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Speak

er Name/Affiliation: Y. Charlie Hu/Purdue University

Talk Title: P

rogram-Counter-Based Prediction Techniques in Operating Systems

Date

/Time: May 31 2006 at 11:00 a.m.

Location: ACES 6.304

Host

: Mike Dahlin

Talk Abstract:
Program instructions uniquely ide

ntified by their program
counters (PCs) provide a convenient and accura

te means of
recording the context
of program execution and PC-based

prediction techniques
have been widely used for performance optimizatio

ns at the
architectural
level. Operating systems on the other hand
have not fully
explored
the benefits of PC-based prediction for res

ource management.
This work explores the potential benefits provided by
PC-based
prediction in operating systems (PCOS). In particular we
investigate the potential of using PC-based prediction techniques
for

managing I/O devices in operating systems.

As a first demonstration

of PCOS we developed a PC-based
access pattern classification techniqu

e (PCC) for buffer
cache management.
PCC allows the operating system
to correlate the I/O operations
with the program context in which they
are issued via the
PCs of the call instructions that trigger the I/O r

equests.
This correlation allows the operating system to classify
I

/O access pattern on a per-call-site
basis which achieves significantly

better accuracy than
previous per-file or per-application classificatio

n techniques.

We have also developed a PC-based technique (PCAP) for
power
management that dynamically learns the application I/O access patterns
and associated disk idle times to predict when an I/O device

erlay networking wireless networking and high performance
computing.