What if you woke up to a new life every day? A collision of universes leaves Abby living two lives at once - and sharing them with her own double. Two worlds. Two guys. Two selves. How will she stay in control?

Two women. Two worlds. One goal: to stay alive. All Fara wants is to earn enough tips to pay the bills, somehow learn to stand up for herself, and eat a good cheeseburger. What she gets is a federal agent who is convinced she is hiding a dangerous device in her tiny apartment; and a new and unexplainable ability that she really could do without. All Blu wants is to restore democracy to her world, preferably without dying in the process. What she gets is the unwanted attention of two of the most lethal leaders of Jurisdiction; one who wants nothing more than to kill her, and the other...well...it's complicated. Neither woman had 'run for my life' on their to-do list, but you don't always get what you want.

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

Insights into the intelligence throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and under our skin. Is there a way to understand the materials that surround us not as passive objects, but as other intelligences interacting with our own? In Parallel Minds, expert in materials science and nanotechnology Laura Tripaldi delivers not only detailed insights into the properties and emergent behaviors of matter as revealed by state-of-the-art chemistry, synthetic biology, and nanotech, but also a rich philosophical reflection that crosses the frontier between nature and culture, where the most cutting-edge scientific syntheses resonate with ancient myth. The result is a technomaterial bestiary full of unexpected encounters with “strange minds”—from cobwebs to kevlar and carbon fibre, from centaurs to amoebas to arachnids, from polycephalic slime to resonating plasmons, from viruses to golems. Parallel Minds reveals the intelligence at large throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and even under our skin. Full of lateral ideas and unexpected images, Tripaldi’s book imbues the study and synthesis of materials with a new urgency. For not only do the materials that surround us participate actively in the construction of the world in which we live, but harnessing their ability to interact intelligently with their environment could be the key to the future of our species.

It’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets, including three chapters on using R and Hadoop together. You’ll learn the basics of Snow, Multicore, Parallel, Segue, RHIPE, and Hadoop Streaming, including how to find them, how to use them, when they work well, and when they don’t. With these packages, you can overcome R’s single-threaded nature by spreading work across multiple CPUs, or offloading work to multiple machines to address R’s memory barrier. Snow: works well in a traditional cluster environment Multicore: popular for multiprocessor and multicore computers Parallel: part of the upcoming R 2.14.0 release R+Hadoop: provides low-level access to a popular form of cluster computing RHIPE: uses Hadoop’s power with R’s language and interactive shell Segue: lets you use Elastic MapReduce as a backend for lapply-style operations

In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.

Mathematics of Computing -- Parallelism.