EM-KDE: A locality-aware job scheduling policy with distributed semantic caches

2015 ◽  
Vol 83 ◽  
pp. 119-132 ◽  
Author(s):  
Youngmoon Eom ◽  
Deukyeon Hwang ◽  
Junyong Lee ◽  
Jonghwan Moon ◽  
Minho Shin ◽  
...  
2014 ◽  
Vol 13 (3) ◽  
pp. 501-507
Author(s):  
Yan Qiang ◽  
Yue Li ◽  
Wei Wei ◽  
Bo Pei ◽  
Juanjuan Zhao ◽  
...  

2011 ◽  
Vol 6 (17) ◽  
pp. 3729-3750 ◽  
Author(s):  
Bouyer Asgarali ◽  
Hanan Abdullah Abdul ◽  
hoseinMokhtari Mohammad

2004 ◽  
Vol 14 (02) ◽  
pp. 255-270 ◽  
Author(s):  
JEMAL H. ABAWAJY

Cluster computing has come to prominence as a cost-effective parallel processing tool for solving many complex computational problems. In this paper, we propose a new timesharing opportunistic scheduling policy to support remote batch job executions over networked clusters to be used in conjunction with the Condor Up-Down scheduling algorithm. We show that timesharing approaches can be used in an opportunistic setting to improve both mean job slowdowns and mean response times with little or no throughput reduction. We also show that the proposed algorithm achieves significant improvement in job response time and slowdown as compared to exiting approaches and some recently proposed new approaches.


2020 ◽  
Vol 245 ◽  
pp. 07043
Author(s):  
Qiulan Huang ◽  
Haibo Li ◽  
Yaodong Cheng ◽  
Jingyan Shi ◽  
Wei Zheng ◽  
...  

In this paper we will describe the LHAASO distributed computing system based on virtualization and cloud computing technologies. Particularly, we discuss the key points of integrating distributed resources. A solution of integrating cross-domain resources is proposed, which adopt the Openstack+HTCondor to make the distributed resources work as a whole resource pool. A flexible resource scheduling strategy and a job scheduling policy are presented to realize the resource expansion on demand and the efficient job scheduling to remote sites transparently, so as to improve the overall resource utilization. We will also introduce the deployment of the computing system located in Daocheng, the LHAASO observation base using cloud-based architecture, which greatly helps to reduce the operation and maintenance cost as well as to make sure the system availability and stability. Finally, we will show running status of the system.


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