Approximate Computing for Deep Learning in TensorFlow Chiang Chi-An T H E U N I V E R S I T Y O F E D I N B U R G H Master of Science School of Informatics University of Edinburgh 2017 Abstract Nowadays, many machine learning techniques are applied on the smart phone […]
PowerPoint Presentation Dr Massoud Zolgharni mzolgharni@lincoln.ac.uk Room SLB1004, SLB Dr Grzegorz Cielniak gcielniak@lincoln.ac.uk Room INB2221, INB Week W/C Lecture Workshop 1 23/01 Introduction – 2 30/01 Architectures Tutorial-1 3 06/02 Patterns 1 4 13/02 Patterns 2 Tutorial-2 5 20/02 Patterns 3 6 27/02 Patterns 4 Tutorial-3 7 06/03 Communication & Synchronisation 8 13/03 Algorithms 1
Approximate Computing for Deep Learning in TensorFlow Chiang Chi-An T H E U N I V E R S I T Y O F E D I N B U R G H Master of Science School of Informatics University of Edinburgh 2017 Abstract Deep learning techniques have achieved remarkable breakthroughs in many areas such
COMP6714 Lecture 2 Information Retrieval and Search Engines Lecturer: Wei Wang Date: 1 Preliminaries Before studying the MaxScore algorithm, it is beneficial to review and have a deeper understanding of the vanilla DAAD query processing algorithm. In particular, find out the similarities and differences between the DAAD algorithm and the algorithm to process the disjunctive
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Operating Systems: Principles and Practice (Volume 3 of 4) Operating Systems Principles & Practice Volume III: Memory Management Second Edition Thomas Anderson University of Washington Mike Dahlin University of Texas and Google Recursive Books recursivebooks.com 2 Operating Systems: Principles and Practice (Second Edition) Volume III: Memory Management by Thomas Anderson and Michael Dahlin Copyright ©Thomas
Operating Systems: Principles and Practice (Volume 4 of 4) Operating Systems Principles & Practice Volume IV: Persistent Storage Second Edition Thomas Anderson University of Washington Mike Dahlin University of Texas and Google Recursive Books recursivebooks.com 2 Operating Systems: Principles and Practice (Second Edition) Volume IV: Persistent Storage by Thomas Anderson and Michael Dahlin Copyright ©Thomas
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (Preliminary White Paper, November 9, 2015) Martı́n Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg,
MODULE & LECTURER: Distributed and Cloud Computing; Dr. Padraig Corcoran TITLE: Design of a Distributed System The penalty for late or non-submission is an award of zero marks. Your work should be submitted using the official Coursework Submission Cover sheet. INSTRUCTIONS You have been hired to build a distributed data storage system for a property
Week 8 – Coordination and Agreement COORDINATION AND AGREEMENT Dr Bailin Deng Motivation • Processes within a distributed system need to coordinate actions or agree on values Motivation • Processes within a distributed system need to coordinate actions or agree on values • Example: different computers controlling a spaceship • Agreement on current mission status:
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PowerPoint Presentation Dr Massoud Zolgharni mzolgharni@lincoln.ac.uk Room SLB1004, SLB Dr Grzegorz Cielniak gcielniak@lincoln.ac.uk Room INB2221, INB Dr Grzegorz Cielniak (module coordinator) • lecturer, researcher in autonomous systems (robotics, machine vision) • week 1-6 Dr Massoud Zolgharni • lecturer, expertise in medical imaging • week 7-13 Demonstrators • Jacob Carse, Cheng Hu, Jacobus Lock Lecture •
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