10 citations · 37 across the 5 of their papers we have counts for
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cs.AR2021★ 8 cited
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator
Chuteng Zhou, Fernando Garcia Redondo, Julian Büchel +7
Always-on TinyML perception tasks in IoT applications require very high energy efficiency. Analog compute-in-memory (CiM) using non-volatile memory (NVM) promises high efficiency a…
cs.AR2021★ 3 cited
A System-Level Voltage/Frequency Scaling Characterization Framework for Multicore CPUs
George Papadimitriou, Manolis Kaliorakis, Athanasios Chatzidimitriou +4
Supply voltage scaling is one of the most effective techniques to reduce the power consumption of microprocessors. However, technology limitations such as aging and process variabi…