Leveraging Approximation to Improve Resource Efficiency in the Cloud

Although cloud computing has increased in popularity, datacenter utilization has remained for the most part low. This is in part due to the interference that comes as a result of applications sharing hardware and software resources. When interference occurs, the resources of at least one co-scheduled application need to be reduced forcing it to take a performance penalty. In current proposals, the penalized application is typically a low-priority, best-effort workload. Approximate computing applications present an opportunity to improve datacenter efficiency without performance degradation, since they can absorb the enforced resource reduction as a loss in output quality. In this paper we present Pliant, a runtime system that improves datacenter utilization by co-scheduling interactive services with approximate computing applications. When the runtime detects QoS violations in the interactive service, it employs approximation to reduce interference, and absorbs the resource reduction as a loss in output accuracy.