Toggle Main Menu Toggle Search

Open Access padlockePrints

Real-Power Computing

Lookup NU author(s): Dr Rishad Shafik, Professor Alex Yakovlev



This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2018.

For re-use rights please refer to the publisher's terms and conditions.


The traditional hallmark in embedded systems is to minimize energy consumption considering hard or soft real-time deadlines. The basic principle is to transfigure the uncertainties of task execution times in the \textit{real} world into energy saving opportunities. The energy saving is achieved by suitably controlling the reliable power supply at circuit or system-level with the aim of minimizing the slack times, while meeting the specified performance requirements. Computing paradigm for emerging ubiquitous systems, particularly for the energy-harvested ones, has clearly shifted from the traditional systems. The energy supply of these systems can vary temporally and spatially within a dynamic range, essentially making computation extremely challenging. Such a paradigm shift requires disruptive approaches to design computing systems that can provide continued functionality under unreliable supply power envelope and operate with autonomous survivability (i.e. the ability to automatically guarantee retention and\slash or completion of a given computation task). In this paper, we introduce \textit{Real-Power Computing}, inspired by the above trends and tenets. We show how computation systems must be designed with power-proportionality to achieve sustained computation and survivability when operating at extreme power conditions. We present extensive analysis of the need for this new computing approach using definitions, where necessary, coupled with detailed taxonomies, empirical observations, a review of relevant research works and example scenarios using three case studies representing the proposed paradigm.

Publication metadata

Author(s): Shafik R, Yakovlev A, Das S

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Computers

Year: 2018

Volume: 67

Issue: 10

Pages: 1445-1461

Print publication date: 01/10/2018

Online publication date: 03/04/2018

Acceptance date: 27/03/2018

Date deposited: 19/04/2018

ISSN (print): 0018-9340

ISSN (electronic): 1557-9956

Publisher: IEEE


DOI: 10.1109/TC.2018.2822697


Altmetrics provided by Altmetric