The PowerNet project aims to characterize the energy consumption of enterprise-style computing infrastructures including user machines, as well as networking, storage, and server equipment. We collect fine-grained power consumption data using wireless powermeters and correlate them to device utilization and system patterns to identify waste and opportunities for reducing energy costs of everyday computing. Currently, out hybrid network of power meters is monitoring 138 devices in Gates Hall, consuming 9,463 watthours.
Christos Kozyrakis
Christos Kozyrakis research focuses on making computer system of any size faster, cheaper, and greener. His current work focuses on the hardware architecture, runtime environment, programming models, and security infrastructure for warehouse-scale data centers and many-core chips with thousands of general purpose cores and fixed functions accelerators.
Last modified Thu, 13 Dec, 2012 at 20:41
Willard R. and Inez Kerr Bell faculty scholar, 2009-11
BM Faculty Award, 2006
NSF Career Award, 2006
Okawa Foundation Research Grant, 2005
PowerNet: a Magnifying Glass for Computing Systems' Energy
EPIC: Efficiency and Proportionality in the Cloud
Energy consumption has emerged as the major limitation for data-centers in terms of operational cost, scalability, reliability, and environmental impact. The EPIC project is investigating hardware and software techniques that improve the energy efficiency and proportionality of data centers. Some aspects of our work include state-aware scale-down techniques, novel server designs, energy efficient memory systems, and data center workload characterization and modeling. The EPIC project follows up on our recent work on energy modeling, benchmarking, and server design (JouleSort project)
Pervasive Parallelism Laboratory
The Pervasive Parallelism Lab (PPL) is developing the hardware and software infrastructure for scalable parallel computing. The key idea is to use domain specific languages to simplify parallel programming and extract the concurrency and locality information necessary to map an application on a highly parallel system. PPL is a multi-faculty effort. I am active in the areas of architecture, runtime environments, and operating systems.
