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...
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...
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...
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...
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...
Parallel Computation (Institute of Mathematics & Its Applications Conference Series, New S., #46)
It is becoming widely accepted that parallel computing is the only way to achieve the processing speeds that are required to meet the future needs of computer users. However designing and building larage parallel computers may not be the most difficult task: there are difficult software problems too that require the development of new solution algorithms which are capable of supporting many parallels. The emphasis of this conference was on the applications of parallel processing, on the implemen...
Build, scale, and maintain microservices in Golang with ease. Key Features Create and organize well-structured Go microservices Learn industry best practices and gain insights into Go microservice development tools, patterns, and solutions Cover hands-on Golang examples in each chapter Book DescriptionThis book covers the key benefits and common issues of microservices, helping you understand the problems microservice architecture helps to solve, the issues it usually introduces, and the ways...
Build fast, scalable, and high performing applications with Delphi Key Features Build efficient and concurrent applications in Delphi with focused examples Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications. Delve into parallel programming and memory management to optimize your code Book DescriptionDelphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Appl...
This text is intended for a first course in Numerical Analysis taken by students majoring in mathematics, engineering, computer science, and the sciences. This text emphasizes the mathematical ideas behind the methods and the idea of mixing methods for robustness. The optional use of MATLAB is incorporated throughout the text.
Advanced Python Programming
by Dr. Gabriele Lanaro, Quan Nguyen, and Sakis Kasampalis
Create distributed applications with clever design patterns to solve complex problemsKey FeaturesSet up and run distributed algorithms on a cluster using Dask and PySparkMaster skills to accurately implement concurrency in your codeGain practical experience of Python design patterns with real-world examplesBook DescriptionThis Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about pro...
Parallel Programming in Openmp
by Rohit Chandra, Dave Kohr, Ramesh Menon, Leo Dagum, Dror Maydan, and Jeff McDonald
The rapid and widespread acceptance of shared-memory multiprocessor architectures has created a pressing demand for an efficient way to program these systems. At the same time, developers of technical and scientific applications in industry and in government laboratories find they need to parallelize huge volumes of code in a portable fashion. OpenMP, developed jointly by several parallel computing vendors to address these issues, is an industry-wide standard for programming shared-memory and di...
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.