我要吃瓜

Conference Paper (published)

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Details

Citation

Grelck C, Niewiadomska-Szynkiewicz E, Aldinucci M, Bracciali A & Larsson E (2019) Why High-Performance Modelling and Simulation for Big Data Applications Matters. In: Ko?odziej J & González-Vélez H (eds.) High-Performance Modelling and Simulation for Big Data Applications. Lecture Notes in Computer Science, 11400. ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), Vilnius, Lithuania, 28.03.2019-29.03.2019. Cham, Switzerland: Springer, pp. 1-35. https://doi.org/10.1007/978-3-030-16272-6_1

Abstract
Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned.

Keywords
artificial intelligence; big data; big datum; bioinformatics; cloud computing; computer architecture; computer systems; health informatics; high-performance computing; hpc; MapReduce; processors; sensors; wireless networks; wireless telecommunication systems;

Journal
Target Identification and Validation in Drug Discovery; Methods in Molecular Biology

StatusPublished
Funders
Title of seriesLecture Notes in Computer Science
Number in series11400
Publication date31/12/2019
Publication date online26/03/2019
URL
PublisherSpringer
Place of publicationCham, Switzerland
eISSN1940-6029
ISSN of series0302-9743
ISBN978-3-030-16271-9
eISBN978-3-030-16272-6
ConferenceICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)
Conference locationVilnius, Lithuania
Dates

Files (1)