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Mass Efficient Computing

Lead Research Organisation: University of Cambridge
Department Name: Engineering

Abstract

Traditionally, a computing system is optimised for one of two things; power or performance. Mass-Efficient computing sees that adoption of a new paradigm, where the system is instead optimised for mass. By developing an architecture tailored to minimising mass, it is expected that it is possible to reduce the mass of a contemporary system by a factor of 2-5 times.

A mass-efficient architecture shall optimise at the system level, using the state-of-the-art in energy scavenge systems, photovoltaics, sensors, actuators, energy storage, imaging systems and microelectronics. It is expected that trading off different parts of these systems, combined with a new way of thinking with mass-efficient systems shall lead to novel solutions. A successful implementation of mass-efficient computing shall have significant implications across a number of fields such as nano-drones, implantable medical devices, miniaturised sensors and robotics.

People

ORCID iD

Andrew Kadis (Student)

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509620/1 30/09/2016 29/09/2022
2108797 Studentship EP/N509620/1 30/09/2018 30/12/2021 Andrew Kadis
NE/W503204/1 31/03/2021 30/03/2022
2108797 Studentship NE/W503204/1 30/09/2018 30/12/2021 Andrew Kadis