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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

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HPC Applications Performance on V100

Authors: Frank Han, Rengan Xu, Nishanth Dandapanthula.

HPC Innovation Lab. August 2017

Overview

This is one of two articles in our Tesla V100 blog series. In this blog, we present the initial benchmark results of NVIDIA® Tesla® Volta-

based V100™ GPUs on 4 different HPC benchmarks, as well as a comparative analysis against previous generation Tesla P100 GPUs.

We are releasing another V100 series blog, which discusses our V100 and deep learning applications. If you haven’t read it yet, it is

highly recommend to take a look here.

PowerEdge C4130 with V100 GPU support

The NVIDIA® Tesla® V100 accelerator is one of the most advanced accelerators available in the market right now and was launched

within one year of the P100 release. In fact, Dell EMC is the first in the industry to integrate Tesla V100 and bring it to market. As was the

case with the P100, V100 supports two form factors: V100-PCIe and the mezzanine version V100-SXM2. The Dell EMC PowerEdge

C4130 server supports both types of V100 and P100 GPU cards. Table 1 below notes the major enhancements in V100 over P100:

Table 1: The comparison between V100 and P100

PCIe

SXM2

P100

V100

Improvement

P100

V100

Improvement

Architecture

Pascal

Volta

Pascal

Volta

CUDA Cores

3584

5120

3584

5120

GPU Max Clock rate (MHz)

1329

1380

1481

1530

Memory Clock rate (MHz)

715

877

23%

715

877

23%

Tensor Cores

N/A

640

N/A

640

Tensor Cores/SM

N/A

Memory Bandwidth (GB/s)

732

900

23%

732

900

23%

Interconnect Bandwidth

Bi-Directional (GB/s)

160

300

Deep Learning (TFlops)

18.6

112

21.2

125

Single Precision (TFlops)

9.3

1.5x

10.6

15.7

1.5x

Double Precision (TFlops)

4.7

1.5x

5.3

7.8

1.5x

TDP (Watt)

250

300

V100 not only significantly improves performance and scalability as will be shown below, but also comes with new features. Below are

some highlighted features important for HPC Applications:

 Second-Generation NVIDIA NVLink™

Summary of content (8 pages)

PAGE 1
Ready Solutions Engineering Test Results HPC Applications Performance on V100 Authors: Frank Han, Rengan Xu, Nishanth Dandapanthula. HPC Innovation Lab. August 2017 Overview This is one of two articles in our Tesla V100 blog series. In this blog, we present the initial benchmark results of NVIDIA® Tesla® Voltabased V100™ GPUs on 4 different HPC benchmarks, as well as a comparative analysis against previous generation Tesla P100 GPUs.
PAGE 2
Ready Specs 2 All four V100-SXM2 GPUs in the C4130 are connected by NVLink™ and each GPU has six links. The bi-directional bandwidth of each link is 50 GB/s, so the bi-directional bandwidth between different GPUs is 300 GB/s. This is useful for applications requiring a lot of peerto-peer data transfers between GPUs.  New Streaming Multiprocessor (SM) Single precision and double precision capability of the new SM is 50% more than the previous P100 for both PCIe and SXM2 form factors.
PAGE 3
Ready Specs 3 In theory, V100 has 6x 25GB/s uni-directional links, giving 150GB/s throughput. The previous P100-SXM2 only has 4x 20GB/s links, delivering 80GB/s. The results of p2pBandwitdhtLatencyTest on both cards are in Table 3. “D/D” represents “device-to-device”, that is the bandwidth available between two devices (GPUs).
PAGE 4
Ready Specs 4 HPL TFLOPS (Higher = Better) 25.0 20.0 19.5 20.0 15.7 15.1 15.0 10.7 10.4 10.0 5.0 8.4 7.9 3.8 5.2 4.1 5.4 0.0 1 2 4 # of GPUs PCIe(ConfigG) P100 PCIe(ConfigG) V100 SXM2(ConfigK) P100 SXM2(ConfigK) V100 Figure2: HPL Multi-GPU results with V100 and P100 on C4130 configuration G and K Figure 2 shows the HPL performance on the C4130 platform with 1, 2 and 4 V100-PCIe and V100-SXM2 installed. P100’s performance number is also listed for comparison.
PAGE 5
Ready Specs 5 HPCG (NX=NY=NZ=256) GFLOP/s (Higher = better) 700 572 600 500 564 395 400 391 300 200 100 0 P100 V100 P100 PCIe(ConfigG) V100 SXM2(ConfigK) 4 GPUs Figure 3: HPCG Performance results with 4x V100 and P100 on C4130 configuration G and K HPCG, the High Performance Conjugate Gradients benchmark, is another well-known metric for HPC system ranking. Unlike HPL, its performance is strongly influenced by memory bandwidth.
PAGE 6
Ready Specs 6 Figure 4: AMBER Multi-GPU results with V100 and P100 on C4130 configuration G and K Figure 4 illustrates AMBER’s results with Satellite Tobacco Mosaic Virus (STMV) dataset. On SXM2 system (Config K), AMBER scales weakly with 2 and 4 GPUs. Even though the scaling is not strong, V100 has noticeable improvement than P100, giving ~78% increase in single card runs, and 1x V100 is actually 23% faster than 4x P100.
PAGE 7
Ready Specs 7 LAMMPS 3d Lennard-Jones melt Timsteps/s (Higher = better) 1000 922 880 900 800 700 600 513 507 500 400 300 200 100 0 P100 V100 P100 PCIe(ConfigG) V100 SXM2(ConfigK) 4 GPUs Figure 6: LAMMPS 4-GPU results with V100 and P100 on C4130 configuration G and K Figure 6 shows LAMMPS performance on both configurations G and K. We use the Lennard-Jones liquid dataset, which contains 512000 atoms, and we compiled LAMMPS with the kokkos package installed.
PAGE 8
Ready Specs 8 Figure 7: V100 Speedups on C4130 configuration G and K The C4130 server with NVIDIA® Tesla® V100™ GPUs demonstrates exceptional performance for HPC applications that require faster computational speed and highest data throughput. Applications like HPL, HPCG benefit from the additional PCIe links between CPU and GPU that are offered by Dell PowerEdge C4130 configuration G.