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Performance Evaluation of Container-based Virtualization for High Performance Computing Environments
Miguel G. Xavier, Marcelo V. Neves, Fabio D. Rossi, Tiago C. Ferreto, Timoteo Lange, Cesar A. F. De Rose
miguel.xavier@acad.pucrs.br
Faculty of Informatics, PUCRSPorto Alegre, Brazil
February 27, 2013
Outline• Introduction• Container-based Virtualization• Evaluation• Conclusion
Introduction• Virtualization
• Hardware independence, availability, isolation and security• Better manageability• Widely used in datacenters/cloud computing• Total cost of ownership is reduced
• HPC and Virtualization • Usage scenarios
• Better resource sharing• Custom environments
• However, hypervisor-based technologies in HPC environments has traditionally been avoided
Container-based Virtualization• A lightweight virtualization layer • Non virtualized drivers• Linux-Vserver, OpenVZ and LXC
Evaluation• Experimental Environment
• Cluster composed by 4 nodes • Two processors with 8 cores (without threads)• 16GB of memory
• Evaluations• Analyzing the best results of performance
• Through micro-benchmarks (such as CPU, disk, memory, network) in a single node
• Through macro-benchmarks (such as HPC)
• Analyzing the best results of isolation• Through IBS benchmark
CPU Evaluation
• All of Container-based systems obtained performance results similar to native
• No influence of the different CPU schedulers when a single CPU-intensive process is run in a single processor
• Xen presents a average overhead of 4.3%
LINPACK Benchmark (source: http://www.netlib.org/linpack/)
Memory Bandwidth Evaluation
STREAM Benchmark (source: https://www.cs.virginia.edu/stream/)
• Container-based systems have the ability to return unused memory to the host and other containers
• Xen presented 31% of performance overhead when compared to the native throughput
Disk Evaluation
IOZone Benchmark (source: https://www.iozone.org)
• LXC and Linux-VServer use the ”deadline” linux scheduler
• OpenVZ uses CFQ scheduler in order to provide the container disk priority functionality
• Xen uses virtualized drivers which are not able to achieve a high performance yet
Network Evaluation
NETPIPE Benchmark (source: http://www.scl.ameslab.gov/netpipe/)
• Xen obtained the worst performance among the virtualization systems probably due to network driver virtualized
HPC Evaluation
NAS-MPI Benchmark (source: http://www.nas.nasa.gov/publications/npb.html)
• At this moment, is possible to observe that all container-based systems slightly exceeds the native performance
• All HPC benchmarks while performed on Xen suffered even more overheads by reason of the network penalties
Isolation
Isolation Benchmark Suite (source: http://web2.clarkson.edu/class/cs644/isolation/
• The results represent how much the applications performance is impacted by different stress tests in another vm/container
• DNR means that application was not able to run• All of Container-based systems had some impact in isolation
LXC OpenVZ Vserver Xen
CPU 0 0 0 0
Memory Bomb 88,2% 89,3% 20,6% 0,9%
Disk Stress 9% 39% 48,8% 0
Fork Bomb DNR DNR DNR 0
Network Receiver 2,2% 4,5% 13,6% 0,9%
Network Sender 10,3% 35,4% 8,2% 0,3%
Conclusions• All container-based systems have a near-native performance of CPU, memory,
disk and network
• The only resource that could be successfully isolated was CPU. All three systems showed poor performance isolation for memory, disk and network
• Since the HPC applications were tested, so far, LXC demonstrates to be the most suitable of the container-based systems for HPC due its use facilities and management
Thank you!
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