1 code implementation • 16 Feb 2023 • Marcel Khalifa, Barak Hoffer, Orian Leitersdorf, Robert Hanhan, Ben Perach, Leonid Yavits, Shahar Kvatinsky
Specifically, we propose a custom filtering technique that drastically narrows the search space and a search approach that facilitates approximate string matching through a distance function.
no code implementations • 30 May 2022 • Marcel Khalifa, Rotem Ben-Hur, Ronny Ronen, Orian Leitersdorf, Leonid Yavits, Shahar Kvatinsky
Pre-alignment filters substantially reduce computation complexity by filtering potential alignment locations.
no code implementations • 24 May 2022 • Mor M. Dahan, Evelyn T. Breyer, Stefan Slesazeck, Thomas Mikolajick, Shahar Kvatinsky
In this paper, we propose a memory architecture named crossed-AND (C-AND), in which each storage cell consists of a single ferroelectric transistor.
no code implementations • 15 Mar 2022 • Wei Wang, Barak Hoffer, Tzofnat Greenberg-Toledo, Yang Li, Minhui Zou, Eric Herbelin, Ronny Ronen, Xiaoxin Xu, Yulin Zhao, Jianguo Yang, Shahar Kvatinsky
Nevertheless, the implementation of the VMM needs complex peripheral circuits and the complexity further increases since non-idealities of memristive devices prevent precise conductance tuning (especially for the online training) and largely degrade the performance of the deep neural networks (DNNs).
no code implementations • 29 Dec 2019 • Tzofnat Greenberg Toledo, Ben Perach, Itay Hubara, Daniel Soudry, Shahar Kvatinsky
A recent example is the GXNOR framework for stochastic training of ternary (TNN) and binary (BNN) neural networks.
1 code implementation • 14 Jun 2016 • Xuan Yang, Jing Pu, Blaine Burton Rister, Nikhil Bhagdikar, Stephen Richardson, Shahar Kvatinsky, Jonathan Ragan-Kelley, Ardavan Pedram, Mark Horowitz
Convolutional Neural Networks (CNNs) are the state of the art solution for many computer vision problems, and many researchers have explored optimized implementations.