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OverviewDesigning new microprocessors is a time-consuming task. Architects rely on slow simulators to evaluate performance and a significant proportion of the design space has to be explored before an implementation is chosen. This becomes even more time-consuming when compiler optimisations are considered as part of the design process; once a new architecture is selected, a new compiler must be developed and tuned. This thesis proposes the use of machine-learning to address architecture/compiler co-design. The techniques developed in this work represent a new methodology that has the potential to speed up the design of new processors and automate the generation of the corresponding optimising compilers, resulting in higher system efficiency and shorter time-to-market. Full Product DetailsAuthor: Dr. Christophe DubachPublisher: BCS Learning & Development Limited Imprint: BCS, The Chartered Institute for IT Dimensions: Width: 21.00cm , Height: 0.50cm , Length: 29.70cm Weight: 0.415kg ISBN: 9781906124663ISBN 10: 1906124663 Pages: 165 Publication Date: 01 March 2010 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction 2 Machine-Learning and Evaluation Methodology 3 Related Work 4 Exploring and Predicting the Microarchitectural Design Space 5 Exploring and Predicting the Co-Design Space 6 Towards a Portable Optimising Compiler 7 ConclusionsReviewsAuthor InformationChristophe Dubach received his Ph.D in Informatics from the University of Edinburgh in 2009 and holds a M.Sc. degree in Computer Science from EPFL, Switzerland. He is currently an RAEng/EPSRC Research Fellow in the Institute for Computing Systems Architecture at the University of Edinburgh. Tab Content 6Author Website:Countries AvailableAll regions |
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