By taking an algorithm-based approach to the subject, this book helps readers grasp overall concepts rather than getting them bogged down with specific syntax details of a programming language that can become obsolete.
Introduction to Computing and Algorithms prepares students for the world of computing by giving them a solid foundation in the study of computer science - algorithms. By taking an algorithm-based approach to the subject, this book helps readers grasp overall concepts rather than getting them bogged down with specific syntax details of a programming language that can become obsolete. Students work with algorithms from the start and apply these ideas to real problems that computers can help solve. The benefit of this approach is that students will understand the power of computers as problem-solving tools, learn to think like programmers, and gain an appreciation of the computer science discipline.
Introduction to Parallel Computing
Release on 2018-09-27 | by Roman Trobec
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing.
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition.
Release on 1988 | by Sara Baase
Three chapters on modern topics are new to this edition: adversary arguments and selection, dynamic programming, and parallel algorithms.
the design and analysis of algorithms, including an exhaustive array of algorithms and their complexity analyses. Baase emphasizes the development of algorithms through a step-by-step process, rather than merely presenting the end result. Three chapters on modern topics are new to this edition: adversary arguments and selection, dynamic programming, and parallel algorithms.
Handbook of Parallel Computing
Release on 2007-12-20 | by Sanguthevar Rajasekaran
Since parallel computing has found applications in a wide variety of domains , the ideas and techniques illustrated ... T.H. Cormen , C.E. Leiserson , R.L. Rivest , and C. Stein , Introduction to Algorithms , Second edition , MIT Press ...
The ability of parallel computing to process large data sets and handle time-consuming operations has resulted in unprecedented advances in biological and scientific computing, modeling, and simulations. Exploring these recent developments, the Handbook of Parallel Computing: Models, Algorithms, and Applications provides comprehensive coverage on a
Algorithms An Introduction to The Computer Science Artificial Intelligence Used to Solve Human Decisions Advance Technology Optimize Habits Learn Faster Your Improve Life
Release on | by Trustgenics
However this book is very accessible to those with no background in computer science.
Discover How Algorithms Shape & Impact Our World Now you might look at this title and shy away, thinking that a book with "Algorithms" in its title must be just for techies and computer scientists. However this book is very accessible to those with no background in computer science. Decisions Oftentimes Have Optimal Solutions Today, many decisions that could be made by human beings from predicting earthquakes to interpreting languages can now be made by computer algorithms with advanced analytic capabilities. Everyday we make millions of decisions from selecting a life partner, to organizing your closet, to scheduling your life, to having a conversation. However, these decisions may be imperfect due to limited experience, implicit biases, or faulty probabilistic reasoning. Algorithms can better predict human behavior than trained psychologists and with much simpler criteria. Studies continue to show that the algorithms can do a better job than experts in a range of fields. Artificial intelligence is reshaping healthcare, science, engineering and life. The results will make our lives more productive, better organized, and essentially, much happier. Everywhere you look, artificial intelligence is beginning to permeate all types of industries and expectations are that it will continue to grow in the future. Imagine The Possibilities More Accurate Medical Diagnoses Better Military Strategies That Could Save Lives Detect Abnormal Genes In An Unborn Child Predict Changes In Weather and Earthquake Safer Self-Driving Cars That Have Learned Your Personal Preferences Analyze DNA Samples & Identify Potential Medical Risks Smart Homes That Will Anticipate Your Every Needs Predicting Where Cyber Hackers & Online Threats May Occur This is a must read for anyone interested in what our digital future looks like. Join The Future
Guide to Programming and Algorithms Using R
Release on 2013-07-23 | by Özgür Ergül
Aho AV, Hopcroft JE, Ullman JD (1974) The design and analysis of computer algorithms. Addison-Wesley, Reading 2. ... Shackelford RL (1997) Introduction to computing and algorithms. Addison-Wesley, Reading 7. Bentley J (1999) Programming ...
This easy-to-follow textbook provides a student-friendly introduction to programming and algorithms. Emphasis is placed on the threshold concepts that present barriers to learning, including the questions that students are often too embarrassed to ask. The book promotes an active learning style in which a deeper understanding is gained from evaluating, questioning, and discussing the material, and practised in hands-on exercises. Although R is used as the language of choice for all programs, strict assumptions are avoided in the explanations in order for these to remain applicable to other programming languages. Features: provides exercises at the end of each chapter; includes three mini projects in the final chapter; presents a list of titles for further reading at the end of the book; discusses the key aspects of loops, recursions, program and algorithm efficiency and accuracy, sorting, linear systems of equations, and file processing; requires no prior background knowledge in this area.
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.