Task-Parallel FP-Growth on Cluster Computers

Author(s):  
Gülistan Özdemir Özdogan ◽  
Osman Abul
2019 ◽  
Vol 44 (4) ◽  
pp. 19-19 ◽  
Author(s):  
Joshua Hooker ◽  
Peter Aldous ◽  
Eric Mercer ◽  
Benjamin Ogles ◽  
Kyle Storey ◽  
...  

Author(s):  
Jing Chen ◽  
Pirah Noor Soomro ◽  
Mustafa Abduljabbar ◽  
Madhavan Manivannan ◽  
Miquel Pericas

2003 ◽  
Vol 7 (4) ◽  
pp. 370-374
Author(s):  
Ckeng Zhou ◽  
Song-Nian Yu
Keyword(s):  

2013 ◽  
Vol 21 (3-4) ◽  
pp. 123-136 ◽  
Author(s):  
Stephen L. Olivier ◽  
Bronis R. de Supinski ◽  
Martin Schulz ◽  
Jan F. Prins

Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, andwork time inflation– additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications. Increased data access latency can cause significant work time inflation in NUMA systems. Our locality framework for task parallel OpenMP programs mitigates this cause of work time inflation. Our extensions to the Qthreads library demonstrate that locality-aware scheduling can improve performance up to 3X compared to the Intel OpenMP task scheduler.


PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0226861
Author(s):  
Timothy Haas

Models of political-ecological systems can inform policies for managing ecosystems that contain endangered species. To increase the credibility of these models, massive computation is needed to statistically estimate the model’s parameters, compute confidence intervals for these parameters, determine the model’s prediction error rate, and assess its sensitivity to parameter misspecification. To meet this statistical and computational challenge, this article delivers statistical algorithms and a method for constructing ecosystem management plans that are coded as distributed computing applications. These applications can run on cluster computers, the cloud, or a collection of in-house workstations. This downloadable code is used to address the challenge of conserving the East African cheetah (Acinonyx jubatus). This demonstration means that the new standard of credibility that any political-ecological model needs to meet is the one given herein.


Author(s):  
Jan Ciesko ◽  
Sergi Mateo ◽  
Xavier Teruel ◽  
Xavier Martorell ◽  
Eduard Ayguadé ◽  
...  
Keyword(s):  

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