Analysis and approximation of optimal co-scheduling on chip multiprocessors

Jiang, Yunlian; Shen, Xipeng; Chen, Jie; Tripathi, Rahul

doi:10.1145/1454115.1454146

Cited by 145 publications

(147 citation statements)

References 28 publications

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“…Multicore cache-aware scheduling: Jiang et al formulated the problem of optimal scheduling and gave a solution based on min-weight perfect matching [34]. Since online scheduling requires low overhead, existing approaches utilize hardware event counters, which can be read at little cost.…”

Section: Related Workmentioning

confidence: 99%

Cache Conscious Task Regrouping on Multicore Processors

Xiang

Bao

Ding

et al. 2012

2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012)

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Abstract-Because of the interference in the shared cache on multicore processors, the performance of a program can be severely affected by its co-running programs. If job scheduling does not consider how a group of tasks utilize cache, the performance may degrade significantly, and the degradation usually varies sizably and unpredictably from run to run.In this paper, we use trace-based program locality analysis and make it efficient enough for dynamic use. We show a complete on-line system for periodically measuring the parallel execution, predicting and ranking cache interference for all co-run choices, and reorganizing programs based on the prediction. We test our system on floating-point and mixed integer and floating-point workloads composed of SPEC 2006 benchmarks and compare with the default Linux job scheduler to show the benefit of the new system in improving performance and reducing performance variation.

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Section: Related Workmentioning

confidence: 99%

Cache Conscious Task Regrouping on Multicore Processors

Xiang

Bao

Ding

et al. 2012

2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012)

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“…However, programs commonly interfere with each other [3]. Some times the interference takes a little effect, which do little effect to program's performance.…”

Section: Introductionmentioning

confidence: 99%

Improving co-running program’s performance on CMP

Tian

Li²,

Niu³

et al. 2017

MATEC Web Conf.

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Abstract. Chip multi-processor (CMP) has become the most common processor in the current cluster and desktop computer, and it is also the current development direction. On CMP, programs usually co-running with each other. However, programs commonly interfere with each other. Some time the interference takes big effect, which cause serious drop down of performance. In order to avoid the serious performance interference, programs should be scheduled reasonably to different socket to improve the program's performance and system's utilization. In this paper we propose a new scheduling method to realize a more reasonable scheduling. We do not only consider the LLC miss rate, but also consider the LLC reference of the programs. By the information of LLC reference and LLC miss rate, we schedule programs to different sockets, which realize a reasonable scheduling. The experiment result show that making use of the scheduling method proposed by our paper, program's performance can improve 4%, because the performance improve is realized by on-chip resource, which is a big contribution.

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“…On CMP, programs commonly interference with each other [3]. Some times the effect of interference is little, which do little effect to program's performance.…”

Section: Introductionmentioning

confidence: 99%

Ensuring the Fairness of program’s performance on CMP

Wang¹,

Gao²,

Hou³

et al. 2017

MATEC Web Conf.

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Abstract. On CMP, programs commonly interference with each other. But for programs co-running on CMP, serious performance dropdown is not expected. With the growth of the program's size, program's contention for limited shared resources in the system will become increasingly intense, and the resulting impact on system performance will be even more pronounced. How to allocate and share limited shared resources among programs is a very important problem. In this paper we propose a new method to ensure the fairness of program's performance on CMP. The share resource CPU and memory are included in our study. Meanwhile, the Linux resource management tool Cgroups is used to realize our idea. By the resource we profiled and the tool support, we realize a reasonable resource dividing method to ensure the fairness of program's performance. The reasonable resource dividing method include three Engine. The experiment result show that making use of the fairness resource dividing method proposed by our paper, compared with operating system scheduling, program's performance difference can be largely reduced.

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Analysis and approximation of optimal co-scheduling on chip multiprocessors

Cited by 145 publications

References 28 publications

Cache Conscious Task Regrouping on Multicore Processors

Cache Conscious Task Regrouping on Multicore Processors

Improving co-running program’s performance on CMP

Ensuring the Fairness of program’s performance on CMP

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