Projects per year
Abstract
Analog in memory Computing (IMC) has emerged as a promising method to accelerate deep neural networks (DNNs) on hardware efficiently. Yet, analog computation typically focuses on the multiply and accumulate operation, while other operations are still being computed digitally. Hence, these mixed-signal IMC cores require extensive use of data converters, which can take a third of the total energy and area consumption. Alternatively, all-analog DNN computation is possible but requires increasingly challenging analog storage solutions, due to noise and leakage of advanced technologies. To enable all-analog DNN acceleration, this work demonstrates a feasible IMC architecture using an efficient analog main memory (AMM) cell. The proposed AMM cell is 42x and 5x more power and area efficient than a baseline analog storage cell. An all-analog architecture using this cell achieves potential efficiency gains of 15x compared with a mixed-signal IMC core using data converters.
Original language | English |
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Title of host publication | 2024 IEEE 6th International Conference on AI Circuits and Systems, AICAS 2024 - Proceedings |
Publisher | IEEE |
Pages | 248-252 |
Number of pages | 5 |
ISBN (Electronic) | 979-8-3503-8363-8 |
DOIs | |
Publication status | Published - 2024 |
MoE publication type | A4 Conference publication |
Event | IEEE International Conference on AI Circuits and Systems - Abu Dhabi, United Arab Emirates Duration: 22 Apr 2024 → 25 Apr 2024 Conference number: 6 |
Conference
Conference | IEEE International Conference on AI Circuits and Systems |
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Abbreviated title | AICAS |
Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 22/04/2024 → 25/04/2024 |
Keywords
- Analog in memory Computing
- Analog Memory
Fingerprint
Dive into the research topics of 'Evaluating an Analog Main Memory Architecture for All-Analog In-Memory Computing Accelerators'. Together they form a unique fingerprint.Projects
- 2 Finished
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WHISTLE: When integrated systems gain life experience: towards self-learning circuits with resource-efficient embedded artificial intelligence
Andraud, M. (Principal investigator), Adam, K. (Project Member), Yao, L. (Project Member), Periasamy, K. (Project Member), Leslin, J. (Project Member) & Bhowmick, S. (Project Member)
01/09/2020 → 31/08/2024
Project: Academy of Finland: Other research funding
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EHIR: Wireless impulse radio data link powered by energy harvesting
Halonen, K. (Principal investigator), Monga, D. (Project Member), Numan, O. (Project Member), Singh, G. (Project Member), Tanweer, M. (Project Member), Ylä-Oijala, P. (Project Member), Gallegos Rosas, K. (Project Member), Adam, K. (Project Member), Najmussadat, M. (Project Member) & Wang, Z. (Project Member)
01/09/2020 → 31/08/2023
Project: Academy of Finland: Other research funding
Equipment
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Aalto Electronics-ICT
Ryynänen, J. (Manager)
Department of Electronics and NanoengineeringFacility/equipment: Facility