Research output per year
Research output per year
Search results
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2023
Neuromorphic Data Converters Using Memristors
Danial, L., Damahe, P., Agrawal, P., Dhamnani, R. & Kvatinsky, S., 2023, Emerging Computing: From Devices to Systems: Looking Beyond Moore and Von Neumann. Aly, M. M. S. & Chattopadhyay, A. (eds.). Singapore, p. 245-290 46 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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2021
abstractPIM: A Technology Backward-Compatible Compilation Flow for Processing-In-Memory
Eliahu, A., Ben-Hur, R., Ronen, R. & Kvatinsky, S., 2021, VLSI-SoC: Design Trends - 28th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2020, Revised and Extended Selected Papers. Calimera, A., Gaillardon, P.-E., Korgaonkar, K., Kvatinsky, S. & Reis, R. (eds.). p. 343-361 19 p. (IFIP Advances in Information and Communication Technology; vol. 621).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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mMPU: Building a Memristor-based General-purpose In-memory Computation Architecture
Eliahu, A., Hur, R. B., Ali, A. H. & Kvatinsky, S., 26 Mar 2021, Multi-Processor System-on-Chip 1: Architectures. Andrade, L. & Rousseau, F. (eds.). p. 119-131 13 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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2020
Accelerating inference on binary neural networks with digital rram processing
Vieira, J., Giacomin, E., Qureshi, Y., Zapater, M., Tang, X., Kvatinsky, S., Atienza, D. & Gaillardon, P. E., 2020, VLSI-SoC: New Technology Enabler - 27th IFIP/IEEE WG 10.5 International Conference on Very Large Scale Integration, VLSI-SoC 2019, Revised and Extended Selected Papers. Metzler, C., Reis, R., Gaillardon, P.-E., De Micheli, G. & Silva-Cardenas, C. (eds.). p. 257-278 22 p. (IFIP Advances in Information and Communication Technology; vol. 586 IFIP).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
Open Access -
Memristor-based in-memory logic and its application in image processing
Haj-Ali, A., Ronen, R., Ben-Hur, R., Wald, N. & Kvatinsky, S., 1 Jan 2020, Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications - Computational Memory, Deep Learning, and Spiking Neural Networks. p. 175-194 20 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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mMPU—A Real Processing-in-Memory Architecture to Combat the von Neumann Bottleneck
Talati, N., Ben-Hur, R., Wald, N., Haj-Ali, A., Reuben, J. & Kvatinsky, S., 2020, Springer Series in Advanced Microelectronics. p. 191-213 23 p. (Springer Series in Advanced Microelectronics; vol. 63).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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2019
A taxonomy and evaluation framework for memristive logic
Reuben, J., Talati, N., Wald, N., Ben-Hur, R., Ali, A. H., Gaillardon, P. E. & Kvatinsky, S., 1 Jan 2019, Handbook of Memristor Networks. p. 1065-1099 35 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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2017
Logic with unipolar memristors – circuits and design methodology
Wald, N., Amrani, E., Drori, A. & Kvatinsky, S., 2017, VLSI-SoC: System-on-Chip in the Nanoscale Era – Design, Verification and Reliability - 24th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2016. Reis, R., Hollstein, T., Raik, J., Kostin, S., Tsertov, A. & O’Connor, I. (eds.). p. 24-40 17 p. (IFIP Advances in Information and Communication Technology; vol. 508).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
Open Access