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SUMMARY:Bayesian State-Space Modelling on High-Performance Hardware Using 
 LibBi - Dr Lawrence Murray\, CSIRO Australia
DTSTART:20140116T150000Z
DTEND:20140116T160000Z
UID:TALK50104@talks.cam.ac.uk
CONTACT:Sumeetpal Sidhu Singh
DESCRIPTION:LibBi is a software package for state-space modelling and Baye
 sian inference on modern computer hardware\, including multi-core central 
 processing units (CPUs)\, many-core graphics processing units (GPUs) and d
 istributed-memory clusters of such devices. The software parses a domain-s
 pecific language for model specification\, then optimises\, generates\, co
 mpiles and runs code for the given model\, inference method and hardware p
 latform. The focus of the software is on sequential Monte Carlo (SMC) meth
 ods such as the particle filter for state estimation\, and the particle Ma
 rkov chain Monte Carlo (PMCMC) and SMC^2 methods for parameter estimation.
  All are well-suited to current computer hardware. This talk will serve as
  an introduction to the software\, and will include a selection of example
  applications drawn from the environmental sciences.\n
LOCATION:LR6\, Engineering\, Department of
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