SOLUTIONS FOR OPTIMIZING THE STREAM COMPACTION ALGORITHMIC FUNCTION USING THE COMPUTE UNIFIED DEVICE ARCHITECTURE

Alexandru Pîrjan ()
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Alexandru Pîrjan: Faculty of Computer Science for Business Management, Romanian-American University

Journal of Information Systems & Operations Management, 2012, vol. 6, issue 1, 216-231

Abstract: In this paper, I have researched and developed solutions for optimizing the stream compaction algorithmic function using the Compute Unified Device Architecture (CUDA). The stream compaction is a common parallel primitive, an essential building block for many data processing algorithms, whose optimization improves the performance of a wide class of parallel algorithms useful in data processing. A particular interest in this research was to develop solutions for optimizing the stream compaction algorithmic function that offers optimal solutions over an entire range of CUDA enabled GPUs: Tesla GT200, Fermi GF100 and the latest Kepler GK104 architecture, released on 22 March 2012. In order to confirm the utility of the developed optimization solutions, I have extensively benchmarked and evaluated the performance of the stream compaction algorithmic function in CUDA.

Keywords: parallel processing; CUDA; Kepler; threads; stream compaction (search for similar items in EconPapers)
Date: 2012
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