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A GPU-accelerated Approximate Algorithm for Incremental Learning of Gaussian Mixture Model
Found in: 2012 26th IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
By Chunlei Chen,Dejun Mu,Huixiang Zhang,Bo Hong
Issue Date:May 2012
pp. 1937-1943
The Gaussian mixture model (GMM) is a widely used probabilistic clustering model. The incremental learning algorithm of GMM is the basis of a variety of complex incremental learning algorithms. It is typically applied to real-time or massive data problems ...
Towards a Moderate-Granularity Incremental Clustering Algorithm for GPU
Found in: 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)
By Chunlei Chen, Dejun Mu, Huixiang Zhang, Wei Hu
Issue Date:October 2013
pp. 194-201
The incremental clustering algorithm plays a vital role in big data processing. The massive data problems generally raise high computation demand on the hardware platform. GPU-based parallel computing is a promising method to satisfy this demand. However, ...
A GPU-Based Approach to Accelerate Computational Protein-DNA Docking
Found in: Computing in Science & Engineering
By Jiadong Wu,Chunlei Chen,Bo Hong
Issue Date:May 2012
pp. 20-29
This article describes a GPU-based high-performance computing method to tackle the protein-DNA docking problem. GPU-specific algorithmic techniques are developed to accelerate a docking algorithm that integrates Monte Carlo simulation and simulated anneali...