Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/8097
AuthorsAlessi, F.* 
Massini, A.* 
Basili, R.* 
TitleHigh Performance Parallelization of COMPSYN on a Cluster of Multicore Processors with GPUs
Issue Date2012
Series/Report no./9 (2012)
DOI10.1016/j.procs.2012.04.103
URIhttp://hdl.handle.net/2122/8097
KeywordsGPU
CUDA
synthetic seismogram
Subject Classification04. Solid Earth::04.06. Seismology::04.06.99. General or miscellaneous 
04. Solid Earth::04.06. Seismology::04.06.03. Earthquake source and dynamics 
04. Solid Earth::04.06. Seismology::04.06.04. Ground motion 
04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
AbstractIn this work we propose a high performance parallelization of the software package COMPSYN, devoted to the production of syntethic seismograms, on a cluster of multicore processors with multiple GPUs. To design and implement the proposed high performance version, we started from a na¨ıve parallel version of COMPSYN. The na¨ıve version consists in a simple parallelization on both device side, obtained by exploiting CUDA, and host side, obtained by exploiting the MPI paradigm and OpenMP API. The proposed high performance version implements several practical techniques of CUDA programming and deeply exploits the GPU architecture, thus achieving a much better performance with respect to the na¨ıve version. We compare the performance of the proposed high performance version and that of the na¨ıve one with the performance of the version running on the cluster of multicore processors without invoking the GPUs. We obtain for the high performance GPU version a speedup of 25x over the version running on the cluster of multicore processors without GPUs against the 10x of the na¨ıve version. Regarding the sequential version, we estimate about 380x the speedup of the high performance GPU version against the about 140x of the na¨ıve version.
Appears in Collections:Papers Published / Papers in press

Files in This Item:
File Description SizeFormat 
2012_Alessi_etal_ProcediaComputerScience.pdfmain post-print article140.48 kBAdobe PDFView/Open
Show full item record

Page view(s)

137
Last Week
1
Last month
checked on Jun 25, 2017

Download(s)

20
checked on Jun 25, 2017

Google ScholarTM

Check

Altmetric