Achieving cost and performance efficiency for cloud-hosted databases requires exploring a
large configuration space, including the parameters exposed by the database along with the …

Resource usage of production workloads running on shared compute clusters often fluctuate
significantly across time. While simultaneous spike in the resource usage between two …

Network contention can significantly degrade training throughput of deep learning jobs in
GPU clusters. In this paper, we present a new approach to mitigate network contention by …

Public cloud providers offer a diverse collection of storage types and configurations with
different costs and performance SLAs. As a consequence, it is difficult to select the most cost …

A digital environment includes multiple computing nodes and a scheduling system that
assigns workloads to computing nodes. The scheduling system includes an equivalence …

We are witnessing an increasing trend towardsusing Machine Learning (ML) based
prediction systems, span-ning across different application domains, including …

Cluster scheduling based on the prior estimation of job execution time is vulnerable to
inaccurate estimates. To avoid performance degradation due to this misestimation, recent …

High performance processors and systems require high storage bandwidth and efficient
external I/O processing. Many systems using high performance processors server a mixture …