Stanford Technology Ventures Program
The hundreds of thousands of servers in modern warehouse-scale systems make performance and efficiency optimizations pressing design challenges. These systems are traditionally considered homogeneous. However, that is not typically the case. Multiple server generations compose a heterogeneous environment, whose performance opportunities have not been fully explored since techniques that account for platform heterogeneity typically do not scale to the tens of thousands of applications hosted in large-scale cloud providers. The authors present ADSM, a scalable and efficient recommendation system for application-to-server mapping in large-scale Data Centers (DCs) that is QoS-aware.