Performance Analysis of Virtualization for

High Performance ComputingA Practical Evaluation of Hypervisor Overheads

Matthew Cawood University of Cape Town

Overview

1. Background

2. Research Objectives

3. HPC

4. Virtualization

5. Performance Tuning

6. The Cloud Cluster

7. Benchmarks

8. Results

9. Conclusions

1. Background

• BSc (Eng) final year research project

• CHPC Advanced Computer Engineering (ACE) Lab

• Cloud Cluster is currently being commissioned

• Research focused on evaluating the hardware and

software configurations

2. Research Objectives

1. Present an in-depth report on the current technologies being developed in the field of High Performance Computing.

2. Provide a quantitative performance analysis of the costs associated with Virtualization, specifically in the field of HPC.

3. High Performance Computing

• HPC data centres are rapidly growing in size and complexity

• Currently emphasis is placed on improving efficiency and utilization

• Wide selection of applications/requirements

• Bioinformatics

• Astrophysics

• Simulation

• Modelling

4. Virtualization

5. Performance Tuning

•Host memory reservation of Linux huge pages•KVM vCPU pinning to improve NUMA cell awareness

6. The Cloud Cluster

Compute Nodes:• 2x Intel Xeon E5-2690, 20MB L3 cache,

2.90 GHz

• 256GB, DDR3-1600, CL11

• Mellanox ConnectX-3 VPI FDR 56Gbps HCA

• Gigabit Ethernet NIC

Switch Infrastructure:

• Mellanox SX6036 FDR 36 port Infiniband Switch

6. The Cloud Cluster

• CentOS 6.4

• OFED 2.0 (with SR-IOV)

• OpenNebula 4.2

7. Performance Benchmarks

• HPC Challenge• HPLinpack

• MPI Random Access

• STREAM

• Effective bandwidth & latency

• OpenFOAM• 7 million cell, 5 millisecond transient simulation

• snappyHexMesh

8. Results

8.1 Software ComparisonHPLinpack throughput comparison of compiler selection

8.2 Single Node Evaluation

HPLinpack throughput efficiency of virtual machines

MPI Random Access Performance

STREAM Memory Bandwidth

8.3 Cluster EvaluationHPLinpack throughput efficiency of virtual machines

8.3 Cluster EvaluationOpenFOAM runtime efficiency of virtual machines

8.4 Interconnect Evaluation

Typical Verbs Latency of virtual machines Typical IPoIB Latency of virtual machines

Native Verbs Vs. IP over Infiniband

8.5 Supplementary Tests

Intel® Hyper-threading

HPLinpack throughput

8.5 Supplementary Tests

Virtual machine Scaling

OpenFOAM runtime

9. Conclusions

• KVM typically provides good performance for HPC

• Tuning is necessary to further improve performance

• Efficiency is highly application dependant

• SR-IOV for Infiniband effectively reduced I/O Virtualization overheads

• Synthetic and real-world results often contradict

Questions ?