Khaddam-Aljameh, Riduan
IBM Research - Zurich
6 papers on CoChatORCID 0000-0002-8320-8311
Most cited papers
- Verified
Memory devices and applications for in-memory computing
Sebastian, A., Le Gallo, M., Khaddam-Aljameh, R., & Eleftheriou, E. (2020) · Nature Nanotechnology
Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance Devices
Cited by 2,289
- Verified
A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference
Le Gallo, M., Khaddam-Aljameh, R., Stanisavljevic, M., Vasilopoulos, A., Kersting, B., Dazzi, M., Karunaratne, G., Brändli, M., Singh, A., Müller, S. M., et al. (2023) · Nature Electronics
Advanced Memory and Neural ComputingLow-power high-performance VLSI design
Cited by 310
- Verified
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
Fully On-Chip MAC at 14 nm Enabled by Accurate Row-Wise Programming of PCM-Based Weights and Parallel Vector-Transport in Duration-Format
Narayanan, P., Ambrogio, S., Okazaki, A., Hosokawa, K., Tsai, H., Nomura, A., Yasuda, T., Mackin, C., Lewis, S. C., Friz, A., et al. (2021) · IEEE Transactions on Electron Devices
Advanced Memory and Neural ComputingLow-power high-performance VLSI design
Cited by 85
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