This talk will tell two stories, one about designing sustainable data centers
and one about the underlying algorithmic challenges, which fall into the context of online
Story 1: The typical message surrounding data centers
is an extremely negative one: Data centers
hogs. This message is pervasive in both the popular press and academia, and it certainly rings true. However, the view of data centers
hogs is too simplistic. One goal of this talk is to highlight that, yes, data centers
use a lot of energy
, but data centers
can also be a huge benefit in terms of integrating renewable energy
into the grid and thus play a crucial role in improving the sustainability of our energy
landscape. In particular, I will highlight a powerful alternative view: data centers
as demand response opportunities.
Story 2: Typically in online
it is enough to exhibit an algorithm with low (sub-linear) regret, which implies that the algorithm can match the performance of the best static solution in retrospect. However, what if one additionally wants to maintain performance that is nearly as good as the dynamic optimal, i.e., a good competitive ratio? In this talk, I'll highlight that it is impossible for an online
algorithm to simultaneously achieve these goals. Luckily though, in practical settings (like data centers
), noisy predictions about the future are often available, and I will show that, under a general model of prediction noise, even very limited predictions about the future are enough to overcome the impossibility result.
Adam Wierman is a Professor in the Department of Computing and Mathematical Sciences at the California Institute of Technology, where he is a founding member of the Rigorous Systems Research Group (RSRG) and maintains a popular blog called Rigor + Relevance. His research interests center around resource allocation and scheduling decisions in computer systems and services. He received the 2011 ACM SIGMETRICS Rising Star award, the 2014 IEEE Communications Society William R. Bennett Prize, and has been coauthor on papers that received of best paper awards at ACM SIGMETRICS, IEEE INFOCOM, IFIP Performance (twice), IEEE Green Computing Conference, IEEE Power & Energy Society General Meeting, and ACM GREENMETRICS.