External Memory Algorithms
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External Memory Algorithms

External Memory Algorithms

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About the Book

We are especially proud to announce the publication of this ""DIMACS"" book - the 50th volume in this series, published by the AMS. The series was established out of a collaborative venture geared to unite the cutting-edge research at DIMACS with the resources at the AMS to produce useful, well-designed, important mathematical and computational sciences works. This volume is a hallmark in this firmly grounded and well-received AMS series. The AMS' 50th ""DIMACS"" volume is also particularly notable at this time: The year 1999 marks the 10th anniversary of the founding of DIMACS as a center. Participants in the DIMACS national research project are Rutgers University, Princeton University, AT&T Labs-Research, Bell Labs (Lucent Technologies), Telcordia Technologies, and NEC Research Institute.The success of the joint publishing venture between the AMS and DIMACS is excellent. We continue to work concordantly with the Center to further their goal of playing a key national leadership role in the development, application, and dissemination of discrete mathematics and theoretical computer science. This 50th ""DIMACS"" volume is in celebration of that dynamic, ongoing partnership. About the book: special techniques from computer science and mathematics are used to solve combinatorial problems whose associated data require a hierarchy of storage devices. These solutions employ 'extended memory algorithms'. The input/output (I/O) communication between the levels of the hierarchy is often a significant bottleneck, especially in applications that process massive amounts of data. Gains in performance are possible by incorporating locality directly into the algorithms and managing the contents of each storage level.The relative difference in data access speeds is more apparent between random access memory and magnetic disks. Therefore, much research has been devoted to algorithms that focus on this I/O bottleneck. These algorithms are usually called 'external memory', 'out-of-core', or 'I/O algorithms'.This volume presents new research results and current techniques for the design and analysis of external memory algorithms. The articles grew out of the workshop, 'External Memory Algorithms and Visualization' held at DIMACS. Leading researchers were invited to give lectures and to contribute their work. The topics presented include problems in computational geometry, graph theory, data compression, disk scheduling, linear algebra, statistics, software libraries, text and string processing, visualization, wavelets, and industrial applications. The vitality of the research and the interdisciplinary nature of the event produced fruitful ground for the compelling fusion of ideas and methods. This volume comprises the rich results that grew out of that process.

Table of Contents:
External memory algorithms and data structures by J. S. Vitter Synopsis data structures for massive data sets by P. B. Gibbons and Y. Matias Calculating robust depth measures for large data sets by I. Al-Furaih, T. Johnson, and S. Ranka Efficient cross-trees for external memory by R. Grossi and G. F. Italiano Computing on data streams by M. R. Henzinger, P. Raghavan, and S. Rajagopalan On maximum clique problems in very large graphs by J. Abello, P. M. Pardalos, and M. G. C. Resende I/O-optimal computation of segment intersections by A. Crauser, P. Ferragina, K. Mehlhorn, U. Meyer, and E. A. Ramos On showing lower bounds for external-memory computational geometry problems by L. Arge and P. B. Miltersen A survey of out-of-core algorithms in numerical linear algebra by S. Toledo Concrete software libraries by K.-P. Vo S(b)-tree library: An efficient way of indexing data by K. V. Shvachko ASP: Adaptive online parallel disk scheduling by M. Kallahalla and P. J. Varman Efficient schemes for distributing data on parallel memory systems by S. K. Das and M. C. Pinotti External memory techniques for isosurface extraction in scientific visualization by Y.-J. Chiang and C. T. Silva R-tree retrieval of unstructured volume data for visualization by S. T. Leutenegger and K.-L. Ma.


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Product Details
  • ISBN-13: 9780821811849
  • Publisher: American Mathematical Society
  • Publisher Imprint: American Mathematical Society
  • Language: English
  • ISBN-10: 0821811843
  • Publisher Date: 30 Nov 1999
  • Binding: Hardback
  • Weight: 794 gr


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