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.

I wish to welcome all of you to the International Symposium on High Perf- mance Computing 2000 (ISHPC 2000) in the megalopolis of Tokyo. After having two great successes with ISHPC’97 (Fukuoka, November 1997) and ISHPC’99 (Kyoto, May 1999), many people have requested that the symposium would be held in the capital of Japan and we have agreed. I am very pleased to serve as Conference Chair at a time when high p- formance computing (HPC) has a signi?cant in?uence on computer science and technology. In particular, HPC has had and will continue to have a signi?cant - pact on the advanced technologies of the “IT” revolution. The many conferences and symposiums that are held on the subject around the world are an indication of the importance of this area and the interest of the research community. One of the goals of this symposium is to provide a forum for the discussion of all aspects of HPC (from system architecture to real applications) in a more informal and personal fashion. Today we are delighted to have this symposium, which includes excellent invited talks, tutorials and workshops, as well as high quality technical papers.

Distributed Systems Comprehensive textbook resource on distributed systems—integrates foundational topics with advanced topics of contemporary importance within the field Distributed Systems: Theory and Applications is organized around three layers of abstractions: networks, middleware tools, and application framework. It presents data consistency models suited for requirements of innovative distributed shared memory applications. The book also focuses on distributed processing of big data, representation of distributed knowledge and management of distributed intelligence via distributed agents. To aid in understanding how these concepts apply to real-world situations, the work presents a case study on building a P2P Integrated E-Learning system. Downloadable lecture slides are included to help professors and instructors convey key concepts to their students. Additional topics discussed in Distributed Systems: Theory and Applications include: Network issues and high-level communication tools Software tools for implementations of distributed middleware. Data sharing across distributed components through publish and subscribe-based message diffusion, gossip protocol, P2P architecture and distributed shared memory. Consensus, distributed coordination, and advanced middleware for building large distributed applications Distributed data and knowledge management Autonomy in distributed systems, multi-agent architecture Trust in distributed systems, distributed ledger, Blockchain and related technologies. Researchers, industry professionals, and students in the fields of science, technology, and medicine will be able to use Distributed Systems: Theory and Applications as a comprehensive textbook resource for understanding distributed systems, the specifics behind the modern elements which relate to them, and their practical applications.

Cloud computing has created a shift from the use of physical hardware and locally managed software-enabled platforms to that of virtualized cloud-hosted services. Cloud assembles large networks of virtual services, including hardware (CPU, storage, and network) and software resources (databases, message queuing systems, monitoring systems, and load-balancers). As Cloud continues to revolutionize applications in academia, industry, government, and many other fields, the transition to this efficient and flexible platform presents serious challenges at both theoretical and practical levels—ones that will often require new approaches and practices in all areas. Comprehensive and timely, Cloud Computing: Methodology, Systems, and Applications summarizes progress in state-of-the-art research and offers step-by-step instruction on how to implement it. Summarizes Cloud Developments, Identifies Research Challenges, and Outlines Future Directions Ideal for a broad audience that includes researchers, engineers, IT professionals, and graduate students, this book is designed in three sections: Fundamentals of Cloud Computing: Concept, Methodology, and Overview Cloud Computing Functionalities and Provisioning Case Studies, Applications, and Future Directions It addresses the obvious technical aspects of using Cloud but goes beyond, exploring the cultural/social and regulatory/legal challenges that are quickly coming to the forefront of discussion. Properly applied as part of an overall IT strategy, Cloud can help small and medium business enterprises (SMEs) and governments in optimizing expenditure on application-hosting infrastructure. This material outlines a strategy for using Cloud to exploit opportunities in areas including, but not limited to, government, research, business, high-performance computing, web hosting, social networking, and multimedia. With contributions from a host of internationally recognized researchers, this reference delves into everything from necessary changes in users’ initial mindset to actual physical requirements for the successful integration of Cloud into existing in-house infrastructure. Using case studies throughout to reinforce concepts, this book also addresses recent advances and future directions in methodologies, taxonomies, IaaS/SaaS, data management and processing, programming models, and applications.

There are many applications that require parallel and distributed processing to allow complicated engineering, business and research problems to be solved in a reasonable time. Parallel and distributed processing is able to improve company profit, lower costs of design, production, and deployment of new technologies, and create better business environments. The major lesson learned by car and aircraft engineers, drug manufacturers, genome researchers and other specialist is that a computer system is a very powerful tool that is able to help them solving even more complicated problems. That has led computing specialists to new computer system architecture and exploiting parallel computers, clusters of clusters, and distributed systems in the form of grids. There are also institutions that do not have so complicated problems but would like to improve profit, lower costs of design and production by using parallel and distributed processing on clusters. In general to achieve these goals, parallel and distributed processing must become the computing mainstream. This implies a need for new architectures of parallel and distributed systems, new system management facilities, and new application algorithms. This also implies a need for better understanding of grids and clusters, and in particular their operating systems, scheduling algorithms, load balancing, heterogeneity, transparency, application deployment, which is of the most critical importance for their development and taking them by industry and business.