Big Data and HPC: Ecosystem and Convergence
1st Edition
Published on 15. August 2018
336 pages
978-1-61499-882-2 (ISBN)
Description
Due to the increasing need to solve complex problems, high-performance computing (HPC) is now one of the most fundamental infrastructures for scientific development in all disciplines, and it has progressed massively in recent years as a result. HPC facilitates the processing of big data, but the tremendous research challenges faced in recent years include: the scalability of computing performance for high velocity, high variety and high volume big data; deep learning with massive-scale datasets; big data programming paradigms on multi-core; GPU and hybrid distributed environments; and unstructured data processing with high-performance computing.
This book presents 19 selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale era, held in Tehran, Iran, in April 2017. The book is divided into 3 sections: State of the Art and Future Scenarios, Big Data Challenges, and HPC Challenges, and will be of interest to all those whose work involves the processing of Big Data and the use of HPC.
This book presents 19 selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale era, held in Tehran, Iran, in April 2017. The book is divided into 3 sections: State of the Art and Future Scenarios, Big Data Challenges, and HPC Challenges, and will be of interest to all those whose work involves the processing of Big Data and the use of HPC.
More details
Series
Language
English
Place of publication
London
Netherlands
Publishing group
IOS Press
Target group
Professional and scholarly
File size
10,52 MB
ISBN-13
978-1-61499-882-2 (9781614998822)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Lucio Grandinetti | Reza Shahbazian | Thomas Sterling
Big Data and HPC: Ecosystem and Convergence
Book
08/2018
1st Edition
IOS Press,US
€120.34
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Content
- 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
