An implementation of the non-negative matrix factorization algorithm for the purpose of text mining on graphics processing units is presented. Performance gains of more than one order of magnitude are obtained.

August 1, 2012 by hgpu

We parallelize a version of the active-set iterative algorithm derived from the original works of Lawson and Hanson [Solving Least Squares Problems, Prentice-Hall, 1974] on multicore architectures. This algorithm requires the solution of an unconstrained least squares problem in every step of the iteration for a matrix composed of the passive columns of the original […]

November 28, 2011 by hgpu

This article presents an optimized algorithm for Nonnegative Tensor Factorization (NTF), implemented in the CUDA (Compute Uniform Device Architecture) framework, that runs on contemporary graphics processors and exploits their massive parallelism. The NTF implementation is primarily targeted for analysis of high-dimensional spectral images, including dimensionality reduction, feature extraction, and other tasks related to spectral imaging; […]

July 2, 2011 by hgpu

In this paper, we describe an alternative method of the recognition of human irises with the usage of Non-Negative Matrix Factorization. The proposed method has been implemented on graphic processor unit (GPU) which makes the method usable in the real world due to short computation time.

June 16, 2011 by hgpu

Attacks on the computer infrastructures are becoming an increasingly serious problem. Whether it is banking, e-commerce businesses, health care, law enforcement, air transportation, or education, we are all becoming increasingly reliant upon the networked computers. The possibilities and opportunities are limitless; unfortunately, so too are the risks and chances of malicious intrusions. Intrusion detection is […]

May 12, 2011 by hgpu

This article brings an interesting comparison of two different methods, which were implemented on GPU and help us to detect system intrusions. Generally, both of them can be widely used in the area of information retrieval. The modern trends of parallel computation have a significant influence on performance of implemented methods (Non-negative Matrix Factorization (NMF) […]

May 3, 2011 by hgpu

This paper discusses the potential of graphics processing units (GPUs) in high-dimensional optimization problems. A single GPU card with hundreds of arithmetic cores can be inserted in a personal computer and dramatically accelerates many statistical algorithms. To exploit these devices fully, optimization algorithms should reduce to multiple parallel tasks, each accessing a limited amount of […]

October 30, 2010 by hgpu