# Irem Boybat

## contact information

In-memory computing

IBM Research Europe

+41447248879

IBM Research Europe

+41447248879

## links

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**More information:**Google Scholar | Neuromorphic & In-memory computing at IBM Research Europe | AI Hardware at IBM Research | WiPLASH (EU Horizon 2020 Project) | Frontiers Research Topic: Hardware for AI

**2021**

Analog in-memory compute cores for accelerating AI applications

I. Boybat

I. Boybat

*High Performance and Embedded Architecture and Compilation (HiPEAC)*, Tutorial: Using gem5 and full-system RISC-V simulation to enable the optimization of heterogeneous architectures, 2021**2020**

Precision of synaptic weights programmed in phase-change memory devices for deep learning inference

S. R. Nandakumar, I. Boybat, J.-P. Han, S. Ambrogio, P. Adusumilli, R. L. Bruce, M. BrightSky, M. Rasch, M. Le Gallo, A. Sebastian

S. R. Nandakumar, I. Boybat, J.-P. Han, S. Ambrogio, P. Adusumilli, R. L. Bruce, M. BrightSky, M. Rasch, M. Le Gallo, A. Sebastian

*International Electron Devices Meeting (IEDM)*, 2020
Accurate deep neural network inference using computational phase-change memory

V. Joshi, M. Le Gallo, S. Haefeli, I. Boybat, S. R. Nandakumar, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian, E. Eleftheriou

V. Joshi, M. Le Gallo, S. Haefeli, I. Boybat, S. R. Nandakumar, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian, E. Eleftheriou

*Nature Communications*, 2020
Experimental demonstration of supervised learning in spiking neural networks with phase-change memory synapses

S. R. Nandakumar, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, B. Rajendran

S. R. Nandakumar, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, B. Rajendran

*Scientific Reports*, 2020
Mixed-precision deep learning based on computational memory

S. R. Nandakumar, M. Le Gallo, C. Piveteau, V. Joshi, G, Mariani, I. Boybat, G. Karunaratne, R. Khaddam-Aljameh, U. Egger, A. Petropoulos, T. Antonakopoulos, B. Rajendran, A. Sebastian, E. Eleftheriou

S. R. Nandakumar, M. Le Gallo, C. Piveteau, V. Joshi, G, Mariani, I. Boybat, G. Karunaratne, R. Khaddam-Aljameh, U. Egger, A. Petropoulos, T. Antonakopoulos, B. Rajendran, A. Sebastian, E. Eleftheriou

*Frontiers in Neuroscience*, 2020
Accurate emulation of memristive crossbar arrays for in-memory computing

A. Petropoulos, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, T. Antonakopoulos

A. Petropoulos, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, T. Antonakopoulos

*IEEE International Symposium on Circuits and Systems (ISCAS)*, 2020
ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning

V. Joshi, G. Karunaratne, M. Le Gallo, I. Boybat, C. Piveteau, A. Sebastian, B. Rajendran, E. Eleftheriou

V. Joshi, G. Karunaratne, M. Le Gallo, I. Boybat, C. Piveteau, A. Sebastian, B. Rajendran, E. Eleftheriou

*IEEE International Symposium on Circuits and Systems (ISCAS)*, 2020
Graphene-based wireless agile interconnects for massive heterogeneous multi-chip processors

S. Abadal, R. Guirado, H. Taghvaee, A. Jain, E. Pereira de Santana, P. H. Bolivar, M. Saeed, R. Negra, Z. Wang, K.-T. Wang, M. C. Lemme, J. Klein, M. Zapater, A. Levisse, D. Atienza, D. Rossi, F. Conti, M. Dazzi, G. Karunaratne, I. Boybat, A. Sebastian

S. Abadal, R. Guirado, H. Taghvaee, A. Jain, E. Pereira de Santana, P. H. Bolivar, M. Saeed, R. Negra, Z. Wang, K.-T. Wang, M. C. Lemme, J. Klein, M. Zapater, A. Levisse, D. Atienza, D. Rossi, F. Conti, M. Dazzi, G. Karunaratne, I. Boybat, A. Sebastian

*ArXiv*, 2020**2019**

Phase-change memory models for deep learning training and inference

S. R. Nandakumar, I. Boybat, V. Joshi, C. Piveteau, M. Le Gallo, B. Rajendran, A. Sebastian, E. Eleftheriou

S. R. Nandakumar, I. Boybat, V. Joshi, C. Piveteau, M. Le Gallo, B. Rajendran, A. Sebastian, E. Eleftheriou

*IEEE International Conference on Electronics Circuits and Systems (ICECS)*, 2019
Deep Learning Acceleration based on In-memory Computing

