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This book constitutes the refereed proceedings of the 16th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2016, held in Granada, Spain, in December 2016. The 30 full papers and 22 short papers presented were carefully reviewed and selected from 117 submissions. They cover many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems trying to push beyond the limits of existing technologies, including experimental efforts, innovative systems, and investigations that identify weaknesses in existing parallel processing technology.
This book constitutes the refereed workshop proceedings of the 16th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2016, held in Granada, Spain, in December 2016. The 30 full papers presented were carefully reviewed and selected from 58 submissions. They cover many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems trying to push beyond the limits of existing technologies, including experimental efforts, innovative systems, and investigations that identify weaknesses in existing parallel processing technology.
The needs of future digital data and computer systems are expected to be two to three orders of magnitude larger than for today's systems, to take account of unprecedented amounts of heterogeneous hardware, lines of source code, numbers of users, and volumes of data. Ultrascale computing systems (UCS) are a solution. Envisioned as large-scale complex systems joining parallel and distributed computing systems, which can be located at multiple sites and cooperate to provide the required resources and performance to the users, these technologies will extend individual systems to provide the resources that are very much needed. Based on the research work in the COST Action IC 1305 Network for Sustainable Ultrascale Computing (NESUS) this book presents important results and methods towards achieving sustainable UCS. The authors present a wide range of emerging programming models that facilitate the task of scaling and extracting performance on continuously evolving platforms, while providing resilience and fault-tolerant mechanisms to tackle the increasing probability of failures throughout the entire software stack. These methods are needed to achieve scale handling, better programmability and adaptation to rapidly changing underlying computing architecture, data centric programming models, resilience, and energy-efficiency.
Recent advances in storage technologies and high performance interconnects have made possible in the last years to build, more and more potent storage systems that serve thousands of nodes. Additionally, the hierarchical organization of current Petascale systems and of the envisioned Exascale platforms contributes to an increase of the I/O subsystem latency. In this dissertation we present a novel generic parallel I/O architecture for clusters and supercomputers. Our design is aimed at large-scale parallel architectures with thousands of compute nodes. Besides acting as middleware for existing parallel file systems, our architecture provides on-line virtualization of storage resources. Another objective of this thesis is to factor out the common parallel I/O functionality from clusters and supercomputers in generic modules in order to facilitate porting of scientific applications across these platforms.
Parallel computation on cluster architectures has become the most common solution for developing high-performance scientific applications. Message Passing Interface (MPI) is the message-passing library most widely used to provide communications in clusters. Along the I/O phase, the processes frequently access a common data set by issuing a large number of small non-contiguous I/O requests, which might create bottlenecks in the I/O subsystem. These bottlenecks are still higher in commodity clusters, where commercial networks are usually installed. Scalability is also an important issue in cluster systems when many processors are used, which may cause network saturation and still higher latencies. As communication-intensive parallel applications spend a significant amount of their total execution time exchanging data between processes, the former problems may lead to poor performance not only in the I/O subsystem, but also in communication phase. Therefore, we can conclude that it is necessary to develop techniques for improving the performance of both communication and I/O subsystems.
In the last years, wireless sensor networks (WSNs) are acquiring more importance as a promising technology based on tiny devices called sensor nodes or motes able to monitor a wide range of physical phenomenon through sensors. The severe hardware restrictions of sensor nodes in relation to computation, communication and specifically, energy, have posed new technical and conceptual challenges. In particular, research is moving towards heterogeneous networks that will contain different devices running custom WSN operating systems. Operating systems specifically designed for sensor nodes are intended to efficiently manage the hardware resources and facilitate the programming. Nevertheless, they often lack the generality and the high-level abstractions expected at this abstraction layer. The book address the problem of designing and implementing a generic sensor node-centric architecture distinguishing clearly the different abstraction levels in a sensor node. Programming language extensions have to be also specified on top of the architecture, in order to write portable applications. In this way, architecture deals with the problem of heterogeneity and portability.
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