Association for Computing Machinery
Large-scale Data Centers (DCs) host tens of thousands of diverse applications each day. However, interference between colocated workloads and the difficulty of matching applications to one of the many hardware platforms available can degrade performance, violating the Quality of Service (QoS) guarantees that many cloud workloads require. While previous work has identified the impact of heterogeneity and interference, existing solutions are computationally intensive, cannot be applied online, and do not scale beyond a few applications. The authors present paragon, an online and scalable DC scheduler that is heterogeneity- and interference-aware.