Reconfigurable and Self-Optimizing Multicore Architectures

Date: 
Tuesday, March 10, 2009 - 3:45pm

UCSB COMPUTER SCIENCE DEPARTMENT PRESENTS:
Computer Engineering CE Program Seminar

FRIDAY, MARCH 13, 2009
9:00
Harold Frank Hall, Room 4164

SPEAKER: Engin Ipek
Microsoft Research

Title: Reconfigurable and Self-Optimizing Multicore Architectures

Abstract:

As industry rides the transistor density growth in multicore
processors by providing more and more cores, these will exert
increasing levels of pressure on shared system resources. Efficient
resource management becomes critical to obtaining high utilization,
and eliminating potential bandwidth, latency, and cost barriers in
multicore systems. Unfortunately, current hardware policies for
microarchitectural resource management are ad hoc at best, and are
generally incapable of providing basic functionalities like
anticipating the long-term consequences of scheduling decisions
(planning), or generalizing from experience obtained through past
resource allocation decisions to act successfully in new situations
(learning). As a result, current hardware controllers tend to grossly
underutilize the (already limited) platform resources available. In
this talk, using the problem of memory scheduling as context, I will
describe the use of machine learning (ML) technology in designing
self-optimizing, adaptive hardware controllers capable of planning,
learning, and continuously adapting to changing workload demands. An
ML-based design approach allows the hardware designer to focus on
what performance target the controller should accomplish and what
system variables might be useful to ultimately derive a good control
policy, rather than devising a fixed policy that describes exactly
how the controller should accomplish that target. This not only
eliminates much of the human design effort involved in traditional
controller design, but also yields higher-performing, more efficient
controllers.

This work was completed as part of Engin Ipek’s Ph.D. thesis at
Cornell’s Computer Systems Laboratory. It has been nominated for the
2008 ACM Doctoral Dissertation Award by Cornell University.

Bio:

Engin Ipek is a researcher in the Computer Architecture group at
Microsoft Research. He earned his Ph.D. (2008), M.S. (2007), and B.S.
(2003) degrees from Cornell University, all in Electrical and
Computer Engineering. His research interests are in computer
architecture, with an emphasis on multicore architectures, hardware-
software interaction, and the application of machine learning to
computer systems. He is a member of the ACM and the IEEE.