Algorithms and Data Structures for External Memory pdf epub mobi txt 电子书 下载 2025
- 算法
- 计算机科学
- algorithm
- Programming
- 性能
- 计算机技术
- 数据库
- 软件工程
- Algorithms
- Data
- Structures
- External
- Memory
- Books
- Computer
- Science
- Operations
- Research
具体描述
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.
作者简介
Jeffrey S. Vitter is a Distinguished Professor of Computer and Information Science at the University of Mississippi (affectionately known as Ole Miss). He has 39 years of experience as a passionate advocate for higher education. He served on the faculty and in leadership roles at noted AAU universities Brown, Duke, Purdue, Texas A&M, and Kansas, before leading Ole Miss as its 17th chancellor from January 2016–January 2019.
目录信息
1: Introduction
2: Parallel Disk Model (PDM)
3: Fundamental I/O Operations and Bounds
4: Exploiting Locality and Load Balancing
5: External Sorting and Related Problems
6: Lower Bounds and I/O
7: Matrix and Grid Computations
8: Batched Problems in Computational Geometry
9: Batched Problems on Graphs
10: External Hashing for Online Dictionary Search
11: Multiway Tree Data Structures
12: Spatial Data Structures and Range Search
13: Dynamic and Kinetic Data Structures
14: String Processing
15: Compressed Data Structures
16: Dynamic Memory Allocation
17: External Memory Programming Environments
Conclusions
Notations and Acronyms
References
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