Abstract:Abstract. Virtualization technology has been gaining acceptance in the scientific community due to its overall flexibility in running HPC applications. It has been reported that a specific class of applications is better suited to a particular type of virtualization scheme or implementation. For example, Xen has been shown to perform with little overhead for compute-bound applications. Such a study, although useful, does not allow us to generalize conclusions beyond the performance analysis of that application… Show more
“…Many researchers put their focus on the performance overheads of several pivotal system components in virtualization environments, e.g., CPU, memory, disk and network etc [5,6]. Some researchers focus the performance overheads in specific scenarios, such as server consolidation [7,8] and HPC environment [9]. However, to the best of our knowledge, none of them have quantified the deployment efficiency for typical server applications and HPC applications under different deployment strategies.…”
Abstract. Virtualization technology plays an important role in modern data center, as it creates an opportunity to improve resource utilization, reduce energy costs, and ease server management. However, virtual machine deployment issues arise when allocating virtual machines into single or multiple physical servers. In this paper, we explore the performance and scalability issues for virtual machine deployment in a virtualized data center. We first evaluate the image scalability when allocating multiple VMs per physical server using four typical servers in data center. Then we investigate how the overall efficiency will be affected when deploying M virtual machines into N physical machines with different deployment strategies. Experimental results show that: (i) There is a resource bottleneck when deploying single type virtual machine server into single physical server, except for composite workloads. (ii) More physical machines do not always benefit for some specific applications to support a fixed number of virtual machines. (iii) MPI and network communication overheads affect the deployment efficiency seriously.
“…Many researchers put their focus on the performance overheads of several pivotal system components in virtualization environments, e.g., CPU, memory, disk and network etc [5,6]. Some researchers focus the performance overheads in specific scenarios, such as server consolidation [7,8] and HPC environment [9]. However, to the best of our knowledge, none of them have quantified the deployment efficiency for typical server applications and HPC applications under different deployment strategies.…”
Abstract. Virtualization technology plays an important role in modern data center, as it creates an opportunity to improve resource utilization, reduce energy costs, and ease server management. However, virtual machine deployment issues arise when allocating virtual machines into single or multiple physical servers. In this paper, we explore the performance and scalability issues for virtual machine deployment in a virtualized data center. We first evaluate the image scalability when allocating multiple VMs per physical server using four typical servers in data center. Then we investigate how the overall efficiency will be affected when deploying M virtual machines into N physical machines with different deployment strategies. Experimental results show that: (i) There is a resource bottleneck when deploying single type virtual machine server into single physical server, except for composite workloads. (ii) More physical machines do not always benefit for some specific applications to support a fixed number of virtual machines. (iii) MPI and network communication overheads affect the deployment efficiency seriously.
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 15211The contribution was presented at PDP 2015:
“…Noting that virtualization adds computational overhead, as we will describe in Chapter III, others have studied the performance of virtualized applications [5], [19][20][21][22][23][24]; some of them specifically studied scientific applications [20][21][22][23][24][25]. For example, in [20], the authors evaluate the performance impact of Xen on different parallel application benchmarks.…”
Section: Ii1 Performance Of Scientific Applications On Virtualized Smentioning
confidence: 99%
“…In [23], they use some popular parallel benchmarks to evaluate the overhead of Xen. They use more low-level profiling details such as the number of cache misses.…”
Section: Ii1 Performance Of Scientific Applications On Virtualized Smentioning
confidence: 99%
“…A drawback with virtualization is that it adds computational overhead [5,[20][21][22][23][24][25]. For scientific applications in particular, virtualization has been shown to result in a significant performance penalty.…”
Section: Iii2 Benefits and Drawbacks Of Virtualizationmentioning
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