Submissions are invited for the fifth special session on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU-2012) to be held in Brisbane, Australia as part of the IEEE World Congress on Computational Intelligence, 10-15 June 2012. More information can be found at http://www.cs.ucl.ac.uk/staff/W.Langdon/cigpu/.
Call for papers: CIGPU 2012, Brisbane, Australia, 10-15 June 2012
November 10th, 2011CIGPU 2011 Submission deadline 7 April 2011
April 6th, 2011The fourth International workshop and tutorial on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU 2011) will be held in Dublin 13 July 2011. Submissions are invited in (but not limited to): Parallel genetic algorithms, GP, EP, ES, PSO, ACO, DE, Computational Biology, EC on video game platforms and mobile devices. Papers that discuss novel implementations and the practicalities of writing software for these hardware platforms are especially welcome.
Papers should be submitted by 7 April, 2011 in PDF format via email to: cigpu@gpgpgpu.com and contain the subject “GECCO Workshop”
CFP: Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU)
January 13th, 2011The fourth International workshop and tutorial on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU 2011) will be held as a workshop in the GECCO-2011 conference in Dublin 12-16 July 2011. Submissions are invited in (but not limited to) the following areas:
- Parallel genetic programming (GP) on GPU
- Parallel genetic algorithms (GA) on GPU
- Parallel evolutionary programming (EP) on GPU
- Associated or hybrid computational intelligence techniques on GPU
- Particle Swarm Optimisation (PSO)
- Ant colony
- Parallel search algorithms
- Data mining
- Differential Evolution on GPU
- Computational Biology or Bioinformatics on GPU
- Evolutionary computation on video game platforms
- Evolutionary computation on mobile devices
See: http://www.sigevo.org/gecco-2011/workshops.html#cigpu and http://www.cs.ucl.ac.uk/staff/W.Langdon/cigpu/ for more information.
Harnessing Graphics Processors for the Fast Computation of Acoustic Likelihoods in Speech Recognition
February 10th, 2010Abstract:
In large vocabulary continuous speech recognition (LVCSR) the acoustic model computations often account for the largest processing overhead. Our weighted finite state transducer (WFST) based decoding engine can utilize a commodity graphics processing unit (GPU) to perform the acoustic computations to move this burden off the main processor. In this paper we describe our new GPU scheme that can achieve a very substantial improvement in recognition speed whilst incurring no reduction in recognition accuracy. We evaluate the GPU technique on a large vocabulary spontaneous speech recognition task using a set of acoustic models with varying complexity and the results consistently show by using the GPU it is possible to reduce the recognition time with largest improvements occurring in systems with large numbers of Gaussians. For the systems which achieve the best accuracy we obtained between 2.5 and 3 times speed-ups. The faster decoding times translate to reductions in space, power and hardware costs by only requiring standard hardware that is already widely installed.
(Paul R. Dixon, Tasuku Oonishi, Sadaoki Furui, “Harnessing graphics processors for the fast computation of acoustic likelihoods in speech recognition”, Computer Speech & Language, Volume 23, Issue 4, October 2009, Pages 510-526, ISSN 0885-2308, DOI: 10.1016/j.csl.2009.03.005)
CIGPU 2010 CALL FOR PAPERS
November 24th, 2009There will be a special session on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU 2010) as part of IEEE World Congress on Computational Intelligence Conference 2010 (WCCI-2010).
Building on the success of previous CIGPU sessions and workshops, CIGPU 2010 will further explore the role that GPU technologies can play in computational intelligence (CI) research. Submissions of original research are invited on the use of parallel graphics hardware for computational intelligence. Work might involve exploring new techniques for exploiting the hardware, new algorithms to implement on the hardware, new applications for accelerated CI, new ways of making the technology available to CI researchers or the utilisation of the next generation of technologies.
“Anyone who has implemented computational intelligence techniques using any parallel graphics hardware will want to submit to this special session.”