E. Eleftheriou, M. Le Gallo, S. R. Nandakumar, C. Piveteau, I. Boybat, V. Joshi, R. Khaddam-Aljameh, M. Dazzi, I. Giannopoulos, G. Karunaratne, B. Kersting, M. Stanisavijevic, V. P, Jonnalagadda, N. Ioannou, K. Kourtis, P. A. Francese, A. Sebastian

E. Eleftheriou, M. Le Gallo, S. R. Nandakumar, C. Piveteau, I. Boybat, V. Joshi, R. Khaddam-Aljameh, M. Dazzi, I. Giannopoulos, G. Karunaratne, B. Kersting, M. Stanisavijevic, V. P, Jonnalagadda, N. Ioannou, K. Kourtis, P. A. Francese, A. Sebastian

*IBM Journal of Research and Development*, 2019
Computational memory-based inference and training of deep neural networks

A. Sebastian, I. Boybat, M. Dazzi, I. Giannopoulos, V. Jonnalagadda, V. Joshi, G. Karunaratne, B. Kersting, R. Khaddam-Aljameh, S. R. Nandakumar, A. Petropoulos, C. Piveteau, T. Antonakopoulos, B. Rajendran, M. Le Gallo, E. Eleftheriou

A. Sebastian, I. Boybat, M. Dazzi, I. Giannopoulos, V. Jonnalagadda, V. Joshi, G. Karunaratne, B. Kersting, R. Khaddam-Aljameh, S. R. Nandakumar, A. Petropoulos, C. Piveteau, T. Antonakopoulos, B. Rajendran, M. Le Gallo, E. Eleftheriou

*VLSI Symposium*, 2019
Accurate deep neural network inference using computational phase-change memory

V. Joshi, M. Le Gallo, I. Boybat, S. Haefeli, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian, E. Eleftheriou

V. Joshi, M. Le Gallo, I. Boybat, S. Haefeli, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian, E. Eleftheriou

*ArXiv*, 2019
Supervised learning in spiking neural networks with phase-change memory synapses

S. R. Nandakumar, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, B. Rajendran

S. R. Nandakumar, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian, B. Rajendran

*ArXiv*, 2019
Multi-ReRAM synapses for artificial neural network training

I. Boybat, C. Giovinazzo, E. Shahrabi, I. Krawczuk, I. Giannopoulos, C. Piveteau, M. Le Gallo, C. Ricciardi, A. Sebastian, E. Eleftheriou, Y. Leblebici

I. Boybat, C. Giovinazzo, E. Shahrabi, I. Krawczuk, I. Giannopoulos, C. Piveteau, M. Le Gallo, C. Ricciardi, A. Sebastian, E. Eleftheriou, Y. Leblebici

*IEEE International Symposium on Circuits and Systems (ISCAS)*, 2019**2018**

Impact of conductance drift on multi-PCM synaptic architectures

I. Boybat, S. R. Nandakumar, M. Le Gallo, B. Rajendran, Y. Leblebici, A. Sebastian, E. Eleftheriou

I. Boybat, S. R. Nandakumar, M. Le Gallo, B. Rajendran, Y. Leblebici, A. Sebastian, E. Eleftheriou

*Non-Volatile Memory Technology Symposium (NVMTS)*, 2018
Multi-PCM synapses for spiking neural networks

I. Boybat, M. Le Gallo, S. R. Nandakumar, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

I. Boybat, M. Le Gallo, S. R. Nandakumar, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

*European Phase-Change and Ovonic Symposium (E\PCOS)*, 2018
Neuromorphic computing with multi-memristive synapses

I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Parnell, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Parnell, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

*Nature Communications (Designated as one of the top 50 Nature Communications physics articles of 2018)*
Equivalent-accuracy accelerated neural-network training using analogue memory

S. Ambrogio, P. Narayanan, H. Tsai, R. M. Shelby, I. Boybat, C. di Nolfo, S. Sidler, M. Giordano, M. Bodini, N. C. P. Farinha, B. Killeen, C. Cheng, Y. Jaoudi and G. W. Burr

S. Ambrogio, P. Narayanan, H. Tsai, R. M. Shelby, I. Boybat, C. di Nolfo, S. Sidler, M. Giordano, M. Bodini, N. C. P. Farinha, B. Killeen, C. Cheng, Y. Jaoudi and G. W. Burr

