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"Parallel processing"
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Parallel programming with co-arrays
This book describes the coarray parallel programming model that will be part of the next standard version of the Fortran language. It provides a practical guide for Fortran programmers who want to start writing parallel applications using coarrays as soon as the compilers become commercially available. The authors present the technical specification of the coarray model in enough detail for programmers to write standard-conforming code. They also offer a large number of examples of parallel algorithms written in the coarray model and include exercises with solutions. A supplementary website offers Fortran code samples for download-- Provided by publisher.
Book
Cyber security in parallel and distributed computing : concepts, techniques, applications and case studies
The book contains several new concepts, techniques, applications and case studies for cyber securities in parallel and distributed computing The main objective of this book is to explore the concept of cybersecurity in parallel and distributed computing along with recent research developments in the field.
eBook
You That Read Wrong Again! A Transposed-Word Effect in Grammaticality Judgments
We report a novel transposed-word effect in speeded grammaticality judgments made about five-word sequences. The critical ungrammatical test sequences were formed by transposing two adjacent words from either a grammatical base sequence (e.g., “The white cat was big” became “The white was cat big”) or an ungrammatical base sequence (e.g., “The white cat was slowly” became “The white was cat slowly”). These were intermixed with an equal number of correct sentences for the purpose of the grammaticality judgment task. In a laboratory experiment (N = 57) and an online experiment (N = 94), we found that ungrammatical decisions were harder to make when the ungrammatical sequence originated from a grammatically correct base sequence. This provides the first demonstration that the encoding of word order retains a certain amount of uncertainty. We further argue that the novel transposed-word effect reflects parallel processing of words during written sentence comprehension combined with top-down constraints from sentence-level structures.
Journal Article
High performance parallelism pearls : multicore and many-core programming approaches
This book shows how to leverage parallelism on processors and coprocessors with the same programming - illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocessors and Intel Xeon processors or other multicore processors. It includes examples of successful programming efforts, drawn from across industries and domains such as chemistry, engineering, and environmental science. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Dozens of new examples and case studies illustrate \"success stories\" demonstrating not just the features of these powerful systems, but also how to leverage parallelism across these heterogeneous systems. --
eBook
High-Speed Vision and its Applications Toward High-Speed Intelligent Systems
Currently, high-speed vision based on parallel processing exists, and its various applications as high-speed intelligent systems have been proposed and implemented. The basic goal of high-speed vision is to realize vision capabilities and systems that operate at speeds necessary for intelligent systems, in which intelligence operating at the speed inherently required by the application system is achieved. This paper described the vision chip and parallel image processing architectures, presented outlines of system architectures, image-processing algorithms, and related peripheral technologies; described the concepts required to configure high-speed intelligent systems, such as hierarchical parallel distributed architecture, parallel decomposition, orthogonal decomposition, dynamics matching, latency minimization, high-speed 3D shape measurement, active vision, tracking vision, dynamic compensation, and dynamic projection mapping; and discussed a wide range of application systems in a systematic manner.
Journal Article
Multilevel Data Processing Using Parallel Algorithms for Analyzing Big Data in High-Performance Computing
The growing gap between users and the Big Data analytics requires innovative tools that address the challenges faced by big data volume, variety, and velocity. Therefore, it becomes computationally inefficient to analyze such massive volume of data. Moreover, advancements in the field of Big Data application and data science poses additional challenges, where High-Performance Computing solution has become a key issue and has attracted attention in recent years. However, these systems are either memoryless or computational inefficient. Therefore, keeping in view the aforementioned needs, there is a requirement for a system that can efficiently analyze a stream of Big Data within their requirements. Hence, this paper presents a system architecture that enhances the working of traditional MapReduce by incorporating parallel processing algorithm. Moreover, complete four-tier architecture is also proposed that efficiently aggregate the data, eliminate unnecessary data, and analyze the data by the proposed parallel processing algorithm. The proposed system architecture both read and writes operations that enhance the efficiency of the Input/Output operation. To check the efficiency of the proposed algorithms exploited in the proposed system architecture, we have implemented our proposed system using Hadoop and MapReduce. MapReduce is supported by a parallel algorithm that efficiently processes a huge volume of data sets. The system is implemented using MapReduce tool at the top of the Hadoop parallel nodes to generate and process graphs with near real-time. Moreover, the system is evaluated in terms of efficiency by considering the system throughput and processing time. The results show that the proposed system is more scalable and efficient.
Journal Article