the memory is required to perform, making the problem much worse. In this work, we quantitatively analyze the impact of PIM applications on endurance considering representative memory technologies. Our findings indicate that limited endurance can easily block the performance and energy efficiency potential of PIM architectures. Even the best known technologies of today can fall short of meeting practical lifetime expectations. This highlights the importance of research efforts to improve endurance especially at the device technology level. Our study represents the first step in characterizing the very demanding endurance needs of PIM applications to derive a detailed technology level design specification.

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