Algorithm Engineering And Experiments
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Author | : David M. Mount |
Publisher | : Springer |
Total Pages | : 215 |
Release | : 2002-01-01 |
Genre | : Computers |
ISBN | : 3540456430 |
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Algorithm Engineering and Experiments, ALENEX 2002, held in San Francisico, CA, USA in January 2002.The 15 revised full papers presented were carefully reviewed and selected from 34 submissions. Among the topics addressed are hewistics for algorithms, combinatorial optimization, searching, graph computation, network optimization, scheduling, computational geometry, sorting, and clustering algorithms.
Author | : Lasse Kliemann |
Publisher | : Springer |
Total Pages | : 428 |
Release | : 2016-11-10 |
Genre | : Computers |
ISBN | : 3319494872 |
Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.
Author | : Matthias Müller-Hannemann |
Publisher | : Springer Science & Business Media |
Total Pages | : 527 |
Release | : 2010-08-05 |
Genre | : Computers |
ISBN | : 3642148654 |
Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.
Author | : Rajeev Raman |
Publisher | : SIAM |
Total Pages | : 298 |
Release | : 2006-01-01 |
Genre | : Mathematics |
ISBN | : 9780898716108 |
The annual Workshop on Algorithm Engineering and Experiments (ALENEX) provides a forum for the presentation of original research in all aspects of algorithm engineering, including the implementation and experimental evaluation of algorithms and data structures. The workshop was sponsored by SIAM, the Society for Industrial and Applied Mathematics, and SIGACT, the ACM Special Interest Group on Algorithms and Computation Theory. The aim of ANALCO is to provide a forum for the presentation of original research in the analysis of algorithms and associated combinatorial structures.
Author | : |
Publisher | : |
Total Pages | : 238 |
Release | : 2002 |
Genre | : Computer algorithms |
ISBN | : |
Author | : Richard E. Ladner |
Publisher | : SIAM |
Total Pages | : 162 |
Release | : 2003-01-01 |
Genre | : Mathematics |
ISBN | : 9780898715422 |
The ALENEX workshop provides a forum for the presentation of original research in the implementation and experimental evaluation of algorithms and data structures. This volume collects extended versions of the 12 papers that were selected for presentation.
Author | : Uwe Naumann |
Publisher | : CRC Press |
Total Pages | : 602 |
Release | : 2012-01-25 |
Genre | : Computers |
ISBN | : 1439827354 |
Combinatorial Scientific Computing explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It includes contributions from international researchers who are pioneers in designing software and applications for high-performance computing systems. The book offers a state-of-the-art overview of the latest research, tool development, and applications. It focuses on load balancing and parallelization on high-performance computers, large-scale optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications in large-scale social networks. The authors unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs. Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations and their importance continues to grow with the demands of new applications and advanced architectures. By addressing current challenges in the field, this volume sets the stage for the accelerated development and deployment of fundamental enabling technologies in high-performance scientific computing.
Author | : Jürgen Lerner |
Publisher | : Springer Science & Business Media |
Total Pages | : 411 |
Release | : 2009-07-02 |
Genre | : Computers |
ISBN | : 3642020933 |
A state-of-the-art survey that reports on the progress made in selected areas of this important and growing field, aiding the analysis of existing networks and the design of new and more efficient algorithms for solving various problems on these networks.
Author | : Ian Munro |
Publisher | : |
Total Pages | : 278 |
Release | : 2008 |
Genre | : Computers |
ISBN | : |
Author | : Michael Mitzenmacher |
Publisher | : Cambridge University Press |
Total Pages | : 372 |
Release | : 2005-01-31 |
Genre | : Computers |
ISBN | : 9780521835404 |
Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.