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Distributed Shared Memory
The papers present in this text survey both distributed shared memory (DSM) efforts and commercial DSM systems. The book discusses relevant issues that make the concept of DSM one of the most attractive approaches for building large-scale, high-performance multiprocessor systems. The authors provide a general introduction to the DSM field as well as a broad survey of the basic DSM concepts, mechanisms, design issues, and systems. The book concentrates on basic DSM algorithms, their enhancements, and their performance evaluation. In addition, it details implementations that employ DSM solutions at the software and the hardware level. This guide is a research and development reference that provides state-of-the art information that will be useful to architects, designers, and programmers of DSM systems.
Event-Based Programming
This book shows how to develop software based on parts that interact primarily through an event mechanism. The book demonstrates the use of events in all sorts of situations to solve recurring development problems without incurring coupling. A novel form of software diagram is introduced, called Signal Wiring Diagram. These diagrams are similar to the circuit diagrams used by hardware designers. A series of case studies concludes the book, bringing all the next concepts introduced together. Source code is provided in both C# and VB.NET
Distributed Computing
* Comprehensive introduction to the fundamental results in the mathematical foundations of distributed computing * Accompanied by supporting material, such as lecture notes and solutions for selected exercises * Each chapter ends with bibliographical notes and a set of exercises * Covers the fundamental models, issues and techniques, and features some of the more advanced topics
Fourth International Conference on High Performance Computing
This text on high-performance computing includes coverage of the topics: applications; I/O and compilers; scientific computing; data and file management; interconnection networks; compilers; image and signal processing; distributed systems; algorithms; architecture; and parallel programming.
Proceedings
None
Heterogeneous Computing Architectures
Heterogeneous Computing Architectures: Challenges and Vision provides an updated vision of the state-of-the-art of heterogeneous computing systems, covering all the aspects related to their design: from the architecture and programming models to hardware/software integration and orchestration to real-time and security requirements. The transitions from multicore processors, GPU computing, and Cloud computing are not separate trends, but aspects of a single trend-mainstream; computers from desktop to smartphones are being permanently transformed into heterogeneous supercomputer clusters. The reader will get an organic perspective of modern heterogeneous systems and their future evolution.
Networks of the Future
With the ubiquitous diffusion of the IoT, Cloud Computing, 5G and other evolved wireless technologies into our daily lives, the world will see the Internet of the future expand ever more quickly. Driving the progress of communications and connectivity are mobile and wireless technologies, including traditional WLANs technologies and low, ultra-power, short and long-range technologies. These technologies facilitate the communication among the growing number of connected devices, leading to the generation of huge volumes of data. Processing and analysis of such "big data" brings about many opportunities, as well as many challenges, such as those relating to efficient power consumptions, securi...
Proceedings of the 17th Annual International Symposium on High Performance Computing Systems and Applications and the OSCAR Symposium
The 17th annual International Symposium on High Performance Systems and Applications (HPCS 2003) and the first OSCAR Symposium were held in Sherbrooke, Quebec Canada, May 11-14, 2003. The proceedings cover various areas of High Performance Computing, from specific scientific applications to computer architecture. OSCAR is an Open Source clustering software suite for building, maintaining, and using high performance clusters.
