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» Accelerating K-Means on the Graphics Processor via CUDA
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INTENSIVE
2009
IEEE
13 years 11 months ago
Accelerating K-Means on the Graphics Processor via CUDA
In this paper an optimized k-means implementation on the graphics processing unit (GPU) is presented. NVIDIA’s Compute Unified Device Architecture (CUDA), available from the G8...
Mario Zechner, Michael Granitzer
HIPC
2007
Springer
13 years 10 months ago
Accelerating Large Graph Algorithms on the GPU Using CUDA
Abstract. Large graphs involving millions of vertices are common in many practical applications and are challenging to process. Practical-time implementations using high-end comput...
Pawan Harish, P. J. Narayanan
BMCBI
2008
211views more  BMCBI 2008»
13 years 4 months ago
CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment
Background: Searching for similarities in protein and DNA databases has become a routine procedure in Molecular Biology. The Smith-Waterman algorithm has been available for more t...
Svetlin Manavski, Giorgio Valle
GCB
2009
Springer
481views Biometrics» more  GCB 2009»
13 years 11 months ago
CUDA-based Multi-core Implementation of MDS-based Bioinformatics Algorithms
: Solving problems in bioinformatics often needs extensive computational power. Current trends in processor architecture, especially massive multi-core processors for graphic cards...
Thilo Fester, Falk Schreiber, Marc Strickert
ASPLOS
2011
ACM
12 years 8 months ago
Sponge: portable stream programming on graphics engines
Graphics processing units (GPUs) provide a low cost platform for accelerating high performance computations. The introduction of new programming languages, such as CUDA and OpenCL...
Amir Hormati, Mehrzad Samadi, Mark Woh, Trevor N. ...