OSDI '04 Abstract
Pp. 395408 of the Proceedings
Program-Counter-Based Pattern Classification in Buffer Caching
Chris Gniady, Ali R. Butt, and Y. Charlie Hu, Purdue University
Program-counter-based (PC-based) prediction techniques have been shown to be
highly effective and are widely used in computer architecture design.
In this paper, we explore the opportunity and viability of applying
PC-based prediction to operating systems design, in particular, to
optimize buffer caching.
We propose a Program-Counter-based Classification (PCC) technique
for use in pattern-based buffer caching that allows the operating
system to correlate the I/O operations with the program
context in which they are issued via the program counters of the
call instructions that trigger the I/O requests. This correlation
allows the operating system to classify I/O access pattern on a
per-PC basis which achieves significantly better accuracy than
previous per-file or per-application classification techniques. PCC
also performs classification more quickly as per-PC pattern just
needs to be learned once. We evaluate PCC via trace-driven
simulations and an implementation in Linux, and compare it to UBM, a
state-of-the-art pattern-based buffer replacement scheme. The
performance improvements are substantial: the hit ratio improves by
as much as 29.3% (with an average of 13.8%), and the execution time
is reduced by as much as 29.0% (with an average of 13.7%).
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