*Nature*, 2018
A phase-change memory model for neuromorphic computing

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, and E. Eleftheriou

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, and E. Eleftheriou

*Journal of Applied Physics*, 2018
Mixed-precision architecture based on computational memory for training deep neural networks

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian and E. Eleftheriou

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian and E. Eleftheriou

*IEEE International Symposium on Circuits and Systems (ISCAS)*, 2018
Memristive synapses for neuromorphic computing

I. Boybat

I. Boybat

*Invited talk at Neuromorphic computing and hardware - Gothenburg - Stockholm joint workshop*, 2018
Signal and noise extraction from non-volatile memory for neuromorphic computing: A machine learning based approach

T. Ando, N. Gong, T. Ide, S. Kim, I. Boybat, A. Sebastian and V. Narayanan

T. Ando, N. Gong, T. Ide, S. Kim, I. Boybat, A. Sebastian and V. Narayanan

*Neuro Inspired Computational Elements Workshop (NICE)*, 2018
Signal and noise extraction from analog memory elements for neuromorphic computing

N. Gong, T. Ide, S. Kim, I. Boybat, A. Sebastian, V. Narayanan and T. Ando

N. Gong, T. Ide, S. Kim, I. Boybat, A. Sebastian, V. Narayanan and T. Ando

*Nature Communications*, 2018**2017**

Multilayer Perceptron Algorithm: Impact of Nonideal Conductance and Area-Efficient Peripheral Circuits

L. L. Sanches, A. Fumarola, S. Sidler, P. Narayanan, I. Boybat, J. Jang, K. Moon, R. M. Shelby, Y. Leblebici, H. Hwang and G. W. Burr

L. L. Sanches, A. Fumarola, S. Sidler, P. Narayanan, I. Boybat, J. Jang, K. Moon, R. M. Shelby, Y. Leblebici, H. Hwang and G. W. Burr

*Neuro-inspired Computing Using Resistive Synaptic Devices*, 2017
Mixed-precision training of deep neural networks using computational memory

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, E. Eleftheriou

S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, E. Eleftheriou

*ArXiv*, 2017
Improved deep neural network hardware-accelerators based on non-volatile-memory: the local gains technique

I. Boybat, C. Di Nolfo, S. Ambrogio, M. Bodini, N. C. P. Farinha, R. M. Shelby, P. Narayanan, S. Sidler, H. Tsai, Y. Leblebici, and G. W. Burr

I. Boybat, C. Di Nolfo, S. Ambrogio, M. Bodini, N. C. P. Farinha, R. M. Shelby, P. Narayanan, S. Sidler, H. Tsai, Y. Leblebici, and G. W. Burr

*International Conference on Rebooting Computing (ICRC)*, 2017
Supervised Learning in Spiking Neural Networks with MLC PCM Synapses

S. R. Nandakumar, I. Boybat, M. Le Gallo, A. Sebastian, B. Rajendran, and E. Eleftheriou

S. R. Nandakumar, I. Boybat, M. Le Gallo, A. Sebastian, B. Rajendran, and E. Eleftheriou

*Device Research Conference (DRC)*, 2017
Stochastic weight updates in phase-change memory-based synapses and their influence on artificial neural networks

I. Boybat, M. Le Gallo, T. Moraitis, Y. Leblebici, A. Sebastian, and E. Eleftheriou

I. Boybat, M. Le Gallo, T. Moraitis, Y. Leblebici, A. Sebastian, and E. Eleftheriou

*Conference on PhD Research in Microelectronics and Electronics (PRIME)*, 2017
Fatiguing STDP: Learning from Spike-Timing Codes in the Presence of Rate Codes

T. Moraitis, A. Sebastian, I. Boybat, M. Le Gallo, T. Tuma, and E. Eleftheriou

T. Moraitis, A. Sebastian, I. Boybat, M. Le Gallo, T. Tuma, and E. Eleftheriou

*International Joint Conference on Neural Networks (IJCNN)*, 2017
An efficient synaptic architecture for artificial neural networks

I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian and E. Eleftheriou

*Non-Volatile Memory Technology Symposium (NVMTS)*, 2017**2016**

Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Impact of conductance response

S. Sidler, I. Boybat, R. M. Shelby, P. Narayanan, J. Jang, A. Fumarola, K. Moon, Y. Leblebici, H. Hwang, and G. W. Burr

S. Sidler, I. Boybat, R. M. Shelby, P. Narayanan, J. Jang, A. Fumarola, K. Moon, Y. Leblebici, H. Hwang, and G. W. Burr

*European Solid-State Device Research Conference (ESSDERC)*, 2016
Neuromorphic computing using non-volatile memory

