Download Free Towards More Scalable Mutual Exclusion For Multicore Architectures Book in PDF and EPUB Free Download. You can read online Towards More Scalable Mutual Exclusion For Multicore Architectures and write the review.

The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Although multicore is now a mainstream architecture, there are few textbooks that cover parallel multicore architectures. Filling this gap, Fundamentals of Parallel Multicore Architecture provides all the material for a graduate or senior undergraduate course that focuses on the architecture of multicore processors. The book is also useful as a ref
Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture. - A practical guide to the essentials of the Intel Xeon Phi coprocessor - Presents best practices for portable, high-performance computing and a familiar and proven threaded, scalar-vector programming model - Includes simple but informative code examples that explain the unique aspects of this new highly parallel and high performance computational product - Covers wide vectors, many cores, many threads and high bandwidth cache/memory architecture
Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the
The saturation of design complexity and clock frequencies for single-core processors has resulted in the emergence of multicore architectures as an alternative design paradigm. Nowadays, multicore/multithreaded computing systems are not only a de-facto standard for high-end applications, they are also gaining popularity in the field of embedded computing. The start of the multicore era has altered the concepts relating to almost all of the areas of computer architecture design, including core design, memory management, thread scheduling, application support, inter-processor communication, debugging, and power management. This book gives readers a holistic overview of the field and guides them to further avenues of research by covering the state of the art in this area. It includes contributions from industry as well as academia.
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 much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years.
A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.
This book presents new concepts, techniques and promising programming models for designing software for chips with "many" (hundreds to thousands) processor cores. Given the scale of parallelism inherent to these chips, software designers face new challenges in terms of operating systems, middleware and applications. This will serve as an invaluable, single-source reference to the state-of-the-art in programming many-core chips. Coverage includes many-core architectures, operating systems, middleware, and programming models.
This book constitutes the refereed proceedings of the 16th International Euro-Par Conference held in Ischia, Italy, in August/September 2010. The 90 revised full papers presented were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load-balancing; high performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance networks; and mobile and ubiquitous computing.