SOLUTIONS FOR OPTIMIZING THE DATA PARALLEL PREFIX SUM ALGORITHM USING THE COMPUTE UNIFIED DEVICE ARCHITECTURE
Ion Lungu (),
Dana-Mihaela Petroşanu () and
Alexandru Pîrjan ()
Additional contact information
Ion Lungu: Academy of Economic Studies Bucharest
Dana-Mihaela Petroşanu: University Politehnica of Bucharest
Alexandru Pîrjan: Romanian-American University Bucharest
Journal of Information Systems & Operations Management, 2011, vol. 5, issue 2.1, 465-477
Abstract:
In this paper, we analyze solutions for optimizing the data parallel prefix sum function using the Compute Unified Device Architecture (CUDA) that provides a viable solution for accelerating a broad class of applications. The parallel prefix sum function is an essential building block for many data mining algorithms, and therefore its optimization facilitates the whole data mining process. Finally, we benchmark and evaluate the performance of the optimized parallel prefix sum building block in CUDA.
Keywords: CUDA; threads; GPGPU; parallel prefix sum; parallel processing; task synchronization; warp (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.rebe.rau.ro/RePEc/rau/jisomg/WI11-2/JISOM-WI11-2-A5.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:5:y:2011:i:2.1:p:465-477
Access Statistics for this article
More articles in Journal of Information Systems & Operations Management from Romanian-American University Contact information at EDIRC.
Bibliographic data for series maintained by Alex Tabusca ().