Название: Sequential and Parallel Algorithms and Data Structures: The Basic Toolbox Автор: Peter Sanders, Kurt Mehlhorn
Издательство: Springer
Год: 2019
Страниц: 516
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Every computer scientist and every professional programmer should know about the basic algorithmic toolbox. Authors address the paradigm shift towards the parallel algorithms required to solve modern performance-critical applications. Includes many examples, pictures, informal explanations, exercises, and implementation notes with efficient implementations in languages such as C++ and Java.
This textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems. The authors aim for a balance between simplicity and efficiency, between theory and practice, and between classical results and the forefront of research. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, optimization, collective communication and computation, and load balancing. The authors also discuss important issues such as algorithm engineering, memory hierarchies, algorithm libraries, and certifying algorithms. Moving beyond the sequential algorithms and data structures of the earlier related title, this book takes into account the paradigm shift towards the parallel processing required to solve modern performance-critical applications and how this impacts on the teaching of algorithms.
The consequence is that nowadays every performance-critical application has to be parallelized. Moreover, big data – the explosion of data set sizes in many applications – has produced an enormous demand for algorithms that scale to a large number of processors. This paradigm shift has profound effects on teaching algorithms. Parallel algorithms are no longer a specialized topic reserved for a small percentage of students. Rather, every student needs some exposure to parallel algorithms, and parallel solution paradigms need to be taught early on. As a consequence, parallel algorithms should be integrated tightly and early into algorithms courses.
The book is suitable for undergraduate and graduate students and professionals familiar with programming and basic mathematical language. Most chapters have the same basic structure: the authors discuss a problem as it occurs in a real-life situation, they illustrate the most important applications, and then they introduce simple solutions as informally as possible and as formally as necessary so the reader really understands the issues at hand. As they move to more advanced and optional issues, their approach gradually leads to a more mathematical treatment, including theorems and proofs.
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