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Realtime Analysis of Large-Scale Data
In photon science more and more data are taken. It is not possible anymore to store and process all data offline. In this book, we explore strategies for handling this large amount of data. A neural network as well as techniques from image processing are used to efficiently categorize and select useful data. We also indicate why many sophisticated algorithms cannot be used in this context. In addition, a prototype for data selection is presented, discussed, and benchmarked.
Facing the Multicore-Challenge III
This state-of-the-art survey features topics related to the impact of multicore, manycore, and coprocessor technologies in science and large-scale applications in an interdisciplinary environment. The papers included in this survey cover research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, hardware-aware computing, heterogeneous platforms, manycore technologies, performance tuning, and requirements for large-scale applications. The contributions presented in this volume are an outcome of an inspiring conference conceived and organized by the editors at the University of Applied Sciences (HfT) in Stuttgart, Germany, in September 2012. The 10 revised full papers selected from 21 submissions are presented together with the twelve poster abstracts and focus on combination of new aspects of microprocessor technologies, parallel applications, numerical simulation, and software development; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing and very likely towards exascale computing.
High Performance Computing
This book constitutes the proceedings of the 38th International Conference on High Performance Computing, ISC High Performance 2023, which took place in Hamburg, Germany, in May 2023. The 21 papers presented in this volume were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: Architecture, Networks, and Storage; HPC Algorithms & Applications; Machine Learning, AI, & Quantum Computing; Performance Modeling, Evaluation, & Analysis; and Programming Environments & Systems Software.
Learning Language in Logic
This volume has its origins in the ?rst Learning Language in Logic (LLL) wo- shop which took place on 30 June 1999 in Bled, Slovenia immediately after the Ninth International Workshop on Inductive Logic Programming (ILP’99) and the Sixteenth International Conference on Machine Learning (ICML’99). LLL is a research area lying at the intersection of computational linguistics, machine learning, and computational logic. As such it is of interest to all those working in these three ?elds. I am pleased to say that the workshop attracted subm- sions from both the natural language processing (NLP) community and the ILP community, re?ecting the essentially multi-disciplinary nature of LLL. Eric B...
Euro-Par 2007 Workshops: Parallel Processing
This book constitutes the thoroughly refereed joint post-workshop proceedings of three international events: the International Workshop on Highly Parallel Processing on a Chip, HPPC 2007, the UNICORE Summit 2007, and the Workshop on Virtualization/Xen in High-Performance Cluster and Grid Computing, VHPC 2007, held in Rennes, France, in August 2007 within the scope of Euro-Par 2007, the 13th International Conference on Parallel Computing. The 8 papers of the HHPC 2007 workshop address all aspects of existing and emerging/envisaged multi-core processors with a significant amount of parallelism, especially to considerations on novel paradigms and models and the related architectural and linguis...
Euro-Par 2004 Parallel Processing
This book constitutes the refereed proceedings of the 10th International Conference on Parallel Computing, Euro-Par 2004, held in Pisa, Italy in August/September 2004. The 122 revised papers presented together with 3 invited papers were carefully reviewed and selected from 352 submissions. The papers are organized in topical sections on support tools and environments, performance evaluation, scheduling and load balancing, compilers and high performance, parallel and distributed databases, grid and cluster computing, applications on high performance clusters, parallel computer architecture and ILP, distributed systems and algorithms, parallel programming, numerical algorithms, high performance multimedia, theory and algorithms for parallel computing, routing and communication in interconnection networks, mobile computing, integrated problem solving environments, high performance bioinformatics, and peer-to-peer and Web computing.
Cybersecurity Analytics
Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.
Grid Computing - GRID 2002
The growth of the Internet and the availability of powerful computers and hi- speed networks as low-cost commodity components are changing the way we do computing. These new technologies have enabled the clustering of a wide variety of geographically distributed resources, such as supercomputers, storage systems, data sources, and special devices and services, which can then be used as a uni?ed resource. Furthermore, they have enabled seamless access to and interaction among these distributed resources, services, applications, and data. The new paradigm that has evolved is popularly termed “Grid computing”. Grid computing and the utilization of the global Grid infrastructure have present...
