Results 271 to 280 of about 36,410 (306)

Computer vision signal processing on graphics processing units

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004
This paper shows speedups attained by using computer graphics hardware for implementation of computer vision algorithms by efficiently mapping mathematical operations of computer vision onto modem computer graphics architecture. As an example computer vision algorithm, we implement a real-time projective camera motion tracking routine on modern ...
James Fung, Steve Mann 0001
openaire   +1 more source

Algorithmic performance studies on graphics processing units

Journal of Parallel and Distributed Computing, 2008
We report on our experience with integrating and using graphics processing units (GPUs) as fast parallel floating-point co-processors to accelerate two fundamental computational scientific kernels on the GPU: sparse direct factorization and nonlinear interior-point optimization.
Olaf Schenk, Matthias Christen, Helmar Burkhart   +2 more
openaire   +1 more source

Faster catalog matching on Graphics Processing Units

Astronomy and Computing, 2017
Abstract One of the most fundamental problems in observational astronomy is the cross-identification of sources. Observations are made at different times in different wavelengths with separate instruments, resulting in a large set of independent observations.
Matthias A. Lee, Tamás Budavári
openaire   +1 more source

Coalition structure generation with the graphics processing unit

International Joint Conference on Autonomous Agents and Multiagent Systems, 2014
Coalition Structure Generation---the problem of finding the optimal division of agents into coalitions---has received considerable attention in recent AI literature. The fastest exact algorithm to solve this problem is IDP-IP$^*$, which is a hybrid of two previous algorithms, namely IDP and IP.
Krzysztof Pawlowski, Karol Kurach, Kim Svensson, Sarvapali D. Ramchurn, Tomasz P. Michalak, Talal Rahwan   +5 more
openaire   +2 more sources

Improved Survey Propagation on Graphics Processing Units

2016
The development of graphic processing units (GPUs) ensures a significant improvement in parallel computing performance. However, it also leads to an unprecedented level of complexity in algorithm design because of its physical architecture. In this paper, we propose an improved survey propagation (SP) algorithm to solve the Boolean satisfiability ...
Yang Zhao 0003, Jingfei Jiang, Pengbo Wu
openaire   +1 more source

Cellular Genetic Algorithm on Graphic Processing Units

2010
The availability of low cost powerful parallel graphic cards has estimulated a trend to implement diverse algorithms on Graphic Processing Units (GPUs). In this paper we describe the design of a parallel Cellular Genetic Algorithm (cGA) on a GPU and then evaluate its performance.
Pablo Vidal, Enrique Alba 0001
openaire   +1 more source

Implementing Survey Propagation on Graphics Processing Units

2006
We show how to exploit the raw power of current graphics processing units (GPUs) to obtain implementations of SAT solving algorithms that surpass the performance of CPU-based algorithms. We have developed a GPU-based version of the survey propagation algorithm, an incomplete method capable of solving hard instances of random k-CNF problems close to the
Panagiotis Manolios, Yimin Zhang
openaire   +1 more source

Graphics Processing Unit Technology

2015
Graphics chips started as fixed-function graphics pipelines. Over the years, these graphic chips became programmable, which led Nvidia Corporationto introduce the first graphics processing unit (GPU) at the end of the last century. Nvidia realized the potential in bringing this performance to the largest scientific and research community and decided to
openaire   +1 more source

Comparision of graphics processing units and central processing units [PDF]

, 2009
Graphic processors are becoming faster and faster. Computational power within graphic processing units (GPUs) is growing rapidly compared to central processing units (CPUs). Usage of this power is becoming very interesting in many areas. Programmers try to use this power. They are developing new algorithms for non-graphic applications.
openaire  

The Echo State Network on the Graphics Processing Unit

2013
Extending on previous work, the Echo State Network (ESN) and Tikhonov Regularisation (TR) training algorithms were implemented for both the CPU, an Intel i7-980; and the GPU, an Nvidia GTX480. The implementation used all 4 cores of the CPU, and all 480 cores of the GPU. The execution times of these implementations were measured and compared. In the ESN
Keith, T., Weddell, S.
openaire   +2 more sources