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User-Centered Agile Method
User-Centered Agile Method

Agile development methods began to emerge around 20 years ago. However, it was not until the early 2000s that they began to be widely used in industry. This growth was often due to the advent of Internet services requiring faster cycles of development in order to heighten the rate at which an ever-greater number of functionalities...

Parallel Programming: for Multicore and Cluster Systems
Parallel Programming: for Multicore and Cluster Systems

Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be...

Advanced Image Processing in Magnetic Resonance Imaging (Signal Processing and Communications)
Advanced Image Processing in Magnetic Resonance Imaging (Signal Processing and Communications)
Magnetic Resonance (MR) imaging produces images of the human tissues in a noninvasive manner, revealing the structure, metabolism, and function of tissues and organs. The impact of this image technique in diagnostic radiology is impressive, due to its versatility and flexibility in joining high-quality anatomical images with functional...
Parallel Algorithms and Cluster Computing: Implementations, Algorithms and Applications
Parallel Algorithms and Cluster Computing: Implementations, Algorithms and Applications
This book presents major advances in high performance computing as well as major advances due to high performance computing. It contains a collection of papers in which results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering are presented. From the science problems to the...
Introduction to Parallel Computing (Oxford Texts in Applied and Engineering Mathematics)
Introduction to Parallel Computing (Oxford Texts in Applied and Engineering Mathematics)
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...
Neural Networks for Electronics Hobbyists: A Non-Technical Project-Based Introduction
Neural Networks for Electronics Hobbyists: A Non-Technical Project-Based Introduction
Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. 

There are no prerequisites here and you won't see a single line of
...
Daniel Arbuckle's Mastering Python
Daniel Arbuckle's Mastering Python

Key Features

  • Covers the latest and advanced concepts of Python such as parallel processing with Python 3.6
  • Explore the Python language from its basic installation and setup to concepts such as reactive programming and microservices
  • Get introduced to the mechanism for rewriting code in a...
An Introduction to Parallel Programming
An Introduction to Parallel Programming

Parallel hardware has been ubiquitous for some time now. It’s difficult to find a laptop, desktop, or server that doesn’t use a multicore processor. Beowulf clusters are nearly as common today as high-powered workstations were during the 1990s, and cloud computing could make distributed-memory systems as accessible as...

Chip Multiprocessor Architecture: Techniques to Improve Throughput and Latency
Chip Multiprocessor Architecture: Techniques to Improve Throughput and Latency
Chip multiprocessors — also called multi-core microprocessors or CMPs for short — are now the only way to build high-performance microprocessors, for a variety of reasons. Large uniprocessors are no longer scaling in performance, because it is only possible to extract a limited amount of parallelism from a typical instruction stream...
Parallel Imaging in Clinical MR Applications (Medical Radiology)
Parallel Imaging in Clinical MR Applications (Medical Radiology)

This book presents the first in-depth introduction to parallel imaging techniques and, in particular, to the application of parallel imaging in clinical MRI. It will provide readers with a broader understanding of the fundamental principles of parallel imaging and of the advantages and disadvantages of specific MR protocols in clinical...

Parallel Scientific Computing and Optimization: Advances and Applications (Springer Optimization and Its Applications)
Parallel Scientific Computing and Optimization: Advances and Applications (Springer Optimization and Its Applications)
This work introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix...
Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA
Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA

Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.

Key Features

  • Get to grips with GPU programming...
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