Coscheduling has been shown to be a critical factor in achieving efficient parallel execution in timeshared environments [11, 18, 4]. However, the most common approach, gang scheduling, has limitations in scaling, can compromise good interactive response, and requires that communicating processes be identified in advance. We explore a technique called dynamic coscheduling (DCS) which produces emergent coscheduling of the processes constituting a parallel job. Experiments are performed in a workstation environment with high performance networks and autonomous timesharing schedulers for each CPU. The results demonstrate that DCS can achieve effective, robust coscheduling for a range of workloads and background loads. Empirical comparisons to ...
Coordinated thread scheduling is a critical factor in achieving good performance for tightly-coupled...
Simultaneous Multithreading machines benefit from jobscheduling software that monitors how well cos...
To reduce the impact of network congestion on big data jobs, cluster management frameworks use vario...
Abstract. Coscheduling has been shown to be a critical factor in achiev-ing ecient parallel executio...
Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system whe...
Many scientific and high-performance computing applications consist of multiple processes running on...
Implicit coscheduling is known to be an effective tech-nique to improve the performance of parallel ...
Implicit coscheduling strategies enable parallel applications to dynamically share the machines in a...
Workstation clusters are emerging as a general-purpose computing platform for the execution of workl...
Buffered coscheduling is a scheduling methodology for time-sharing communicating processes in parall...
Fine-grained parallel applications require all their processes to run simultaneously on distinct pro...
Gang Scheduling improves the performance of parallel programs by running all child processes concurr...
Modern high-performance computing (HPC) system designs have converged to heavyweight nodes with grow...
Abstract. Predictable network computing still involves a number of open questions. One such question...
It is ubiquitous that multiple jobs coexist on the same machine, because tens or hundreds of cores a...
Coordinated thread scheduling is a critical factor in achieving good performance for tightly-coupled...
Simultaneous Multithreading machines benefit from jobscheduling software that monitors how well cos...
To reduce the impact of network congestion on big data jobs, cluster management frameworks use vario...
Abstract. Coscheduling has been shown to be a critical factor in achiev-ing ecient parallel executio...
Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system whe...
Many scientific and high-performance computing applications consist of multiple processes running on...
Implicit coscheduling is known to be an effective tech-nique to improve the performance of parallel ...
Implicit coscheduling strategies enable parallel applications to dynamically share the machines in a...
Workstation clusters are emerging as a general-purpose computing platform for the execution of workl...
Buffered coscheduling is a scheduling methodology for time-sharing communicating processes in parall...
Fine-grained parallel applications require all their processes to run simultaneously on distinct pro...
Gang Scheduling improves the performance of parallel programs by running all child processes concurr...
Modern high-performance computing (HPC) system designs have converged to heavyweight nodes with grow...
Abstract. Predictable network computing still involves a number of open questions. One such question...
It is ubiquitous that multiple jobs coexist on the same machine, because tens or hundreds of cores a...
Coordinated thread scheduling is a critical factor in achieving good performance for tightly-coupled...
Simultaneous Multithreading machines benefit from jobscheduling software that monitors how well cos...
To reduce the impact of network congestion on big data jobs, cluster management frameworks use vario...