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Ready Solutions Engineering Test Results

the property of their respective owners. Published in the USA. Dell EMC believes the information in this document is accurate as of its publication date. The information is

subject to change without notice.

HPC Applications Performance on R740 with V100

GPUs

Authors: Frank Han, Rengan Xu, Nishanth Dandapanthula.

HPC Innovation Lab. February 2018

Overview

Not long ago, PowerEdge R740 Server was released as part of Dell’s 14

Generation server portfolio. It is a 2U Intel SkyLake based

rack mount server and provides the ideal balance between storage, I/O and application acceleration. Besides VDI and Cloud, the server

is also designed for HPC workloads. Compared to the previous R730 server, one of the major changes on GPU support is that, R740

supports up to 3 double width cards, which is one more than what R730 could support. This blog will focus on the performance of a

single R740 server with 1, 2 and 3 Nvidia Tesla V100-PCIe GPUs. Multiple cards scaling number for HPC applications like High-

Performance Linpack (HPL), High Performance Conjugate Gradients benchmark (HPCG) and Large-scale Atomic/Molecular Massively

Parallel Simulator (LAMMPS) will be presented.

Table1: Details of R740 configuration and software version

Processor

2 x Intel(R) Xeon(R) Gold 6150 @2.7GHz, 18c

Memory

384G(12*32G@2666MHz)

Local Disk

480G SSD

Operating System

Red Hat Enterprise Linux Server release 7.3

GPU

Nvidia Tesla V100-PCIe

CUDA Driver

387.26

CUDA Toolkit

9.1.85

Processor Settings > Logical Processors

Disabled

System Profiles

Performance

High Performance Linpack (HPL)

Figure 1: HPL Performance and efficiency with R740

Summary of content (5 pages)

PAGE 1
Ready Solutions Engineering Test Results HPC Applications Performance on R740 with V100 GPUs Authors: Frank Han, Rengan Xu, Nishanth Dandapanthula. HPC Innovation Lab. February 2018 Overview Not long ago, PowerEdge R740 Server was released as part of Dell’s 14th Generation server portfolio. It is a 2U Intel SkyLake based rack mount server and provides the ideal balance between storage, I/O and application acceleration. Besides VDI and Cloud, the server is also designed for HPC workloads.
PAGE 2
Ready Specs 2 Figure 1 shows HPL performance and efficiency numbers. Performance data increases with multiple GPUs nearly linearly. Efficiency line isn’t flat, the peak 67.8% appears with the 2-card, which means configuration with 2 GPUs is the most optimized one for HPL. Number of 1 and 3 cards are about 7% lower than 2 card and they are affected by different factors:  For the 1 card case, this GPU based HPL application designs to bond CPU and GPU.
PAGE 3
Ready Specs 3 Figure 2: HPCG Performance with R740 As shown in Figure 2, comparing with dual Xeon 6150 CPU only performance, single V100 is already 3 times faster, 2 V100 is 8 times and 3 V100 (CPU only node vs GPU node) is nearly 12 times. Just like HPL, HPCG is also designed for a large scale, so single card performance isn’t as efficient as multiple cards on HPCG. But unlike HPL, 3 card performance on HPCG is linearly scaled. It is 1.
PAGE 4
Ready Specs 4 Figure 3: LAMMPS Performance with R740 The LAMMPS version used for this testing is 17Aug2017, which is the latest stable version at the time of testing. The testing dataset is in.intel.lj, which is the same one in all pervious GPU LAMMPS testing and it can be found here. With the same parameters set from previous testing, the initial values of space were x=4, y=z=2, the simulation executes with 512k atoms. Weak scaling obvious as timesteps/s number of 2 and 3 cards only 1.5 and 1.
PAGE 5
Ready Specs 5