Sriram Sankar, Aman Kansal, and Jie Liu
18 September 2013
Data center (DC) design has become increasingly important with the rapid growth of cloud computing and online services. The rapid growth rate makes them a significant consumer on the energy grid. Differences in environmental operating conditions, energy price and availability, network bandwidth and latency, as well as unpredictable user demand pose significant challenges for determining the right size, density, and energy sources for data centers. Data from real data centers is often proprietary and severely limits academia and research institutions from addressing these challenges. Building a data center testbed for research is not only cost prohibitive (e.g., a 1 MW datacenter costs approximately 10 Million- 22 Million ) but is also difficult to continually upgrade or explore diversified technologies and industry practices.
Existing modeling, design methodologies and tools are not capable of capturing the scale and heterogeneity in complex systems like data centers. To effectively model performance, energy consumption, energy technologies, network, server trends, failure recovery, and varied operational scenarios, we propose coordinated research efforts to build a DC level full system modeling and simulation platform that enables researchers to investigate multiple DC design aspects for energy and resource efficiency.
|Published in||ASCR Workshop on Modeling & Simulation of Exascale Systems & Applications (MODSIM)|
Christina Delimitrou, Sriram Sankar, Aman Kansal, and Christos Kozyrakis. ECHO: Recreating Network Traffic Maps for Datacenters with Tens of Thousands of Servers, IEEE, 4 November 2012.