ALPINE: Analog In-Memory Acceleration with Tight Processor Integration for Deep Learning

Author:

Klein Joshua1ORCID,Boybat Irem2ORCID,Qureshi Yasir1ORCID,Dazzi Martino2ORCID,Levisse Alexandre1ORCID,Ansaloni Giovanni1ORCID,Zapater Marina3ORCID,Sebastian Abu2ORCID,Atienza David1ORCID

Affiliation:

1. Embedded Systems Laboratory (ESL), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

2. IBM Research Europe, Ruschlikon, Switzerland

3. HEIG-VD, Yverdon-les-Bains, Switzerland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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2. Overflow-free Compute Memories for Edge AI Acceleration;ACM Transactions on Embedded Computing Systems;2023-09-09

3. Time-domain Subtractive Readout Scheme for Scalable Capacitive Analog In-Memory Computing;2023 IEEE 36th International System-on-Chip Conference (SOCC);2023-09-05

4. Brain-inspired methods for achieving robust computation in heterogeneous mixed-signal neuromorphic processing systems;Neuromorphic Computing and Engineering;2023-07-25

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