Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation
Abstract
:1. Introduction
2. Initial Concepts
2.1. Computer Cluster
2.2. IPython Parallel Environment
2.3. Algorithms
Surrogate
Algorithm 1 IAAFT 

3. Material and Methods
Transfer Entropy
Algorithm 2 Execute DTE with surrogate 

4. Results and Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Appendix A.1. Source Code
Parallel Strategy  Revision Hash 

Data Parallelism  f85aac7e8ff46c74b8e758211197dfc8b069571d 
Task Parallelism  e97a687c51cfad61ac097fb5fc26b029967615da 
Appendix A.2. Cluster Configuration
Node  Processor (cores)  RAM (speed)  Main Storage Size (model)  Ethernet 

host  i52500 CPU @ 3.30GHz  4 + 4 GiB (1333MHz)  2TB WDC WD20EARX00P  Gigabit 
lps01  i74770 CPU @ 3.40GHz (8)  8 + 8 GiB (1333MHz)  1TB ST1000DM0031CH1  Gigabit 
lps02  i73770 CPU @ 3.40GHz (8)  8 GiB (1333MHz)  60GB KINGSTON SV300S3  Gigabit 
lps04  i74820K CPU @ 3.70GHz (8)  8 GiB (1333MHz)  2TB ST2000DM0011CH1  Gigabit 
lps05  i74820K CPU @ 3.70GHz (8)  8 GiB (1333MHz)  1863GiB ST2000DM0011CH1  Gigabit 
lps06  i74820K CPU @ 3.70GHz (8)  8 + 8 GiB (1333MHz)  60GB KINGSTON SV300S3  Gigabit 
lps08  i7 950 CPU @ 3.07GHz (8)  4 + 4 + 4 GiB (1066MHz)  2TB ST32000542AS  Gigabit 
lps09  i74790 CPU @ 3.60GHz (8)  8 + 8 GiB (1600MHz)  256GB SMART SSD SZ9STE  Gigabit 
lps10  i74790 CPU @ 3.60GHz (8)  8 + 8 GiB (1600MHz)  256GB SMART SSD SZ9STE  Gigabit 
lps11  i74790 CPU @ 3.60GHz (8)  8 + 8 GiB (1600MHz)  256GB SMART SSD SZ9STE  Gigabit 
lps12  i74790 CPU @ 3.60GHz (8)  8 + 8 GiB (1600MHz)  256GB SMART SSD SZ9STE  Gigabit 
Node  Operating System (updated at)  Numpy  IPython  pyfftw  Linux Kernel 

host  Fedora 24 Workstation (17082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps01  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps02  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps04  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps05  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps06  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps08  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps09  Fedora 24 Workstation (20160816)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps10  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps11  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
lps12  Fedora 24 Server (16082016)  1.11.0  3.2.1  0.10.3.dev0+e827cb5  4.6.6300.fc24.x86_64 
Appendix A.3. Dataset
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Dourado, J.R.; Oliveira Júnior, J.N.d.; Maciel, C.D. Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation. Algorithms 2019, 12, 190. https://doi.org/10.3390/a12090190
Dourado JR, Oliveira Júnior JNd, Maciel CD. Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation. Algorithms. 2019; 12(9):190. https://doi.org/10.3390/a12090190
Chicago/Turabian StyleDourado, Jonas R., Jordão Natal de Oliveira Júnior, and Carlos D. Maciel. 2019. "Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation" Algorithms 12, no. 9: 190. https://doi.org/10.3390/a12090190