Abstract: The slowing of Moore’s Law and increased concerns about the environmental impacts of computing are exerting pressure on datacenter operators to use resources such as CPUs and memory more efficiently. However, it is difficult to improve efficiency without degrading the performance of applications.
In this talk, I will focus on CPU efficiency and how we can increase efficiency while maintaining low tail latency for applications. The key innovation is to reallocate cores between applications on the same server very quickly, every few microseconds. First I will describe Shenango, a system design that makes such frequent core reallocations possible. Then I will show how policy choices for core reallocation and load balancing impact CPU efficiency and tail latency, and present the policies that yield the best combination of both.
Bio: Amy is a postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. She received her PhD in Computer Science from MIT and her BSE in Computer Science from Princeton University. Her research is on operating systems and distributed systems, and focuses on improving the efficiency, performance, and usability of applications in datacenters. She is a recipient of a Jacobs Presidential Fellowship at MIT, an NSF Graduate Research Fellowship, and a Hertz Foundation Fellowship.