Search results for "Science and Computing with Raspberry Pi"
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Learn Robotics With Raspberry Pi
Matt Timmons-Brown takes you through the process of building your own robot with the Raspberry Pi microcomputer - with no experience necessary! Starting from the ground up, you'll add complexity to your robot with each chapter by adding and tweaking code and components, and also receive advice on which materials you can use to make your builds unique and personal. By the end of the book, you'll know how to apply the knowledge you've gained to build other robots. If you're ready to level up your robotics skills with Raspberry Pi, let Learn Robotics with Raspberry Pi be your guide!
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Computing for Scientists
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition F. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars A. C. Phillips Computing for Scientists R. J. Barlow and A. R. Barnett Computing for Scientists focuses on the principles involved in scientific programming. Topics of importance and interest to scientists are presented in a thoughtful and thought-provoking way, with coverage ranging from high-level object-oriented software to low-level machine-code operations. Taking a problem-solving approach, this book gives the reader an insight into the ways programs are implemented and what actually happens when they run. Throughout, the importance of good programming style is emphasised and illustrated. Two languages, Fortran 90 and C++, are used to provide contrasting examples, and explain how various techniques are used and when they are appropriate or inappropriate. For scientists and engineers needing to write programs of their own or understand those written by others, Computing for Scientists: * Is a carefully written introduction to programming, taking the reader from the basics to a considerable level of sophistication. * Emphasises an understanding of the principles and the development of good programming skills. * Includes optional "starred" sections containing more specialised and advanced material for the more ambitious reader. * Assumes no prior knowledge, and has many examples and exercises with solutions included at the back of the book.
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Software Development
Computational software is the backbone of progress in many fields of science and engineering. As the importance and complexity of this software grows, developers should apply software development best practices systematically. However, exploratory, agile, and numerical codes present unique challenges.Developers must combine cutting-edge expertise from applied mathematics, computer science, high-performance computing and domain-specific knowledge, relying on small, highly specialised research groups and individuals from diverse career levels, to maintain codebases across generations of team members, often working asynchronously across the globe. These conditions demand bespoke development techniques tailored to the research environment.This book presents a collection of best practices and lessons learned from the computational science community, offering critical observations on where mainstream development techniques struggle or fail in this specialised domain, or where mainstream software development technology is widely adopted yet might not be the best fit overall. The author challenges common recommendations for code development and suggests that there is a need to design and implement bespoke software development workflows that deliver research software capable of facilitating new insights in challenging research environments.The discussion remains technically focused, avoiding high-level management theory, career development frameworks, and team dynamics discussions in favour of practical ideas that make day-to-day research code development more efficient, effective, and enjoyable.The book is written specifically for practitioners who develop software as part of computational science research. It addresses techniques, recipes, and principles relevant to PhD students, research software engineers, postdoctoral researchers, and senior academics who mentor and instruct colleagues.
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Advances in Computers
Advances in Computers, Volume 119, presents innovations in computer hardware, software, theory, design, and applications, with this updated volume including new chapters on Fast Execution of RDF Queries Using Apache Hadoop, A Study of DVFS Methodologies for Multicore Systems with Islanding Feature, Effectiveness of State-of-the-art Dynamic Analysis Techniques in Identifying Diverse Android Malware and Future Enhancements, Eyeing the Patterns: Data Visualization Using Doubly-Seriated Color Heatmaps, Eigenvideo for Video Indexing.
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Introduction to HPC with MPI for Data Science
This gentle introduction to High Performance Computing (HPC) for Data Science using the Message Passing Interface (MPI) standard has been designed as a first course for undergraduates on parallel programming on distributed memory models, and requires only basic programming notions.Divided into two parts the first part covers high performance computing using C++ with the Message Passing Interface (MPI) standard followed by a second part providing high-performance data analytics on computer clusters.In the first part, the fundamental notions of blocking versus non-blocking point-to-point communications, global communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up laws are described before addressing parallel sorting and parallel linear algebra on computer clusters. The common ring, torus and hypercube topologies of clusters are then explained and global communication procedures on these topologies are studied. This first part closes with the MapReduce (MR) model of computation well-suited to processing big data using the MPI framework.In the second part, the book focuses on high-performance data analytics. Flat and hierarchical clustering algorithms are introduced for data exploration along with how to program these algorithms on computer clusters, followed by machine learning classification, and an introduction to graph analytics. This part closes with a concise introduction to data core-sets that let big data problems be amenable to tiny data problems.Exercises are included at the end of each chapter in order for students to practice the concepts learned, and a final section contains an overall exam which allows them to evaluate how well they have assimilated the material covered in the book.
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Software Development
Computational software is the backbone of progress in many fields of science and engineering. As the importance and complexity of this software grows, developers should apply software development best practices systematically. However, exploratory, agile, and numerical codes present unique challenges.Developers must combine cutting-edge expertise from applied mathematics, computer science, high-performance computing and domain-specific knowledge, relying on small, highly specialised research groups and individuals from diverse career levels, to maintain codebases across generations of team members, often working asynchronously across the globe. These conditions demand bespoke development techniques tailored to the research environment.This book presents a collection of best practices and lessons learned from the computational science community, offering critical observations on where mainstream development techniques struggle or fail in this specialised domain, or where mainstream software development technology is widely adopted yet might not be the best fit overall. The author challenges common recommendations for code development and suggests that there is a need to design and implement bespoke software development workflows that deliver research software capable of facilitating new insights in challenging research environments.The discussion remains technically focused, avoiding high-level management theory, career development frameworks, and team dynamics discussions in favour of practical ideas that make day-to-day research code development more efficient, effective, and enjoyable.The book is written specifically for practitioners who develop software as part of computational science research. It addresses techniques, recipes, and principles relevant to PhD students, research software engineers, postdoctoral researchers, and senior academics who mentor and instruct colleagues.
R 2,711.00
Microprocessor Theory and Applications with 68000/68020 and Pentium
MICROPROCESSOR THEORY AND APPLICATIONS WITH 68000/68020 AND PENTIUM A SELF-CONTAINED INTRODUCTION TO MICROPROCESSOR THEORY AND APPLICATIONSThis book presents the fundamental concepts of assembly language programming and system design associated with typical microprocessors, such as the Motorola MC68000/68020 and Intel® Pentium®. It begins with an overview of microprocessors—including an explanation of terms, the evolution of the microprocessor, and typical applications—and goes on to systematically cover: Microcomputer architectureMicroprocessor memory organizationMicroprocessor Input/Output (I/O)Microprocessor programming conceptsAssembly language programming with the 6800068000 hardware and interfacingAssembly language programming with the 6802068020 hardware and interfacingAssembly language programming with PentiumPentium hardware and interfacing The author assumes a background in basic digital logic, and all chapters conclude with a Questions and Problems section, with selected answers provided at the back of the book. Microprocessor Theory and Applications with 68000/68020 and Pentium is an ideal textbook for undergraduate- and graduate-level courses in electrical engineering, computer engineering, and computer science. (An instructor’s manual is available upon request.) It is also appropriate for practitioners in microprocessor system design who are looking for simplified explanations and clear examples on the subject. Additionally, the accompanying Website, which contains step-by-step procedures for installing and using Ide 68k21 (68000/68020) and MASM32 / Olly Debugger (Pentium) software, provides valuable simulation results via screen shots.
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