Many cluster management systems (CMSs) have been proposed to share a single cluster
with multiple distributed computing systems. However, none of the existing approaches can
handle distributed machine learning (ML) workloads given the following criteria: high
resource utilization, fair resource allocation and low sharing overhead. To solve this
problem, we propose a new CMS named Dorm, incorporating a dynamically-partitioned
cluster management mechanism and an utilization-fairness optimizer. Specifically, Dorm …

Many cluster management systems (CMSs) have been proposed to share a single cluster
with multiple distributed computing systems. However, none of the existing approaches can
handle distributed machine learning (ML) workloads given the following criteria: high
resource utilization, fair resource allocation and low sharing overhead. To solve this
problem, we propose a new CMS named Dorm, incorporating a dynamicallypartitioned
cluster management mechanism and an utilizationfairness optimizer. Specifically, Dorm …