Imperial College London
Professor Wayne Luk

ProfessorWayneLuk

Faculty of Engineering, Department of Computing

Professor of Computer Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8313w.luk Website

 
 
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Location

 

434Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Guo:2014:10.1145/2554688.2554765,
author = {Guo, C and Luk, W},
doi = {10.1145/2554688.2554765},
pages = {181--184},
title = {Accelerating parameter estimation for multivariate self-exciting point processes},
url = {http://dx.doi.org/10.1145/2554688.2554765},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Self-exciting point processes are stochastic processes capturing occurrence patterns of random events. They oer powerful tools to describe and predict temporal distributions of random events like stock trading and neurone spiking. A critical calculation in self-exciting point process models is parameter estimation, which ts a model to a data set. This calculation is computationally demanding when the number of data points is large and when the data dimension is high. This paper proposes the rst recongurable computing solution to accelerate this calculation. We derive an acceleration strategy in a mathematical specication by eliminating complex data dependency, by cutting hardware resource requirement, and by parallelising arithmetic operations. In our experimental evaluation, an FPGA-based implementation of the proposed solution is up to 79 times faster than one CPU core, and 13 times faster than the same CPU with eight cores.
AU  - Guo,C
AU  - Luk,W
DO  - 10.1145/2554688.2554765
EP  - 184
PY  - 2014///
SP  - 181
TI  - Accelerating parameter estimation for multivariate self-exciting point processes
UR  - http://dx.doi.org/10.1145/2554688.2554765
ER  -
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