Abstract
Computing in memory (CIM) technique is being researched for process multiply-And-Accumulate operation which is used in deep neural networks efficiently. Conventional CIM architecture only supports binary neural network which has lower accuracy. Some approaches use capacitor for multi bit operation. However, because capacitor has large size, the area efficiency of CIM macro is degraded. This paper proposes CIM macro structure that supports multi bit operation using parasitic capacitance of transistor. The proposed structure does not need additional capacitor and thus, it can achieve area efficient multi bit operation.
Original language | English |
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Title of host publication | Proceedings - International SoC Design Conference 2021, ISOCC 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 361-362 |
Number of pages | 2 |
ISBN (Electronic) | 9781665401746 |
DOIs | |
Publication status | Published - 2021 |
Event | 18th International System-on-Chip Design Conference, ISOCC 2021 - Jeju Island, Korea, Republic of Duration: 2021 Oct 6 → 2021 Oct 9 |
Publication series
Name | Proceedings - International SoC Design Conference 2021, ISOCC 2021 |
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Conference
Conference | 18th International System-on-Chip Design Conference, ISOCC 2021 |
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Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 21/10/6 → 21/10/9 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
- Hardware and Architecture
- Electrical and Electronic Engineering