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© 2014 VMware Inc. All rights reserved. 
Virtualized High Performance Computing 
with Mellanox FDR InfiniBand and RoCE 
on VMware ESXi 5.5 
Initial Performance Results 
Josh Simons 
Office of the CTO 
VMware, Inc. 
August 26, 2014
High Performance Computing 
2 
“High Performance Computing refers to the practice of aggregating computing power 
in a way that delivers much higher performance than one could get out of a typical desktop or 
workstation in order to solve large problems in science, engineering, or business.” [1] 
Commercial: 
 Oil exploration 
 Pharmaceutical design 
 Financial and economic modeling 
 Advanced data visualization 
HPC Applications 
Science and Engineering: 
 Atmosphere, earth, environment 
 Bioscience, biotechnology, genetics 
 Physics - applied, nuclear, particle, condensed matter; 
 Electrical engineering, circuit design, microelectronics 
 Mechanical engineering - from prosthetics to spacecraft 
[1] G. Sravanthi, B. Grace. A Review of High Performance Computing. IOSR Journal of 
Computer Engineering, vol. 16, pp36-43, 2014
VMware vCAC API 
Secure Private Cloud for HPC 
Research Group 1 Research Group m 
Users IT 
Public/Hybrid 
Clouds 
Programmatic 
Control and 
Integrations 
VMware vCloud Automation Center 
User Portals Blueprints 
Security 
Research Cluster 1 Research Cluster n 
NSX 
VMware 
vCenter Server 
VMware 
vCenter Server 
VMware 
vCenter Server 
VMware vSphere VMware vSphere VMware vSphere 
3
HPC Workloads 
• Scientific or technical workloads 
• Often floating-point intensive 
• Often parallel 
• Often storage intensive 
• Run on server-class systems 
4 
Throughput Workloads MPI Oriented Workloads
FDR InfiniBand Read Latency 
5 
2048 
1024 
512 
256 
128 
64 
32 
16 
8 
4 
2 
1 
0.5 
Half Roundtrip Latency (μs) 
Message Sizes (Bytes) 
Native 
ESXi 5.5 
ESXi 5.5 with 
SR-IOV 
3 
2.5 
2 
1.5 
1 
0.5 
Four-node HP cluster 
DL380 G8 nodes 
128 GB, 3.0 GHz 
FDR IB/RoCE HCAs 
12-port FDR switch 
ESX 5.5u1
RoCE Read Latency 
6 
2048 
1024 
512 
256 
128 
64 
32 
16 
8 
4 
2 
1 
0.5 
Half Roundtrip latency (us) 
3 
2.5 
2 
Native 
ESXi 5.5 0.5 
Message Size (Bytes) 
1.5 
1
HPC Challenge Benchmark (HPCC) with FDR IB 
7 
100.00% 
80.00% 
60.00% 
40.00% 
20.00% 
0.00% 
HPCC Virtual to Native Ratios 
(higher is better) 
n4np4 n4np8 
n4np16 n4np32 
n4np64
NAMD Molecular Dynamics with FDR IB 
1 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0 
NAMD Benchmarks Native to Virtual Ratios 
(Higher is Better) 
Apoa1 f1atpase 
n4np4 n4np8 
n4np16 n4np32 
n4np64 
8
LAMMPS Molecular Dynamics with FDR IB 
CONFIDENTIAL 9 
1 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0 
LAMMPS Benchmarks Native to Virtual Ratios 
(Higher is Better) 
Atomic Fluid Bulk Copper Bead-Spring Polymer 
n4np4 
n4np8 
n4np16 
n4np32 
n4np64
To Learn More: 
• Office of the CTO Expo Booth (2-6pm) 
• How to Engage with Your Engineering, Science, 
and Research Groups About Virtualization and 
Cloud Computing 
Thursday 10:30-11:30 Moscone West 2003 
Josh Simons, simons@vmware.com

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Virtualized high performance computing with mellanox fdr and ro ce

