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LFCS Seminar: Richard Hayden

Scalable Performance Analysis of Massively Parallel Stochastic Systems

When Oct 09, 2012
from 03:00 PM to 04:00 PM
Where IF 4.31-4.33
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Performance analysis has always suffered from the state-space explosion
problem which directly prohibits the scalability of stochastic modelling
as a tool for resolving resource provisioning and quality of service
questions in massively parallel computer and communication systems. This
is especially true when applied to the recent ubiquitous breed of
distributed and peer-to-peer systems.

One way around these scalability limitations are asymptotic techniques
formally justified by functional laws of large numbers often termed
variously ``fluid'' or ``mean-field'' analysis. These techniques have
their roots in classical heavy-traffic analysis in the context of
queueing networks, and also borrow from ideas in chemistry and biology.
Such approaches have recently experienced something of a revival in the
context of general massive interacting computational systems such as
might be specified formally using a stochastic process algebra or
stochastic Petri nets.

In this talk, we will introduce these approaches and showcase some of
the methods and the results which can be obtained. Furthermore, we will
introduce the freely available Grouped PEPA Analyser (GPA) tool which
provides efficient implementation of a wide range of these techniques.

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