Parallel And Distributed Processing And Applications

Here, authors from academia and practice provide practitioners, scientists and graduates with basic methods and paradigms, as well as important issues and trends across the spectrum of parallel and distributed processing. In particular, they cover such fundamental topics as efficient parallel algorithms, languages for parallel processing, parallel operating systems, architecture of parallel and distributed systems, management of resources, tools for parallel computing, parallel database systems and multimedia object servers, as well as the relevant networking aspects. A chapter is dedicated to each of parallel and distributed scientific computing, high-performance computing in molecular sciences, and multimedia applications for parallel and distributed systems.

This book constitutes the proceedings of the 21st International Conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2020, which took place in Shenzhen, China, during December 28-30, 2020. The 34 full papers included in this volume were carefully reviewed and selected from 109 submissions. They deal with parallel and distributed computing of networking and architectures, software systems and technologies, algorithms and applications, and security and privacy.

The book presents the proceedings of four conferences: The 26th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'20), The 18th International Conference on Scientific Computing (CSC'20); The 17th International Conference on Modeling, Simulation and Visualization Methods (MSV'20); and The 16th International Conference on Grid, Cloud, and Cluster Computing (GCC'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students. Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the research tracks Parallel and Distributed Processing, Scientific Computing, Modeling, Simulation and Visualization, and Grid, Cloud, and Cluster Computing; Features papers from PDPTA’20, CSC’20, MSV’20, and GCC’20.

Collects the Latest Research Involving the Application of Process Algebra to Computing Exploring state-of-the-art applications, Process Algebra for Parallel and Distributed Processing shows how one formal method of reasoning—process algebra—has become a powerful tool for solving design and implementation challenges of concurrent systems. Parallel Programming Divided into three parts, the book begins by parallelizing an algorithm for the Cell Broadband Engine processor of IBM, Sony, and Toshiba. It also develops a runtime environment that can be ported to different parallel platforms and describes the formal model of action systems. Distributed Systems The next part presents a process algebra (mCRL2) that targets distributed applications, looks at how to turn prose descriptions into unambiguous specifications, extends pi-calculus to create a service-oriented mobility abstract machine, and introduces the Channel Ambient Machine for mobile applications. Embedded Systems The final section combines state-based Z with the event-based process algebra CSP in a formal methodology called Circus. It also develops a pair of process algebras (PARS) to address the problem of scheduling in real-time embedded systems and emphasizes the reuse of concurrent artifacts across different hardware platforms. Highlighting recent research work, this volume addresses multicore programming problems and the evolution of the growing body of concurrency-enabled languages. It proposes solutions to the problems of designing and implementing today’s concurrency-constrained multicore processor and cloud architectures.

Welcometotheproceedingsofthe2ndInternationalSymposiumonParalleland Distributed Processing and Applications (ISPA2004) which was held in Hong Kong, China, 13–15 December, 2004. With the advance of computer networks and hardware technology, parallel and distributed processing has become a key technology which plays an imp- tant part in determining future research and development activities in many academic and industrial branches. It provides a means to solve computati- ally intensive problems by improving processing speed. It is also the only - ableapproachtobuildinghighlyreliableandinherentlydistributedapplications. ISPA2004 provided a forum for scientists and engineers in academia and ind- try to exchange and discuss their experiences, new ideas, research results, and applications about all aspects of parallel and distributed computing. There was a very large number of paper submissions (361) from 26 countries and regions, including not only Asia and the Paci?c, but also Europe and North America. All submissions were reviewed by at least three program or technical committee members or external reviewers. It was extremely di?cult to select the presentations for the conference because there were so many excellent and interesting submissions. In order to allocate as many papers as possible and keep the high quality of the conference, we ?nally decided to accept 78 regular papers and 38 short papers for oral technical presentations. We believe that all of these papers and topics not only provide novel ideas, new results, work in progress and state-of-the-art techniques in this ?eld, but also stimulate the future research activities in the area of parallel and distributed computing with applications.

Parallel and distributed computation has been gaining a great lot of attention in the last decades. During this period, the advances attained in computing and communication technologies, and the reduction in the costs of those technolo gies, played a central role in the rapid growth of the interest in the use of parallel and distributed computation in a number of areas of engineering and sciences. Many actual applications have been successfully implemented in various plat forms varying from pure shared-memory to totally distributed models, passing through hybrid approaches such as distributed-shared memory architectures. Parallel and distributed computation differs from dassical sequential compu tation in some of the following major aspects: the number of processing units, independent local dock for each unit, the number of memory units, and the programming model. For representing this diversity, and depending on what level we are looking at the problem, researchers have proposed some models to abstract the main characteristics or parameters (physical components or logical mechanisms) of parallel computers. The problem of establishing a suitable model is to find a reasonable trade-off among simplicity, power of expression and universality. Then, be able to study and analyze more precisely the behavior of parallel applications.