Efficient online scheduling for coflow-aware machine learning clusters
Distributed machine learning (DML) is an increasingly important workload. In a DML job,
each communication phase can comprise a coflow, and there are dependencies among its …
each communication phase can comprise a coflow, and there are dependencies among its …
Scheduling mix-coflows in datacenter networks
Data-parallel applications generate a mix of coflows with and without deadlines. Deadline
coflows are mission-critical and must be completed within deadlines, while the non-deadline …
coflows are mission-critical and must be completed within deadlines, while the non-deadline …
Coflow scheduling with performance guarantees for data center applications
Data-parallel applications run on cluster of servers in a datacenter and their communication
triggers correlated resource demand on multiple links that can be abstracted as coflow. They …
triggers correlated resource demand on multiple links that can be abstracted as coflow. They …
Selective coflow completion for time-sensitive distributed applications with poco
Recently, the abstraction of coflow is introduced to capture the collective data transmission
patterns among modern distributed data-parallel application. During processing, coflows …
patterns among modern distributed data-parallel application. During processing, coflows …