Dynamic Data Partitioning and Virtual Machine Mapping: Efficient Data Intensive Computation

2013 ◽  
Author(s):  
Kenn Slagter ◽  
Ching-Hsien Hsu ◽  
Yeh-Ching Chung
Keyword(s):  
Virtual Machine ◽  
Data Partitioning ◽  
Dynamic Data ◽  
Data Intensive ◽  
Efficient Data

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.

Efficient data partitioning for the GPU computation of moment functions

2014 ◽  
Vol 74 (1) ◽  
pp. 1994-2004 ◽  
Author(s):  
Manuel Jesús Martín Requena ◽  
Pablo Moscato ◽  
Manuel Ujaldón
Keyword(s):  
Data Partitioning ◽  
Moment Functions ◽  
Efficient Data
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