Vivek Parmar
Indian Institute of Technology Delhi
40 Papers
133 Citations
Vivek Parmar is an academic researcher from Indian Institute of Technology Delhi. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 9, co-authored 25 publications. Previous affiliations of Vivek Parmar include Indian Institutes of Technology.
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Papers
SLIM: Simultaneous Logic-in-Memory Computing Exploiting Bilayer Analog OxRAM Devices
TL;DR: In this paper, the authors proposed a novel "simultaneous logic in-memory" (SLIM) methodology that allows to implement both memory and logic operations simultaneously on the same bitcell in a non-destructive manner without losing the previously stored Memory state.
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Neuromorphic hybrid RRAM-CMOS RBM architecture
Manan Suri,Vivek Parmar,Ashwani Kumar,Damien Querlioz,Fabien Alibart +4 more
- 01 Oct 2015
TL;DR: This paper presents a novel approach for realizing a hybrid RRAM-CMOS RBM architecture, HfOx based (filamentary-type switching) RRAM devices are extensively used to implement: (i) Synapses (ii) Internal neuron-state storage and (iii) Stochastic neuron activation function.
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OxRAM RNG Circuits Exploiting Multiple Undesirable Nanoscale Phenomena
TL;DR: It is shown how multiple undesirable nanoscale OxRAM phenomena, such as reset-current fluctuation, random telegraph noise (RTN), and reset-state resistance variability in HfO$_{\rm x}$ devices can be coupled to realize RNGs.
25
NV-BNN: An Accurate Deep Convolutional Neural Network Based on Binary STT-MRAM for Adaptive AI Edge
Chih-Cheng Chang,Ming-Hung Wu,Jia-Wei Lin,Chun-Hsien Li,Vivek Parmar,Heng-Yuan Lee,Jeng-Hua Wei,Shyh-Shyuan Sheu,Manan Suri,Tian-Sheuan Chang,Tuo-Hung Hou +10 more
- 02 Jun 2019
TL;DR: Based on the soon-available STT-MRAM, the first binary deep convolutional neural network (NV-BNN) capable of both local and remote learning is reported, which exploits intrinsic cumulative switching probability to ensure accurate online training of CIFAR-10 color images.
25
Dual-configuration in-memory computing bitcells using SiOx RRAM for binary neural networks
Sandeep Kaur Kingra,Vivek Parmar,Shubham Negi,Alessandro Bricalli,G. Piccolboni,Amir Regev,J. F. Nodin,G. Molas,Manan Suri +8 more
TL;DR: In this paper , a dual-configuration XNOR (exclusive NOR) IMC bitcell is realized using fabricated 1T-1R SiOx RRAM (resistive random access memory) arrays.
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