G. W. Burr, R. M. Shelby, A. Sebastian, S. Kim, S. Kim, S.Sidler, K. Virwani, M. Ishii, P. Narayanan, A. Fumarola, L. L. Sanches, I. Boybat, M. Le Gallo, K. Moon, J. Woo, H. Hwang, Y. Leblebici

G. W. Burr, R. M. Shelby, A. Sebastian, S. Kim, S. Kim, S.Sidler, K. Virwani, M. Ishii, P. Narayanan, A. Fumarola, L. L. Sanches, I. Boybat, M. Le Gallo, K. Moon, J. Woo, H. Hwang, Y. Leblebici

*Advances in Physics: X*, 2016
Nonvolatile nemory crossbar arrays for non-von Neumann computing

S. Sidler, J. Jang, G. W. Burr, R. M. Shelby, I. Boybat, C. di Nolfo, P. Narayanan, K. Virwani, H. Hwang

S. Sidler, J. Jang, G. W. Burr, R. M. Shelby, I. Boybat, C. di Nolfo, P. Narayanan, K. Virwani, H. Hwang

*Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices*, 2016**2015**

Cognitive Computing with Non-Volatile Memory Elements

I. Boybat, J. Sandrini, D. Sacchetto, G.W. Burr, and Y. Leblebici

I. Boybat, J. Sandrini, D. Sacchetto, G.W. Burr, and Y. Leblebici

*MemoCIS Training School*, 2015
Non-volatile memory crossbar arrays for non-Von Neumann computing (Invited)

G. W. Burr, R. M. Shelby, I. Boybat, S. Sidler, and C. di Nolfo

G. W. Burr, R. M. Shelby, I. Boybat, S. Sidler, and C. di Nolfo

*Electronic Materials Conference (EMC)*, 2015
Crossbar arrays for Storage Class Memory and non-Von Neumann computing (Invited)

G. W. Burr, R. M. Shelby, S. Sidler, P. Narayanan, I. Boybat, and C. di Nolfo

G. W. Burr, R. M. Shelby, S. Sidler, P. Narayanan, I. Boybat, and C. di Nolfo

*European Phase-Change and Ovonic Symposium (E\PCOS)*, 2015
PCM for neuromorphic applications: Impact of device characteristics on neural network performance

I. Boybat, S. Sidler, C. di Nolfo, R. M. Shelby, P. Narayanan, Y. Leblebici, and G. W. Burr

I. Boybat, S. Sidler, C. di Nolfo, R. M. Shelby, P. Narayanan, Y. Leblebici, and G. W. Burr

*European Phase-Change and Ovonic Symposium (E\PCOS)*, 2015
Non-volatile memory as hardware synapse in neuromorphic computing: A first look at reliability issues (Invited)

R. M. Shelby, G. W. Burr, I. Boybat, and C. di Nolfo

R. M. Shelby, G. W. Burr, I. Boybat, and C. di Nolfo

*International Reliability Physics Symposium (IRPS)*, 2015
Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Comparative performance analysis (accuracy, speed, and power) (Invited)

G. W. Burr, P. Narayanan, R. M. Shelby, S. Sidler, I. Boybat, C. di Nolfo, Y. Leblebici

G. W. Burr, P. Narayanan, R. M. Shelby, S. Sidler, I. Boybat, C. di Nolfo, Y. Leblebici

*International Electron Devices Meeting (IEDM)*, 2015
Experimental demonstration and tolerancing of a large-scale neural network (165,000 synapses), using phase-change memory as the synaptic weight element (Invited)

G. W. Burr, R. M. Shelby, C. di Nolfo, J. W. Jang, I. Boybat, R. S. Shenoy, P. Narayanan, K. Virwani, E. U. Giacometti, B. Kurdi, and H. Hwang

G. W. Burr, R. M. Shelby, C. di Nolfo, J. W. Jang, I. Boybat, R. S. Shenoy, P. Narayanan, K. Virwani, E. U. Giacometti, B. Kurdi, and H. Hwang

*IEEE Transactions on Electron Devices*, 2015**2013**

A hardware-oriented dynamically adaptive disparity estimation algorithm and its real-time hardware

A. Akin, I. Baz, B. Atakan, I. Boybat, A. Schmid, and Y. Leblebici

A. Akin, I. Baz, B. Atakan, I. Boybat, A. Schmid, and Y. Leblebici

*Proceedings of the ACM international conference on Great lakes symposium on VLSI (GLSVLSI)*, 2013