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As machine-learning models become larger and more complex, they require faster and more energy-efficient hardware to perform computations. Conventional digital computers are struggling to keep up.
Software Techniques to Reduce the Energy Consumption of Low-Power Devices at the Limits of Digital Abstractions
embedded systems energy low-power rfid security storage
2014/12/18
My thesis explores the effectiveness of software techniques that bend digital abstractions in order to allow embedded systems to do more with less energy. Recent years have witnessed a proliferation o...
The Limits of Buffering: A Tight Lower Bound for Dynamic Membership in the External Memory Model
Data Structures External Memory Membership
2012/12/3
We study the dynamic membership (or dynamic dictionary) problem, which is one of the most fundamental problems in data structures. We study the problem in the external memory model with cell size b bi...