1 Thermal Management of Datacenter Qinghui Tang

2 Preliminaries What is data center What is thermal management Why does Intel Care Why Computer Science

3 Typical layout of a datacenter Rack outlet temperature T out Rack inlet temperature T in Air conditioner supply temperature T s

4 State-of-Art Thermal Management of Data Center Power densities are increasing exponentially along with Moore’s Law Current cooling solutions at various levels Chip / component level Server/board level Rack level Data center level S/W based Thermal management solutions – HP+Duke

5 Thermal Management of Datacenter Motivation and significance Compute Intensive Applications (Online Gaming, Computer Movie Animation, Data Mining) requiring increased utilization of Data Center Maximizing computing capacity is a demanding requirement New blade servers can be packed more densely Energy cost is rising dramatically Goal Improving thermal performance Lowering hardware failure rate Reducing energy cost

6 Typical layout of a datacenter

7 New Challenges Planning perspective: How to design efficient data center? does upgrading 10% blade servers to smart ones help to reduce cost Operation perspective: How to efficiently operate data center and lower the cost? What’s the trade-off between utility cost and hardware failure cost Overcooling: wastes energy and increases utility cost Undercooling: increases frequency of hardware failures

8 Research Issues of Thermal Management of Datacenter Abstract Heat Flow Model Power & Load Characterization Modeling Thermal Performance Multiscale & Multimodal Info Analysis Thermal Performance Evaluation Cost Optimization Scheduler Other Impact Factors Understanding Control

9 Example of multiple granularity and scale

10 Multiscale and multimodal nature of datacenter management Information perspective Multiple system variables Different change pattern Different sampling Rate Control perspective Responsiveness Control granularity (spatial and temporal level) Sensitivity Analysis

11 Approaches CFD simulation to characterize thermal performance of data center Online measurement and feedback control system

12 CFD Simulation CFD real model based on ASU HPC center

13 Thermal-aware task scheduling

14 Two-Pronged Approach Real-time measurement Online lightweight simulation & prediction

15 Goal: Datacenter energy cost optimization

16 Different optimization goals Maximizing computation capacity given energy cost constraint Minimizing individual cost (computing cost/cooling cost) Achieving thermal balancing

17 Questions and answers