🚀 go-pugleaf

Please join us this Thursday November 9 at noon in Wean Hall Room 8220:
Tajana Simunic, a Doctoral Candidate in EE from Stanford University,
will deliver
"Energy Efficient System Design."

Abstract:
Energy consumption of electronic devices has become a serious concern in
recent years.  Energy-efficient design of systems demands optimization
in design and
utilization of both hardware and software. In this work we first discuss
power management algorithms that enable optimal utilization of hardware
at run time. In addition, we develop a modular approach for accurate and
fast simulation of hardware and software energy consumption at the
system level. Finally, we present an energy consumption profiler that is
used to optimize software.  Power management (PM) algorithms aims at
reducing energy consumption at the system-level by selectively placing
components into low-power states.
Our approaches are event-driven and give optimal results verified by
measurements.
The first approach we present is based on renewal theory. This model
assumes that
the decision to transition to low power state can be made in only one
state.
Another method we developed is based on the Time-Indexed Semi-Markov
Decision Process model (TISMDP).  This model assumes that a decision to
transition into a lower-power state can be made upon each event
occurrence from any number of states.  This model allows for transitions
into low power states from any state, but it is also more complex than
our other approach.  It is important to note that the results obtained
by renewal model are guaranteed to match results obtained by TISMDP
model, as both approaches give globally optimal solutions.  We
implemented our power management algorithms on two different classes of
devices:  two different hard disks and client-server WLAN systems such
as the SmartBadge or a laptop.  The measurement results show power
savings ranging from a factor of 1.7 up to 5.0 with performance
basically unaffected.

We next present a modular approach for enhancing instruction level
simulators with cycle-accurate simulation of energy dissipation in
systems.  Our methodology has tightly coupled component models thus
making our approach more accurate.  Performance and energy computed by
our simulator are within 5% tolerance of hardware measurements on the
SmartBadge. We show how the simulation  methodology can be used for
hardware design exploration aimed at enhancing the SmartBadge with
real-time MPEG video feature. In addition, we present a profiler that
relates energy consumption to the source code.  Using the profiler we
can quickly and easily redesign the MP3 audio decoder software to run in
real time on the SmartBadge with low energy consumption. Performance
increase of 92% and energy consumption decrease of 77% over the original
executable specification have been achieved.