Energy analysis and optimisation techniques for automatically synthesised coprocessors

Morgan, Paul (2008) Energy analysis and optimisation techniques for automatically synthesised coprocessors. EngD thesis, Universities of Edinburgh, Glasgow, Heriot-Watt, Strathclyde.

Abstract

The primary outcome of this research project is the development of a methodology enabling fast automated early-stage power and energy analysis of configurable processors for system-on-chip platforms. Such capability is essential to the process of selecting energy efficient processors during design-space exploration, when potential savings are highest. This has been achieved by developing dynamic and static energy consumption models for the constituent blocks within the processors.

Several optimisations have been identified, specifically targeting the most significant blocks in terms of energy consumption. Instruction encoding mechanism reduces both the energy and area requirements of the instruction cache; modifications to the multiplier unit reduce energy consumption during inactive cycles. Both techniques are demonstrated to offer substantial energy savings.

The aforementioned techniques have undergone detailed evaluation and, based on the positive outcomes obtained, have been incorporated into Cascade, a system-on-chip coprocessor synthesis tool developed by Critical Blue, to provide automated analysis and optimisation of processor energy requirements. This thesis details the process of identifying and examining each method, along with the results obtained. Finally, a case study demonstrates the benefits of the developed functionality, from the perspective of someone using Cascade to automate the creation of an energy-efficient configurable processor for system-on-chip platforms.

• Item Type: Thesis (EngD)
• Qualification Level: Doctoral
• Keywords: low power, low energy, system-on-chip, coprocessors, design automation
• Subjects: T Technology > T Technology (General)
• Colleges/Schools: College of Science and Engineering > School of Computing Science; College of Science and Engineering > School of Engineering
• Supervisor's Name: Topham, Prof Nigel
• Date of Award: 2008
• Depositing User: Mr Paul Morgan
• Unique ID: glathesis:2008-459
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 06 Nov 2008
• Last Modified: 10 Dec 2012 13:18
• URI: https://theses.gla.ac.uk/id/eprint/459