Parallel Algorithms & Architectures (Lecture Notes in Computer Science, #269)
by Kurt Mehlhorn
Parallel Programming at its best! Discover A Book That Tells You What You Should Do and How! Instead of jumping right into the instructions, this book will provide you first with all the necessary concepts that you need to learn in order to make the learning process a whole lot easier. This way, you're sure not to get lost in confusion once you get to the more complex lessons provided in the latter chapters. Graphs and flowcharts, as well as sample codes, are provided for a more visual approa...
Reactive programming is revolutionary. It makes asynchronous programming cleaner, intuitive, and robust. Discover how to use the RxJS library to write programs in a simpler way, unifying asynchronous mechanisms such as callbacks and promises into a single, powerful construct. Learn to think about your programs as streams of data that you can transform by expressing whatshould happen, instead of having to painstakingly program how it should happen. You'll be able to handle real-world concurrency...
Don't accept the compromise between fast and beautiful: you can have it all. Phoenix creator Chris McCord, Elixir creator Jose Valim, and award-winning author Bruce Tate walk you through building an application that's fast and reliable. At every step, you'll learn from the Phoenix creators not just what to do, but why. Packed with insider insights and completely updated for Phoenix 1.4, this definitive guide will be your constant companion in your journey from Phoenix novice to expert, as you bu...
Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA
by Bhaumik Vaidya
Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPUKey FeaturesExplore examples to leverage the GPU processing power with OpenCV and CUDAEnhance the performance of algorithms on embedded hardware platformsDiscover C++ and Python libraries for GPU accelerationBook DescriptionComputer vision has been revolutionizing a wide range of industries, and OpenCV is the most widely chosen tool for computer...
Professional CUDA C Programming
by John Cheng, Max Grossman, and Ty McKercher
Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes...
Introduction to Parallel Computing (Oxford Texts in Applied and Engineering Mathematics, #9)
by Wesley Petersen and Peter Arbenz
In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to s...
Covers Win32 multithreading techniques that make the Windows NT software faster and more responsive. This book explains how multithreading works, and the fundamentals of the Windows NT Thread Interface, including processes, thread management, creation, termination, and prioritization.
The state-of-the-art in high-performance concurrent computing -- theory and practice.-- Detailed coverage of the growing integration between parallel and distributed computing.-- Advanced approaches for programming distributed, parallel systems -- and adapting traditional sequential software.-- Creating a Parallel Virtual Machine (PVM) from networked, heterogeneous systems.This is the most up-to-date, comprehensive guide to the rapidly changing field of distributed and parallel systems.The book...
Parallel Algorithms (Lecture Notes Series on Computing, #0)
by M. H. Alsuwaiyel
This book is an introduction to the field of parallel algorithms and the underpinning techniques to realize the parallelization. The emphasis is on designing algorithms within the timeless and abstracted context of a high-level programming language. The focus of the presentation is on practical applications of the algorithm design using different models of parallel computation. Each model is illustrated by providing an adequate number of algorithms to solve some problems that quite often arise i...
Hands-On Data Structures and Algorithms with Rust
by Claus Matzinger
Design and implement professional level programs by exploring modern data structures and algorithms in Rust.Key FeaturesUse data structures such as arrays, stacks, trees, lists and graphs with real-world examplesLearn the functional and reactive implementations of the traditional data structuresExplore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner.Book DescriptionRust has come a long way and is now utilized in several contexts. Its...
Parallel and Distributed Computing (Lecture Notes in Computer Science, #3320)
by Kimmeow Liew
The 2004 International Conference on Parallel and Distributed Computing, - plications and Technologies (PDCAT 2004) was the ?fth annual conference, and was held at the Marina Mandarin Hotel, Singapore on December 8-10, 2004. Since the inaugural PDCAT held in Hong Kong in 2000, the conference has - come a major forum for scientists, engineers, and practitioners throughout the world to present the latest research, results, ideas, developments, techniques, and applications in all areas of parallel...
Hands-On GPU Programming with Python and CUDA
by Dr. Brian Tuomanen
Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book.Key FeaturesExpand your background in GPU programming—PyCUDA, scikit-cuda, and NsightEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook DescriptionHands-On GPU Programming with Python and CUDA hits the ground running: you’ll...
Parallel Computing Using the Prefix Problem
by S Lakshmivarahan and S K Dhall
The prefix operation on a set of data is one of the simplest and most useful building blocks in parallel algorithms. This introduction to those aspects of parallel programming and parallel algorithms that relate to the prefix problem emphasizes its use in a broad range of familiar and important problems. The book illustrates how the prefix operation approach to parallel computing leads to fast and efficient solutions to many different kinds of problems. Students, lecturers, and programmers w...
This publication contains papers from the Occam User Group (OUG). The main aim of the OUG is to act as an independent forum for the exchange of ideas, results and information in research and development of projects in the area of parallel systems design and programming using various communicating processes oriented approaches for transputer based machines. The papers collected in this volume cover topics such as: methodology of Occam programming, parallel asynchronous algorithms, control of real...
Learn how to switch from writing serial code to parallel code NVIDIA made it easy and understandable to program the rarely used engine inside a PC with CUDA (Compute Unified Device Architecture). It allows for a significant increase in your computer's performance because it harnesses the power of the GPU. With this book, you'll learn to switch on that hidden power and turbo charge your programs. CUDA specialist Shane Cook discusses the many uses for CUDA, including image and video processing, co...
Personal Expense Tracker (Make It Easy, #6) (Control the Chaos, #4)
by Daisy Publishing
Parallel Computational Technologies (Communications in Computer and Information Science, #753)
This book constitutes refereed proceedings of the 14th International Conference on Parallel Computational Technologies, PCT 2020, held in May 2020. Due to the COVID-19 pandemic the conference was held online.The 22 revised full papers and 2 short papers presented were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections on high performance architectures, tools and technologies; parallel numerical algorithms; supercomputer simulation.