SCHEDULE: NOV 10-16, 2012
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ValuePack - Value-Based Scheduling Framework for CPU-GPU Clusters
SESSION: Datacenter Technologies
EVENT TYPE: Papers
TIME: 2:30PM - 3:00PM
SESSION CHAIR: Rolf Riesen
AUTHOR(S):Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar
ROOM:255-BC
ABSTRACT:
Heterogeneous computing nodes are becoming commonplace today, and recent trends strongly indicate that clusters, supercomputers, and cloud environments will increasingly host more heterogeneous resources, with some being massively parallel (e.g., GPU, MIC). With such heterogeneous environments becoming common, it is important to revisit scheduling problems for clusters and cloud environments.
In this paper, we formulate and address the problem of value-driven scheduling of independent jobs on heterogeneous clusters, which captures both the urgency and relative priority of jobs. Our overall scheduling goal is to maximize the aggregate value or yield of all jobs. Exploiting the portability available from the underlying programming model, we propose four novel scheduling schemes that can automatically and dynamically map jobs onto heterogeneous resources. Additionally, to improve the utilization of massively parallel resources, we also propose heuristics to automatically decide when and which jobs can share a single resource.
Chair/Author Details:
Rolf Riesen (Chair) - IBM
Vignesh T. Ravi - Ohio State University
Michela Becchi - University of Missouri
Gagan Agrawal - Ohio State University
Srimat Chakradhar - NEC Laboratories America
Click here to download .ics calendar file
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ValuePack - Value-Based Scheduling Framework for CPU-GPU Clusters
SESSION: Datacenter Technologies
EVENT TYPE:
TIME: 2:30PM - 3:00PM
SESSION CHAIR: Rolf Riesen
AUTHOR(S):Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar
ROOM:255-BC
ABSTRACT:
Heterogeneous computing nodes are becoming commonplace today, and recent trends strongly indicate that clusters, supercomputers, and cloud environments will increasingly host more heterogeneous resources, with some being massively parallel (e.g., GPU, MIC). With such heterogeneous environments becoming common, it is important to revisit scheduling problems for clusters and cloud environments.
In this paper, we formulate and address the problem of value-driven scheduling of independent jobs on heterogeneous clusters, which captures both the urgency and relative priority of jobs. Our overall scheduling goal is to maximize the aggregate value or yield of all jobs. Exploiting the portability available from the underlying programming model, we propose four novel scheduling schemes that can automatically and dynamically map jobs onto heterogeneous resources. Additionally, to improve the utilization of massively parallel resources, we also propose heuristics to automatically decide when and which jobs can share a single resource.
Chair/Author Details:
Rolf Riesen (Chair) - IBM
Vignesh T. Ravi - Ohio State University
Michela Becchi - University of Missouri
Gagan Agrawal - Ohio State University
Srimat Chakradhar - NEC Laboratories America
Click here to download .ics calendar file