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Advances in Computers
This book constitutes the refereed proceedings of the Second International Symposium on Parallel and Distributed Processing and Applications, ISPA 2004, held in Hong Kong, China in December 2004. The 78 revised full papers and 38 revised short papers presented were carefully reviewed and selected from 361 submissions. The papers are organized in topical sections on parallel algorithms and systems, data mining and management, distributed algorithms and systems, fault tolerance protocols and systems, sensor networks and protocols, cluster systems, grid applications and systems, peer-to-peer and ad hoc networking, grid scheduling and algorithms, data replication and caching, software engineering and testing, grid protocols, context-aware and mobile computing, distributed routing and switching protocols, cluster resource scheduling and algorithms, security, high performance processing, networking and protocols, artificial intelligence systems, hardware architecture and implementations, high performance computing architecture, and distributed systems architecture.
This book constitutes the refereed proceedings of the 5th International Conference on Parallel and Distributed Computing, Applications and Technologies; PDCAT 2004, held in Singapore in December 2004. The 173 papers presented were carefully reviewed and selected from 242 submissions. The papers focus on parallel and distributed computing from the perspectives of algorithms, networking and architecture, software systems and technologies, and applications. Besides classical topics from high performance computing, major recent developments are addressed, such as molecular computing, date mining, knowledge discovery, optical networks, secure computing and communications, wireless networks, mobile computing, component-based systems, Internet computing, and Web Technologies.
This three-volume work presents a compendium of current and seminal papers on parallel/distributed processing offered at the 22nd International Conference on Parallel Processing, held August 16-20, 1993 in Chicago, Illinois. Topics include processor architectures; mapping algorithms to parallel systems, performance evaluations; fault diagnosis, recovery, and tolerance; cube networks; portable software; synchronization; compilers; hypercube computing; and image processing and graphics. Computer professionals in parallel processing, distributed systems, and software engineering will find this book essential to their complete computer reference library.
This book constitutes the refereed proceedings of the 6th International Workshop on Advanced Parallel Processing Technologies, APPT 2005, held in Hong Kong, China in September 2005. The 55 revised full papers presented were carefully reviewed and selected from over 220 submissions. All current aspects in parallel and distributed computing are addressed ranging from hardware and software issues to algorithmic aspects and advanced applications. The papers are organized in topical sections on architecture, algorithm and theory, system and software, grid computing, networking, and applied technologies.
The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing.
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world’s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how sub...
High-Performance Embedded Computing, Second Edition, combines leading-edge research with practical guidance in a variety of embedded computing topics, including real-time systems, computer architecture, and low-power design. Author Marilyn Wolf presents a comprehensive survey of the state of the art, and guides you to achieve high levels of performance from the embedded systems that bring these technologies together. The book covers CPU design, operating systems, multiprocessor programs and architectures, and much more. Embedded computing is a key component of cyber-physical systems, which combine physical devices with computational resources for control and communication. This revised editi...
After publishing data on the Internet, the data publisher loses control over it. However, there are several situations where it is desirable to revoke published information. To support this, the European Commission has elaborated the General Data Protection Regulation (GDPR). In particular, this regulation requires that controllers must delete data on user's demand. However, the data might already have been copied by third parties. Therefore, Article 17 of the GDPR includes the regulation that a controller must also inform all affected third parties about revocation requests. Hence, the controllers would need to track every access, which is hard to achieve. This technical infeasibility is a gap between the legislation and the current technical possibilities. To close it, we provide a distributed and decentralized Internet-wide data revocation service (DRS), which is based on the combination of the technical mechanisms and the obligation to follow the legal regulations. With the DRS, the user can notify automatically and simultaneously all affected controllers about her revocation request. Thus, we implicitly provide the notification of third parties about the user's request.
This three-volume work presents a compendium of current and seminal papers on parallel/distributed processing offered at the 22nd International Conference on Parallel Processing, held August 16-20, 1993 in Chicago, Illinois. Topics include processor architectures; mapping algorithms to parallel systems, performance evaluations; fault diagnosis, recovery, and tolerance; cube networks; portable software; synchronization; compilers; hypercube computing; and image processing and graphics. Computer professionals in parallel processing, distributed systems, and software engineering will find this book essential to their complete computer reference library.