Experimental Algorithmics From Algorithm Design to Robust and Efficient Software /
Experimental Algorithmics From Algorithm Design to Robust and Efficient Software / [electronic resource] :
edited by Rudolf Fleischer, Bernhard Moret, Erik Meineche Schmidt.
- 1st ed. 2002.
- XVIII, 286 p. online resource.
- Lecture Notes in Computer Science, 2547 1611-3349 ; .
- Lecture Notes in Computer Science, 2547 .
Algorithm Engineering for Parallel Computation -- Visualization in Algorithm Engineering: Tools and Techniques -- Parameterized Complexity: The Main Ideas and Connections to Practical Computing -- A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation -- Using Finite Experiments to Study Asymptotic Performance -- WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms -- Algorithms and Heuristics in VLSI Design -- Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics -- Presenting Data from Experiments in Algorithmics -- Distributed Algorithm Engineering -- Implementations and Experimental Studies of Dynamic Graph Algorithms.
Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
9783540363835
10.1007/3-540-36383-1 doi
Computer science.
Artificial intelligence--Data processing.
Algorithms.
Numerical analysis.
Computer science--Mathematics.
Discrete mathematics.
Computer Science.
Data Science.
Algorithms.
Numerical Analysis.
Discrete Mathematics in Computer Science.
QA75.5-76.95
004
Algorithm Engineering for Parallel Computation -- Visualization in Algorithm Engineering: Tools and Techniques -- Parameterized Complexity: The Main Ideas and Connections to Practical Computing -- A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation -- Using Finite Experiments to Study Asymptotic Performance -- WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms -- Algorithms and Heuristics in VLSI Design -- Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics -- Presenting Data from Experiments in Algorithmics -- Distributed Algorithm Engineering -- Implementations and Experimental Studies of Dynamic Graph Algorithms.
Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
9783540363835
10.1007/3-540-36383-1 doi
Computer science.
Artificial intelligence--Data processing.
Algorithms.
Numerical analysis.
Computer science--Mathematics.
Discrete mathematics.
Computer Science.
Data Science.
Algorithms.
Numerical Analysis.
Discrete Mathematics in Computer Science.
QA75.5-76.95
004