scholarly journals Secure, Efficient Data Transport and Replica Management for High-Performance Data-Intensive Computing

2001 ◽  
Author(s):  
Bill Allcock ◽  
Joe Bester ◽  
John Bresnahan ◽  
Ann Chervenak ◽  
Carl Kesselman ◽  
...  
Keyword(s):  
High Performance ◽  
Performance Data ◽  
Data Transport ◽  
Data Intensive Computing ◽  
Data Intensive ◽  
Replica Management ◽  
Efficient Data

Hardware Technologies for High-Performance Data-Intensive Computing

Computer ◽  
2008 ◽  
Vol 41 (4) ◽  
pp. 60-68 ◽  
Author(s):  
Maya Gokhale ◽  
Jonathan Cohen ◽  
Andy Yoo ◽  
W. Marcus Miller ◽  
Arpith Jacob ◽  
...  
Keyword(s):  
High Performance ◽  
Performance Data ◽  
Data Intensive Computing ◽  
Data Intensive

scholarly journals Infrastructure and Energy Conservation in Big Data Computing: A Survey

2019 ◽  
Vol 2 ◽  
pp. 73-82
Author(s):  
Ewa Niewiadomska-Szynkiewicz ◽  
Michał P. Karpowicz
Keyword(s):  
Big Data ◽  
High Performance ◽  
Physical Sciences ◽  
Communication Management ◽  
Data Intensive ◽  
Efficient Data ◽  
Software Platforms ◽  
Allocation Algorithms ◽  
And Storage ◽  
Big Data Computing

Progress in life, physical sciences and technology depends on efficient data-mining and modern computing technologies. The rapid growth of data-intensive domains requires a continuous development of new solutions for network infrastructure, servers and storage in order to address Big Datarelated problems. Development of software frameworks, include smart calculation, communication management, data decomposition and allocation algorithms is clearly one of the major technological challenges we are faced with. Reduction in energy consumption is another challenge arising in connection with the development of efficient HPC infrastructures. This paper addresses the vital problem of energy-efficient high performance distributed and parallel computing. An overview of recent technologies for Big Data processing is presented. The attention is focused on the most popular middleware and software platforms. Various energy-saving approaches are presented and discussed as well.

scholarly journals Enabling Large-Scale Biomedical Analysis in the Cloud

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Ying-Chih Lin ◽  
Chin-Sheng Yu ◽  
Yen-Jen Lin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Computing System ◽  
Biomedical Data ◽  
Data Intensive Computing ◽  
Biomedical Analysis ◽  
Data Intensive ◽  
Large Scale Data ◽  
Performance Computing ◽  
Scale Data

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable.

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