UTCS Colloquium/AI: Greg Hamerly/Baylor University Improving SimPoint Accuracy for Small Simulation Budgets with EDCM Clustering ACES 2.402 Wed. April 30 2008 at 1:00 p.m.
Type of Talk: UTCS Colloquium/AI
Speaker/A
ffiliation: Greg Hamerly/Baylor University
Date/Time: Wednesday A
pril 30 2008 1:00 p.m.
Location: ACES 2.402
Host: Emmett
Witchel
Talk Title: Improving SimPoint Accuracy for Small Simulatio
n Budgets with EDCM Clustering
Talk Abstract:
Detailed processor
simulation is extremely costly on large
benchmark suites where each pr
ogram may run for billions
of instructions and take months of simulatio
n time. We can
obtain good approximate answers in less time using limit
ed
simulation but deciding which regions to simulate is a difficult problem. SimPoint is one approach for choosing simulation
regions ba
sed on the k-means clustering algorithm. We
propose using an alternati
ve clustering model based on a
mixture of exponential Dirichlet compoun
d multinomial (EDCM)
models. This method outperforms k-means in perfor
mance
prediction accuracy when simulation budgets are limited. The
EDCM mixture can cluster high-dimension frequency vector
data directly
without dimension reduction and trains quickly.
Speaker Bio:
Gr
eg Hamerly is an assistant professor of computer science
at Baylor Univ
ersity. His research is in machine learning
particularly in unsupervi
sed learning algorithms and their
applications. He is a primary contri
butor to the SimPoint
project which uses unsupervised learning for eff
icient
computer processor simulation.
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