Nandakumar, S. R.
IBM Research - Zurich
8 papers on CoChatORCID 0000-0002-7930-508X
Most cited papers
- Verified
Neuromorphic computing with multi-memristive synapses
Boybat, I., Le Gallo, M., Nandakumar, S. R., Moraitis, T., Parnell, T., Tuma, T., Rajendran, B., Leblebici, Y., Sebastian, A., & Eleftheriou, E. (2018) · Nature Communications
Advanced Memory and Neural ComputingNeural Networks and Reservoir Computing
Cited by 899
- Verified
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Rasch, M. J., Mackin, C., Le Gallo, M., Chen, A., Fasoli, A., Odermatt, F., Li, N., Nandakumar, S. R., Narayanan, P., Tsai, H., et al. (2023) · Nature Communications
Advanced Memory and Neural ComputingAdvanced Neural Network Applications
Cited by 213
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HERMES-Core—A 1.59-TOPS/mm 2 PCM on 14-nm CMOS In-Memory Compute Core Using 300-ps/LSB Linearized CCO-Based ADCs
Khaddam-Aljameh, R., Stanisavljevic, M., Fornt Mas, J., Karunaratne, G., Brändli, M., Liu, F., Singh, A., Müller, S. M., Egger, U., Petropoulos, A., et al. (2022) · IEEE Journal of Solid-State Circuits
Advanced Memory and Neural ComputingLow-power high-performance VLSI design
Cited by 144
- Verified
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
Khaddam-Aljameh, R., Stanisavljevic, M., Fornt Mas, J., Karunaratne, G., Braendli, M., Liu, F., Singh, A., Müller, S. M., Egger, U., Petropoulos, A., et al. (2021) · 2021 Symposium on VLSI Circuits
Advanced Memory and Neural ComputingLow-power high-performance VLSI design
Cited by 124
- Verified
Mixed-Precision Deep Learning Based on Computational Memory
Nandakumar, S. R., Le Gallo, M., Piveteau, C., Joshi, V., Mariani, G., Boybat, I., Karunaratne, G., Khaddam-Aljameh, R., Egger, U., Petropoulos, A., et al. (2020) · Frontiers in Neuroscience
Advanced Memory and Neural ComputingAdvanced Neural Network Applications
Cited by 120
- Verified
Phase-Change Memory Models for Deep Learning Training and Inference
Nandakumar, S. R., Boybat, I., Joshi, V., Piveteau, C., Le Gallo, M., Rajendran, B., Sebastian, A., & Eleftheriou, E. (2019) · 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
Advanced Memory and Neural ComputingPhase-change materials and chalcogenides
Cited by 34
- Verified
Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation
Bruce, R. L., Sarwat, S. G., Boybat, I., Cheng, C.-W., Kim, W., Nandakumar, S. R., Mackin, C., Philip, T., Liu, Z., Brew, K., et al. (2021) · 2021 IEEE International Reliability Physics Symposium (IRPS)
Advanced Memory and Neural ComputingPhase-change materials and chalcogenides
Cited by 23
- Verified
Supervised learning in spiking neural networks with MLC PCM synapses
Nandakumar, S. R., Boybat, I., Le Gallo, M., Sebastian, A., Rajendran, B., & Eleftheriou, E. (2017) · 2017 75th Annual Device Research Conference (DRC)
Advanced Memory and Neural ComputingNeural dynamics and brain function
Cited by 13
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