PROC: Process ReOrdering-Based Coscheduling on Workstation Clusters

Authors:
Jung-Lok Yu;Driss Azougagh;Jin-Soo Kim;Seung-Ryoul Maeng
Affiliations:
Korea Advanced Institute of Science and Technology (KAIST), South Korea;Korea Advanced Institute of Science and Technology (KAIST), South Korea;Korea Advanced Institute of Science and Technology (KAIST), South Korea;Korea Advanced Institute of Science and Technology (KAIST), South Korea
Venue:
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Year:
2005

Citing 17
Cited 0

U-Net: a user-level network interface for parallel and distributed computing

SOSP '95 Proceedings of the fifteenth ACM symposium on Operating systems principles
Effective distributed scheduling of parallel workloads

Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A closer look at coscheduling approaches for a network of workstations

Proceedings of the eleventh annual ACM symposium on Parallel algorithms and architectures
An evaluation of parallel job scheduling for ASCI Blue-Pacific

SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Alternatives to coscheduling a network of workstations

Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Dynamic adaptation to available resources for parallel computing in an autonomous network of workstations

PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
Impact of Workload and System Parameters on Next Generation Cluster Scheduling Mechanisms

IEEE Transactions on Parallel and Distributed Systems
CSIM19: CSIM19: a powerful tool for building system models

Proceedings of the 33nd conference on Winter simulation
Myrinet: A Gigabit-per-Second Local Area Network

IEEE Micro
The Virtual Interface Architecture

IEEE Micro
Improved Utilization and Responsiveness with Gang Scheduling

IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Dynamic Coscheduling on Workstation Clusters

IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Metrics for Parallel Job Scheduling and Their Convergence

JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
A Comparative Evaluation of Implicit Coscheduling Strategies for Networks of Workstations

HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
Flexible CoScheduling: Mitigating Load Imbalance and Improving Utilization of Heterogeneous Resources

IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
An Efficient Implementation of Virtual Interface Architecture using Adaptive Transfer Mechanism on Myrinet

ICPADS '01 Proceedings of the Eighth International Conference on Parallel and Distributed Systems
Demand-based coscheduling of parallel jobs on multiprogrammed multiprocessors

Demand-based coscheduling of parallel jobs on multiprogrammed multiprocessors

Quantified Score

Hi-index	0.00

Visualization

Abstract

Workstation clusters are emerging as a platform for the execution of general-purpose workloads. To use clusters as shared computing servers, scheduling techniques able to effectively handle workloads with diverse characteristics on demands, are required. Implicit coscheduling is known to be an effective technique to improve the performance of parallel workloads in time-sharing clusters. However, implicit coscheduling still does not take into consideration the system behavior like load imbalance that affects cluster utilization. In this paper, we propose the use of global information to enhance the existing implicit coscheduling schemes. We also introduce a novel coscheduling approach based on process reordering exploiting global load imbalance information to coordinate communicating processes. The results obtained from a detailed simulation study show that our approach significantly decreases the average job response time (by up to 21.4%) by reducing the idle time (by up to 55.6%) and spin time (by up to 31.8%) caused by the load imbalance.