Task mapper and application-aware virtual machine scheduler oriented for parallel computing

Jing ZHANG; Xiao-jun CHEN; Jun-huai LI; Xiang LI

doi:10.1631/jzus.C1100217

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Task mapper and application-aware virtual machine scheduler oriented for parallel computing

Computer & Automation | Updated：2022-12-09

- Task mapper and application-aware virtual machine scheduler oriented for parallel computing
- Task mapper and application-aware virtual machine scheduler oriented for parallel computing
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 3, Pages: 155-177(2012)
- Affiliations：
  
  1.School of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China
  2.State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710048, China
- Author bio：
  
  [ "Jing ZHANG, ZhangJing@xaut.edu.cn" ]
  Xiao-jun CHEN, army.net@163.com
  [ "Jun-huai LI, lijunhuai@xaut.edu.cn" ]
  [ "Xiang LI, lixiang@163.com" ]
- Funds：
- DOI：10.1631/jzus.C1100217
  CLC： TP391;TP393
- Received：27 July 2011，
  
  Revised：2012-;2-;9，
  
  Published：2012-03
- Accepted：
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Jing ZHANG, Xiao-jun CHEN, Jun-huai LI, et al. Task mapper and application-aware virtual machine scheduler oriented for parallel computing[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(3): 155-177.
DOI：

Jing ZHANG, Xiao-jun CHEN, Jun-huai LI, et al. Task mapper and application-aware virtual machine scheduler oriented for parallel computing[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(3): 155-177. DOI： 10.1631/jzus.C1100217.

摘要

Abstract

We design a task mapper TPCM for assigning tasks to virtual machines

and an application-aware virtual machine scheduler TPCS oriented for parallel computing to achieve a high performance in virtual computing systems. To solve the problem of mapping tasks to virtual machines

a virtual machine mapping algorithm (VMMA) in TPCM is presented to achieve load balance in a cluster. Based on such mapping results

TPCS is constructed including three components: a middleware supporting an application-driven scheduling

a device driver in the guest OS kernel

and a virtual machine scheduling algorithm. These components are implemented in the user space

guest OS

and the CPU virtualization subsystem of the Xen hypervisor

respectively. In TPCS

the progress statuses of tasks are transmitted to the underlying kernel from the user space

thus enabling virtual machine scheduling policy to schedule based on the progress of tasks. This policy aims to exchange completion time of tasks for resource utilization. Experimental results show that TPCM can mine the parallelism among tasks to implement the mapping from tasks to virtual machines based on the relations among subtasks. The TPCS scheduler can complete the tasks in a shorter time than can Credit and other schedulers

because it uses task progress to ensure that the tasks in virtual machines complete simultaneously

thereby reducing the time spent in pending

synchronization

communication

and switching. Therefore

parallel tasks can collaborate with each other to achieve higher resource utilization and lower overheads. We conclude that the TPCS scheduler can overcome the shortcomings of present algorithms in perceiving the progress of tasks

making it better than schedulers currently used in parallel computing.

关键词

Keywords

references

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