Foundations and TrendsŪ in Theoretical Computer Science
ALGORITHMS AND DATA STRUCTURES FOR EXTERNAL MEMORY
by Jeffrey Scott Vitter (Purdue University, USA)
Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. Algorithms and Data Structures for External Memory surveys the state of the art in the design and analysis of external memory (or EM) algorithms and data structures, where the goal is to exploit locality and parallelism in order to reduce the I/O costs. A variety of EM paradigms are considered for solving batched and online problems efficiently in external memory.
Algorithms and Data Structures for External Memory describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
Algorithms and Data Structures for External Memory is an invaluable reference for anybody interested in, or conducting research in the design, analysis, and implementation of algorithms and data structures.
Published by Now Publishers and marketed by World Scientific
Contents:
- Introduction
- Parallel Disk Model (PDM)
- Fundamental I/O Operations
and Bounds
- Exploiting Locality and Load Balancing
- External Sorting and Related Problems
- Lower Bounds and I/O 7: Matrix and Grid Computations
- Batched Problems in Computational Geometry
- Batched Problems on Graphs
- External Hashing for Online Dictionary Search
- Multiway Tree Data Structures
- Spatial Data Structures and Range Search
- Dynamic and Kinetic Data Structures
- String Processing
- Compressed Data Structures
- Dynamic Memory Allocation
- External Memory Programming Environments
- Conclusions
- Notations and Acronyms
- References
Readership: Postgraduates, researchers and professors of computer science,
especially algorithms, data structures and computational geometry.
| 180pp |
Pub. date: May 2008 |
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