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Synopsis
Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations, and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs, and tools for use in experimental projects.
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About the Author
Dr Catherine C. McGeoch is the Beitzel Professor of Technology and Society in the Department of Computer Science at Amherst College. Professor McGeoch was co-founder (with David S. Johnson) in 1990 of the Discrete Mathematics and Theoretical Computer Science (DIMACS) Implementation Challenges. In 1999 she co-founded (with Michael Goodrich) the annual Workshop on Algorithm Engineering and Experimentation (ALENEX), sponsored by SIAM. She was Editor-in-Chief of the ACM Journal of Experimental Algorithmics from 2003 to 2008 and currently serves on the ACM Publications Board.
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A Guide to Experimental Algorithmics (Hardcover)
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Cambridge University Press, Cambridge, 2012
ISBN 10: 1107001730
ISBN 13: 9781107001732
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Hardcover. Condition: new. Hardcover. Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab contains downloadable files, programs and tools for use in experimental projects. This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781107001732
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A Guide to Experimental Algorithmics
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ISBN 10: 1107001730
ISBN 13: 9781107001732
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A Guide to Experimental Algorithmics
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ISBN 13: 9781107001732
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A Guide to Experimental Algorithmics
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A Guide to Experimental Algorithmics
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A Guide to Experimental Algorithmics (Hardcover)
Published by
Cambridge University Press, Cambridge, 2012
ISBN 10: 1107001730
ISBN 13: 9781107001732
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Hardcover
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab contains downloadable files, programs and tools for use in experimental projects. This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781107001732
Quantity: 1 available
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A Guide to Experimental Algorithmics (Hardcover)
Published by
Cambridge University Press, Cambridge, 2012
ISBN 10: 1107001730
ISBN 13: 9781107001732
New
Hardcover
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab contains downloadable files, programs and tools for use in experimental projects. This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781107001732
Quantity: 1 available