High Performance Computing


Book Description

This book constitutes revised selected papers from 7 workshops that were held in conjunction with the ISC High Performance 2016 conference in Frankfurt, Germany, in June 2016. The 45 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They stem from the following workshops: Workshop on Exascale Multi/Many Core Computing Systems, E-MuCoCoS; Second International Workshop on Communication Architectures at Extreme Scale, ExaComm; HPC I/O in the Data Center Workshop, HPC-IODC; International Workshop on OpenPOWER for HPC, IWOPH; Workshop on the Application Performance on Intel Xeon Phi – Being Prepared for KNL and Beyond, IXPUG; Workshop on Performance and Scalability of Storage Systems, WOPSSS; and International Workshop on Performance Portable Programming Models for Accelerators, P3MA.




High Performance Computing


Book Description

This book constitutes the refereed proceedings of the 5th International Symposium on High-Performance Computing, ISHPC 2003, held in Tokyo-Odaiba, Japan in October 2003. The 23 revised full papers and 16 short papers presented together with 4 invited papers and 7 refereed papers accepted for a concurrently held workshop on OpenMP (WOMPEI 2003) were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on architecture, software, applications, and ITBL.




Advanced Computer Architecture


Book Description

This book constitutes the refereed proceedings of the 11th Annual Conference on Advanced Computer Architecture, ACA 2016, held in Weihai, China, in August 2016. The 17 revised full papers presented were carefully reviewed and selected from 89 submissions. The papers address issues such as processors and circuits; high performance computing; GPUs and accelerators; cloud and data centers; energy and reliability; intelligence computing and mobile computing.




High Performance Computing – HiPC 2005


Book Description

This book constitutes the refereed proceedings of the 12th International Conference on High-Performance Computing, HiPC 2005, held in Goa, India in December 2005. The 50 revised full papers presented were carefully reviewed and selected from 362 submissions. After the keynote section and the presentation of the 2 awarded best contributions the papers are organized in topical sections on algorithms, applications, architecture, systems software, communication networks, and systems and networks.




High Performance Computing - HiPC 2002


Book Description

This book constitutes the refereed proceedings of the 9th International Conference on High Performance Computing, HiPC 2002, held in Bangalore, India in December 2002. The 57 revised full contributed papers and 9 invited papers presented together with various keynote abstracts were carefully reviewed and selected from 145 submissions. The papers are organized in topical sections on algorithms, architecture, systems software, networks, mobile computing and databases, applications, scientific computation, embedded systems, and biocomputing.




Job Scheduling Strategies for Parallel Processing


Book Description

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2021, held as a virtual event in May 2021 (due to the Covid-19 pandemic). The 10 revised full papers presented were carefully reviewed and selected from 17 submissions. In addition to this, one keynote paper was included in the workshop. The volume contains two sections: Open Scheduling Problems and Proposals and Technical Papers. The papers cover such topics as parallel computing, distributed systems, workload modeling, performance optimization, and others.




OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity


Book Description

This book constitutes the proceedings of the 5th OpenSHMEM Workshop, held in Baltimore, MD, USA, in August 2018. The 14 full papers presented in this book were carefully reviewed and selected for inclusion in this volume. The papers discuss a variety of ideas for extending the OpenSHMEM specification and discuss a variety of concepts, including interesting use of OpenSHMEM in HOOVER – a distributed, flexible, and scalable streaming graph processor and scaling OpenSHMEM to handle massively parallel processor arrays. The papers are organized in the following topical sections: OpenSHMEM library extensions and implementations; OpenSHMEM use and applications; and OpenSHMEM simulators, tools, and benchmarks.




Handbook on Data Centers


Book Description

This handbook offers a comprehensive review of the state-of-the-art research achievements in the field of data centers. Contributions from international, leading researchers and scholars offer topics in cloud computing, virtualization in data centers, energy efficient data centers, and next generation data center architecture. It also comprises current research trends in emerging areas, such as data security, data protection management, and network resource management in data centers. Specific attention is devoted to industry needs associated with the challenges faced by data centers, such as various power, cooling, floor space, and associated environmental health and safety issues, while still working to support growth without disrupting quality of service. The contributions cut across various IT data technology domains as a single source to discuss the interdependencies that need to be supported to enable a virtualized, next-generation, energy efficient, economical, and environmentally friendly data center. This book appeals to a broad spectrum of readers, including server, storage, networking, database, and applications analysts, administrators, and architects. It is intended for those seeking to gain a stronger grasp on data center networks: the fundamental protocol used by the applications and the network, the typical network technologies, and their design aspects. The Handbook of Data Centers is a leading reference on design and implementation for planning, implementing, and operating data center networks.




Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning, volume II


Book Description

Towards the long-standing dream of artificial intelligence, two solution paths have been paved: (i) neuroscience-driven neuromorphic computing; (ii) computer science-driven machine learning. The former targets at harnessing neuroscience to obtain insights for brain-like processing, by studying the detailed implementation of neural dynamics, circuits, coding and learning. Although our understanding of how the brain works is still very limited, this bio-plausible way offers an appealing promise for future general intelligence. In contrast, the latter aims at solving practical tasks typically formulated as a cost function with high accuracy, by eschewing most neuroscience details in favor of brute force optimization and feeding a large volume of data. With the help of big data (e.g. ImageNet), high-performance processors (e.g. GPU, TPU), effective training algorithms (e.g. artificial neural networks with gradient descent training), and easy-to-use design tools (e.g. Pytorch, Tensorflow), machine learning has achieved superior performance in a broad spectrum of scenarios. Although acclaimed for the biological plausibility and the low power advantage (benefit from the spike signals and event-driven processing), there are ongoing debates and skepticisms about neuromorphic computing since it usually performs worse than machine learning in practical tasks especially in terms of the accuracy.