Algorithms and Data Structures for External Memory

Algorithms and Data Structures for External Memory PDF Author: Jeffrey Scott Vitter
Publisher: Now Publishers Inc
ISBN: 1601981066
Category : Computers
Languages : en
Pages : 192

Get Book Here

Book Description
Describes several useful paradigms for the design and implementation of efficient external memory (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

Algorithms and Data Structures for External Memory PDF Author: Jeffrey Scott Vitter
Publisher: Now Publishers Inc
ISBN: 1601981066
Category : Computers
Languages : en
Pages : 192

Get Book Here

Book Description
Describes several useful paradigms for the design and implementation of efficient external memory (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.

External Memory Algorithms

External Memory Algorithms PDF Author: James M. Abello
Publisher: American Mathematical Soc.
ISBN: 9780821870938
Category : Mathematics
Languages : en
Pages : 330

Get Book Here

Book Description
This volume presents new research results and current techniques for the design and analysis of external memory algorithms. 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.

External Memory Algorithms

External Memory Algorithms PDF Author: James M. Abello
Publisher: American Mathematical Soc.
ISBN: 0821811843
Category : Computers
Languages : en
Pages : 321

Get Book Here

Book Description
The algorithms involve using techniques from computer science and mathematics to solve combinatorial problems whose associated data require the use of a hierarchy of storage devices. The 15 papers discuss such topics as synopsis data structures for massive data sets, maximum clique problems in very large graphs, concrete software libraries, computing on data streams, efficient cross-trees for external memory, efficient schemes for distributing data on parallel memory systems, and external memory techniques for iso-surface extraction in scientific visualization. Annotation copyrighted by Book News, Inc., Portland, OR.

Algorithms for Memory Hierarchies

Algorithms for Memory Hierarchies PDF Author: Ulrich Meyer
Publisher: Springer
ISBN: 3540365745
Category : Computers
Languages : en
Pages : 443

Get Book Here

Book Description
Algorithms that have to process large data sets have to take into account that the cost of memory access depends on where the data is stored. Traditional algorithm design is based on the von Neumann model where accesses to memory have uniform cost. Actual machines increasingly deviate from this model: while waiting for memory access, nowadays, microprocessors can in principle execute 1000 additions of registers; for hard disk access this factor can reach six orders of magnitude. The 16 coherent chapters in this monograph-like tutorial book introduce and survey algorithmic techniques used to achieve high performance on memory hierarchies; emphasis is placed on methods interesting from a theoretical as well as important from a practical point of view.

External-memory Algorithms with Applications in Geographic Information Systems

External-memory Algorithms with Applications in Geographic Information Systems PDF Author: Lars Arge
Publisher:
ISBN:
Category :
Languages : en
Pages : 53

Get Book Here

Book Description


External Memory Algorithms for Geographic Information Systems

External Memory Algorithms for Geographic Information Systems PDF Author: Jan Vahrenhold
Publisher:
ISBN:
Category :
Languages : en
Pages : 165

Get Book Here

Book Description


External Memory Algorithms: Dealing With MASSIVE Data

External Memory Algorithms: Dealing With MASSIVE Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 6

Get Book Here

Book Description
The bottleneck in many applications that process massive amounts of data is the I/O communications between internal memory and external memory. The bottleneck is accentuated as processors get faster and parallel processors are used. Parallel disk arrays are often used to increase the I/O bandwidth. The goal of this proposal is to deepen our understanding of the limits of I/O systems and to construct external memory algorithms that are provably efficient. The three measures of performance are number of I/Os, disk storage space, and CPU time. Even when the data fit entirely in memory, communication can still be the bottleneck, and the related issues of caching become important. Theoretical work involves development and analysis of provably efficient external memory algorithms and cache-efficient algorithms for a variety of important application areas. We address several batched and on-line problems, involving text databases, prefetching and streaming data from parallel disks, and database selectivity estimation. Our experimental validation uses our TPIE programming environment. Plans for the coming year are to address bottleneck issues in parallel disks, text databases, and XML databases.

Algorithms and Data Structures for Massive Datasets

Algorithms and Data Structures for Massive Datasets PDF Author: Dzejla Medjedovic
Publisher: Simon and Schuster
ISBN: 1638356564
Category : Computers
Languages : en
Pages : 302

Get Book Here

Book Description
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting

LEDA-SM: External Memory Algorithms and Data Structures in Theory and Practice

LEDA-SM: External Memory Algorithms and Data Structures in Theory and Practice PDF Author: Andreas Crauser
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


External-memory Algorithms for Processing Line Segments in Geographic Information Systems

External-memory Algorithms for Processing Line Segments in Geographic Information Systems PDF Author: Lars Arge
Publisher:
ISBN:
Category :
Languages : en
Pages : 34

Get Book Here

Book Description