Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Are Sleep States Effective in Data Centers?
Proceedings of the International Green Computing Conference (IGCC'12), San Jose, CA, June 5-8, 2012.
Anshul Gandhi, Mor Harchol-Balter, Michael A. Kozuch*
Carnegie Mellon University
* Intel Labs
While sleep states have existed for mobile devices and workstations for some time, these sleep states have not been incorporated into most of the servers in today's data centers. High setup times make data center administrators fearful of any form of dynamic power management, whereby servers are suspended or shut down when load drops. This general reluctance has stalled research into whether there might be some feasible sleep state (with sufficiently low setup overhead and/or sufficiently low power) that would actually be beneficial in data centers.
This paper investigates the regime of sleep states that would be advantageous in data centers. We consider the benefits of sleep states across three orthogonal dimensions: (i) the variability in the workload trace, (ii) the type of dynamic power management policy employed, and (iii) the size of the data center.
Our implementation results on a 24-server multi-tier testbed indicate that under many traces, sleep states greatly enhance dynamic power management. In fact, given the right sleep states, even a naive policy that simply tries to match capacity with demand, can be very effective. By contrast, we characterize certain types of traces for which even the "best" sleep state under consideration is ineffective. Our simulation results suggest that sleep states are even more beneficial for larger data centers.
FULL PAPER: pdf