A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference
- Manuel Le Gallo
- Riduan Khaddam-Aljameh
- et al.
- Nature Electronics
Geethan Karunaratne received his B.Sc. degree in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka in 2014, and the M.Sc. degree in Information Technology and Electrical Engineering from ETH Zurich in 2018. Prior to beginning his master's, he joined the then incubated start-up Paraqum Technologies, Sri Lanka, where he worked on developing high-end hardware video encoders and decoders.
In 2018, he joined IBM Research – Zurich, where he is currently a member of the In-memory computing group. Geethan is working towards his PhD at ETH Zurich. His main research interests are in-memory computing and brain-inspired computing.
Geethan is interested in hardware acceleration, energy-efficient VLSI architectures, machine learning, neuromorphic computing, and machine vision. He has experience in configurable architectures, FPGA ASIC design flows, and hardware emulation.