  • 1. © 2014 VMware Inc. All rights reserved. Virtualized High Performance Computing with Mellanox FDR InfiniBand and RoCE on VMware ESXi 5.5 Initial Performance Results Josh Simons Office of the CTO VMware, Inc. August 26, 2014
  • 2. High Performance Computing 2 “High Performance Computing refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop or workstation in order to solve large problems in science, engineering, or business.” [1] Commercial:  Oil exploration  Pharmaceutical design  Financial and economic modeling  Advanced data visualization HPC Applications Science and Engineering:  Atmosphere, earth, environment  Bioscience, biotechnology, genetics  Physics - applied, nuclear, particle, condensed matter;  Electrical engineering, circuit design, microelectronics  Mechanical engineering - from prosthetics to spacecraft [1] G. Sravanthi, B. Grace. A Review of High Performance Computing. IOSR Journal of Computer Engineering, vol. 16, pp36-43, 2014
  • 3. VMware vCAC API Secure Private Cloud for HPC Research Group 1 Research Group m Users IT Public/Hybrid Clouds Programmatic Control and Integrations VMware vCloud Automation Center User Portals Blueprints Security Research Cluster 1 Research Cluster n NSX VMware vCenter Server VMware vCenter Server VMware vCenter Server VMware vSphere VMware vSphere VMware vSphere 3
  • 4. HPC Workloads • Scientific or technical workloads • Often floating-point intensive • Often parallel • Often storage intensive • Run on server-class systems 4 Throughput Workloads MPI Oriented Workloads
  • 5. FDR InfiniBand Read Latency 5 2048 1024 512 256 128 64 32 16 8 4 2 1 0.5 Half Roundtrip Latency (μs) Message Sizes (Bytes) Native ESXi 5.5 ESXi 5.5 with SR-IOV 3 2.5 2 1.5 1 0.5 Four-node HP cluster DL380 G8 nodes 128 GB, 3.0 GHz FDR IB/RoCE HCAs 12-port FDR switch ESX 5.5u1
  • 6. RoCE Read Latency 6 2048 1024 512 256 128 64 32 16 8 4 2 1 0.5 Half Roundtrip latency (us) 3 2.5 2 Native ESXi 5.5 0.5 Message Size (Bytes) 1.5 1
  • 7. HPC Challenge Benchmark (HPCC) with FDR IB 7 100.00% 80.00% 60.00% 40.00% 20.00% 0.00% HPCC Virtual to Native Ratios (higher is better) n4np4 n4np8 n4np16 n4np32 n4np64
  • 8. NAMD Molecular Dynamics with FDR IB 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 NAMD Benchmarks Native to Virtual Ratios (Higher is Better) Apoa1 f1atpase n4np4 n4np8 n4np16 n4np32 n4np64 8
  • 9. LAMMPS Molecular Dynamics with FDR IB CONFIDENTIAL 9 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 LAMMPS Benchmarks Native to Virtual Ratios (Higher is Better) Atomic Fluid Bulk Copper Bead-Spring Polymer n4np4 n4np8 n4np16 n4np32 n4np64
  • 10. To Learn More: • Office of the CTO Expo Booth (2-6pm) • How to Engage with Your Engineering, Science, and Research Groups About Virtualization and Cloud Computing Thursday 10:30-11:30 Moscone West 2003 Josh Simons, simons@vmware.com

Editor's Notes

  1. This architectural approach offers the most value to both end-users and IT providers. It takes the approach described on the previous slide and wraps it in a private cloud infrastructure. This adds self-provisioning, which allows individual departments or researchers/engineers to instantiate the resources they need for their project w/o needing to wait for the IT department to create the resource for them. When an end-user instantiates a virtual HPC cluster, it is done using a blueprint which specifies the required machine attributes, the number of machines, and the software that should be included in the VM, including operating system and middleware – which allows full customization to their requirements. By the same token, the blueprint approach also allows the central IT group to enforce corporate IT requirements by including those in the blueprint as well – for example, security and data protection policies. Once created, these private clouds can be burst to the VMware Hybrid Cloud or to partner offerings to create seamless and secure extensions to their own on-premise resources. One specific point to note about this model: The assumption is that end-users would continue to run their usual HPC batch schedulers within their virtual HPC clusters. This approach allows them to continue to interact with their HPC resources in a familiar way while at the same time allowing DRS and other components to dynamically manage the placement and priority of workload on the underlying physical resources.