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» Accelerating K-Means on the Graphics Processor via CUDA
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INTENSIVE
2009
IEEE
14 years 2 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
14 years 1 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 7 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»
14 years 2 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 11 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. ...