*Tid:* **13 februari 2017 kl 15.15-16.15.**
**Seminarierummet 3721**, Institutionen för
matematik, KTH, Lindstedtsvägen 25, plan 7.
Karta!
*Föredragshållare:*
**
Lawrence Murray, (Uppsala)
**
**Titel:**
Anytime Monte Carlo
**Abstract**
A Monte Carlo algorithm typically simulates a prescribed number of
samples, taking some random real time to complete the computations
necessary. This work considers the converse: to impose a real-time
budget on the computation, so that the number of samples simulated is
random. To complicate matters, the real time taken for each simulation
may depend on the sample produced, so that the samples themselves are
not independent of their number, and a length bias with respect to
compute time is apparent. We propose an anytime framework to address
this concern, using a continuous-time Markov jump process to study the
progress of the computation in real time. We show that the length bias
can be eliminated for any Markov chain Monte Carlo algorithm by using a
multiple chain construction. The utility of this construction is
demonstrated on a large-scale Sequential Monte Carlo Squared
implementation, using four billion particles distributed across a
cluster of 128 graphics processing units on the Amazon EC2 service. The
anytime framework is used to impose a real-time budget on move steps,
ensuring that all processors are simultaneously ready for the resampling
step, demonstrably reducing wait times.
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