Franklin

Big Data and HPC.

Author/Creator:
Grandinetti, L.
Publication:
Amsterdam : IOS Press, Incorporated, 2018.
Format/Description:
Book
1 online resource (338 pages)
Edition:
1st ed.
Series:
Advances in Parallel Computing Ser.
Advances in Parallel Computing Ser. ; v.33
Status/Location:
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Details

Subjects:
Big data-Congresses.
High performance computing-Congresses.
Form/Genre:
Electronic books.
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
Local notes:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Contributor:
Mirtaheri, S. L.
Shahbazian, R.
Other format:
Print version: Grandinetti, L. Big Data and HPC: Ecosystem and Convergence
ISBN:
9781614998822
9781614998815
OCLC:
1057679225