Big data and HPC : ecosystem and convergence / edited by Lucio Grandinetti, Seyedeh Leili Mirtaheri, Reza Shahbazian, Thomas Sterling and Vladimir Voevodin.

Includes bibliographical references and index.

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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 SystemAutonomous 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 EraTime 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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