Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Saxena, Utkarsh"'
Large language models (LLMs) represent a groundbreaking advancement in the domain of natural language processing due to their impressive reasoning abilities. Recently, there has been considerable interest in increasing the context lengths for these m
Externí odkaz:
http://arxiv.org/abs/2408.05646
Large Language Models (LLMs) have distinguished themselves with outstanding performance in complex language modeling tasks, yet they come with significant computational and storage challenges. This paper explores the potential of quantization to miti
Externí odkaz:
http://arxiv.org/abs/2405.07135
Analog Compute-in-Memory (CiM) accelerators are increasingly recognized for their efficiency in accelerating Deep Neural Networks (DNN). However, their dependence on Analog-to-Digital Converters (ADCs) for accumulating partial sums from crossbars lea
Externí odkaz:
http://arxiv.org/abs/2403.13577
Publikováno v:
IEEE Transactions on Emerging Topics in Computing (2023)
Spiking Neural Networks (SNNs) are bio-plausible models that hold great potential for realizing energy-efficient implementations of sequential tasks on resource-constrained edge devices. However, commercial edge platforms based on standard GPUs are n
Externí odkaz:
http://arxiv.org/abs/2211.02167
Autor:
Iyer, Kiran, Liu, Peiyuan, Berchielli, Alfred, Doshi, Pankaj, Saxena, Utkarsh, Khan, Murtja, Suryawanshi, Tukaram, Kasat, Gopal
Publikováno v:
In Powder Technology 1 September 2024 445
Autor:
Dey, Nilabjo, Sharda, Janak, Saxena, Utkarsh, Kaushik, Divya, Singh, Utkarsh, Bhowmik, Debanjan
On-chip learning in a crossbar array based analog hardware Neural Network (NN) has been shown to have major advantages in terms of speed and energy compared to training NN on a traditional computer. However analog hardware NN proposals and implementa
Externí odkaz:
http://arxiv.org/abs/1907.00625
Autor:
Dankar, Apoorv, Verma, Anand, Saxena, Utkarsh, Kaushik, Divya, Chatterjee, Shouri, Bhowmik, Debanjan
Publikováno v:
Journal of Magnetism and Magnetic Materials vol. 489, no. 165434, 2019
Spintronic devices are considered as promising candidates in implementing neuromorphic systems or hardware neural networks, which are expected to perform better than other existing computing systems for certain data classification and regression task
Externí odkaz:
http://arxiv.org/abs/1811.09966
Publikováno v:
Scientific Reports; 11/14/2024, Vol. 12 Issue 1, p1-15, 15p
Akademický článek
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Autor:
Saxena, Utkarsh1 (AUTHOR), Moulik, Soumen1 (AUTHOR), Nayak, Soumya Ranjan2 (AUTHOR), Hanne, Thomas3 (AUTHOR), Sinha Roy, Diptendu1 (AUTHOR)
Publikováno v:
Mathematical Problems in Engineering. 11/23/2021, p1-12. 12p.