Big Data and HPC : Ecosystem and Convergence.

Intro -- Title Page -- Preface -- Contents -- State of the Art and Future Scenarios -- Runtime System Architecture for Dynamic Adaptive Execution -- High Performance Computing and Big Data Convergence: A Technical Review -- Challenges in HPC Evaluation: Towards a Methodology for Scientific Application Requirements -- Scaling Big Data Neuroscience: From Interactive Analytics to HPC Platforms -- Big Data Challenges -- CBIR on Big Data by Use of Deep Learning -- APPGRIT: A Parallel Pipeline for Graph Representation in Text Mining -- Introduction and Patent Analysis of Signal Processing for Big Data -- Analysis and Design of IoT Based Physical Location Monitoring System -- Autonomous Task Scheduling for Fast Big Data Processing -- Adaptive Resource Management for Distributed Data Analytics -- HPC Challenges -- High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication -- Final Parallel and Distributed Computing Assignment for Master Students: Description of the Properties and Parallel Structure of Algorithms -- Parallel Motion Estimation Based on GPU and Combined GPU-CPU -- GPU-Based Iterative Hill Climbing Algorithm to Solve Symmetric Traveling Salesman Problem -- Reliability-Aware Voltage Scaling of Multicore Processors in Dark Silicon Era -- Time Collection: An Abstraction for Shared Objects in Parallel Programming -- Parallel and Distributed Analysis of Microarray Data -- Extracting Distributed Architecture from Source Code Using an Evolutionary Approach -- An Architectural Approach to Grid Provisioning -- Subject Index -- Author Index.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.