Job Re-packing for Enhancing the Performance of Gang Scheduling

Zhou, Bing Bing; Brent, Richard P.; Johnson, Charles W.; Walsh, David O.

doi:10.1007/3-540-47954-6_7

Cited by 11 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The one advantage that GS has over its dynamic coscheduling counterparts is that it is fair across different job types. It should be noted that GS could be enhanced further, as others [12], [41] have suggested, which may tip the balance in favor of GS when the above factors are not overwhelming.…”

Section: Concluding Remarks and Future Workmentioning

confidence: 92%

Impact of workload and system parameters on next generation cluster scheduling mechanisms

Zhang

Sivasubramaniam

Moreira

et al. 2001

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

AbstractÐScheduling of processes onto processors of a parallel machine has always been an important and challenging area of research. The issue becomes even more crucial and difficult as we gradually progress to the use of off-the-shelf workstations, operating systems, and high bandwidth networks to build cost-effective clusters for demanding applications. Clusters are gaining acceptance not just in scientific applications that need supercomputing power, but also in domains such as databases, web service, and multimedia which place diverse Quality-of-Service (QoS) demands on the underlying system. Further, these applications have diverse characteristics in terms of their computation, communication, and I/O requirements, making conventional parallel scheduling solutions, such as space sharing or gang scheduling, unattractive. At the same time, leaving it to the native operating system of each node to make decisions independently can lead to ineffective use of system resources whenever there is communication. Instead, an emerging class of dynamic coscheduling mechanisms that attempt to take remedial actions to guide the system toward coscheduled execution without requiring explicit synchronization offers a lot of promise for cluster scheduling. Using a detailed simulator, this paper evaluates the pros and cons of different dynamic coscheduling alternatives while comparing their advantages over traditional gang scheduling (and not performing any coordinated scheduling at all). The impact of dynamic job arrivals, job characteristics, and different system parameters on these alternatives is evaluated in terms of several performance criteria. In addition, heuristics to enhance one of the alternatives even further are identified, classified, and evaluated. It is shown that these heuristics can significantly outperform the other alternatives over a spectrum of workload and system parameters and is thus a much better option for clusters than conventional gang scheduling.

show abstract

Section: Concluding Remarks and Future Workmentioning

confidence: 92%

Impact of workload and system parameters on next generation cluster scheduling mechanisms

Zhang

Sivasubramaniam

Moreira

et al. 2001

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

show abstract

“…In job re-packing we always utilise this kind of legal shift to rearrange jobs between time slots so that small fragments of available processors in different time slots can be combined into a larger and more useful one. This kind of job repacking can effectively be done based on the following two simple properties [11].…”

Section: Job Re-packingmentioning

confidence: 99%

“…To alleviate the problem of fragmentation we proposed another scheme, namely job re-packing [11]. In this scheme we try to rearrange the order of job execution on the originally allocated processors so that small fragments of idle resources from different time slots can be combined together to form a larger and more useful one in a single time slot.…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation Schemes for Gang Scheduling

Zhou

Walsh

Brent

2000

Job Scheduling Strategies for Parallel Processing

View full text Add to dashboard Cite

Gang scheduling is currently the most popular scheduling scheme for parallel processing in a time shared environment. In this paper we first describe the ideas of job re-packing and workload tree for efficiently allocating resources to enhance the performance of gang scheduling. We then present some experimental results obtained by implementing four different resource allocation schemes. These results show how the ideas, such as re-packing jobs, running jobs in multiple slots and minimising the average number of time slots in the system, affect system and job performance when incorporated into the buddy based allocation scheme for gang scheduling.

show abstract

“…Scheduling strategies can have a significant impact on the performance characteristics of a large parallel system [2,3,4,7,10,13,14,17,18,21,22]. Early strategies used a space-sharing approach, wherein jobs can run concurrently on different nodes of the machine at the same time, but each node is exclusively assigned to a job.…”

Section: Introductionmentioning

confidence: 99%

“…The second approach is to add a time-sharing dimension to space sharing using a technique called gangscheduling or coscheduling [16,22]. This technique virtualizes the physical machine by slicing the time axis into multiple virtual machines.…”

Section: Introductionmentioning

confidence: 99%

An integrated approach to parallel scheduling using gang-scheduling, backfilling, and migration

Zhang

Franke

Moreira

et al. 2003

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

Effective scheduling strategies to improve response times, throughput, and utilization are an important consideration in large supercomputing environments. Such machines have traditionally used space-sharing strategies to accommodate multiple jobs at the same time. This approach, however, can result in low system utilization and large job wait times. This paper discusses three techniques that can be used beyond simple space-sharing to greatly improve the performance figures of large parallel systems. The first technique we analyze is backfilling, the second is gang-scheduling, and the third is migration. The main contribution of this paper is an evaluation of the benefits from combining the above techniques. We demonstrate that, under certain conditions, a strategy that combines backfilling, gang-scheduling, and migration is always better than the individual strategies for all quality of service parameters that we consider.

show abstract

Job Re-packing for Enhancing the Performance of Gang Scheduling

Cited by 11 publications

References 5 publications

Impact of workload and system parameters on next generation cluster scheduling mechanisms

Impact of workload and system parameters on next generation cluster scheduling mechanisms

Resource Allocation Schemes for Gang Scheduling

An integrated approach to parallel scheduling using gang-scheduling, backfilling, and migration

Contact Info

Product

Resources

About