S. Nandakumar

发表

A phase-change memory model for neuromorphic computing

E. Eleftheriou, B. Rajendran, A. Sebastian, 2018, Journal of Applied Physics.

Supervised learning in spiking neural networks with MLC PCM synapses

B. Rajendran, S. R. Nandakumar, A. Sebastian, 2017, 2017 75th Annual Device Research Conference (DRC).

Optimised weight programming for analogue memory-based deep neural networks

M. Rasch, P. Narayanan, G. Burr, 2022, Nature Communications.

HERMES Core – A 14nm CMOS and PCM-based In-Memory Compute Core using an array of 300ps/LSB Linearized CCO-based ADCs and local digital processing

I. Ahsan, E. Eleftheriou, V. Narayanan, 2021, 2021 Symposium on VLSI Circuits.

ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator

Fernando García Redondo, Xavier Timoneda Comas, P. Whatmough, 2022, IEEE Micro.

Bio-mimetic Synaptic Plasticity and Learning in a sub-500mV Cu/SiO2/W Memristor

B. Rajendran, S. Nandakumar, 2020, ArXiv.

Building Brain-Inspired Computing Systems: Examining the Role of Nanoscale Devices

Bipin Rajendran, Shruti R. Kulkarni, Anakha V. Babu, 2018, IEEE Nanotechnology Magazine.

Neuromorphic computing with multi-memristive synapses

Yusuf Leblebici, Thomas P. Parnell, Evangelos Eleftheriou, 2017, Nature Communications.

Accurate deep neural network inference using computational phase-change memory

Evangelos Eleftheriou, S. R. Nandakumar, Irem Boybat, 2019, Nature Communications.

Mixed-precision architecture based on computational memory for training deep neural networks

Evangelos Eleftheriou, S. R. Nandakumar, Irem Boybat, 2018, 2018 IEEE International Symposium on Circuits and Systems (ISCAS).

HERMES-Core—A 1.59-TOPS/mm2 PCM on 14-nm CMOS In-Memory Compute Core Using 300-ps/LSB Linearized CCO-Based ADCs

I. Ahsan, E. Eleftheriou, A. Sebastian, 2022, IEEE Journal of Solid-State Circuits.

Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

Evangelos Eleftheriou, Bipin Rajendran, S. R. Nandakumar, 2019, Scientific Reports.

Mixed-Precision Deep Learning Based on Computational Memory

E. Eleftheriou, B. Rajendran, A. Sebastian, 2020, Frontiers in Neuroscience.

Phase-Change Memory Models for Deep Learning Training and Inference

Irem Boybat, Manuel Le Gallo, Abu Sebastian, 2019, 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS).

A 250 mV Cu/SiO2/W Memristor with Half-Integer Quantum Conductance States.

Catherine Dubourdieu, Bipin Rajendran, B. Rajendran, 2016, Nano letters.

AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator pdf

S. R. Nandakumar, Irem Boybat, Abu Sebastian, 2021, ArXiv.

Computational memory-based inference and training of deep neural networks

B. Rajendran, S. R. Nandakumar, A. Petropoulos, 2019, 2019 Symposium on VLSI Technology.

Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators

M. Rasch, P. Narayanan, G. Burr, 2023, Nature communications.

Impact of conductance drift on multi-PCM synaptic architectures

Yusuf Leblebici, Evangelos Eleftheriou, S. R. Nandakumar, 2018, 2018 Non-Volatile Memory Technology Symposium (NVMTS).

Deep learning acceleration based on in-memory computing

Nikolas Ioannou, Evangelos Eleftheriou, Pier Andrea Francese, 2019, IBM J. Res. Dev..

Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation

S. Ambrogio, A. Sebastian, T. Yamashita, 2021, 2021 IEEE International Reliability Physics Symposium (IRPS).

Precision of bit slicing with in-memory computing based on analog phase-change memory crossbars

A. Sebastian, I. Boybat, S. Nandakumar, 2022, Neuromorph. Comput. Eng..

Mixed-Precision Deep Learning Based on Computational Memory

Theodore Antonakopoulos, Evangelos Eleftheriou, Bipin Rajendran, 2020, Frontiers in Neuroscience.

Mixed-precision training of deep neural networks using computational memory pdf

Evangelos Eleftheriou, S. R. Nandakumar, Irem Boybat, 2017, ArXiv.

A 250 mV Cu/SiO2/W Memristor with Half-Integer Quantum Conductance States.

B. Rajendran, M. Minvielle, C. Dubourdieu, 2016, Nano letters.