April 4-7, 2016 | Silicon Valley

Manvender Rawat, NVIDIA

Jason K. Lee, NVIDIA

Uday Kurkure, VMware Inc.

REAL PERFORMANCE RESULTS WITH VMWARE HORIZON AND VIEWPLANNER

2

AGENDA

Overview of VMware Horizon 7 and NVIDIA GRID 2.0

Overview of VMware View Planner

Blast Protocol

Performance and Scaling Results with Knowledge Worker Workloads

Blast Extreme (GPU) vs. Blast Extreme (CPU ) vs PCoIP

3

INTRODUCTION

4

VMWARE HORIZON WITH NVIDIA GRID

5

Server

Hypervisor

Virtual

PC

Virtual

Workstation

Virtual

PC

Virtual

Workstation

HOW DOES NVIDIA GRID WORK? Virtual

PC

NVIDIA

GPU

H.264 Encode

Virtual

Workstation

NVIDIA Graphics

Driver

NVIDIA Quadro

Driver

NVIDIA GRID vGPU manager

NVIDIA Graphics

Driver

NVIDIA Graphics

Driver

NVIDIA Quadro

Driver

NVIDIA Quadro

Driver

vGPU vGPU vGPU vGPU vGPU vGPU

CPUs NVIDIA

GPU

Hard

ware

Vir

tualizati

on L

ayer

6

HOW IT WORKS TODAY: PCoIP

CLIENT

Render

Kybd/Mse

SERVER with GRID GPU

Capture

Encode

IP Network

CPU NIC

GRID GPU WORKLOAD

NON GPU WORKLOAD

Decode

Render

7

NVIDIA BLAST EXTREME ACCELERATION

CLIENT

Render

Kybd/Mse

SERVER with GRID GPU

Capture

Encode

IP Network

CPU NIC

GRID GPU WORKLOAD

NON GPU WORKLOAD

Decode

Render

8

CPU BASED CAPTURE & ENCODE PIPELINE

Load App Execute

CPU workload

Load GPU data in FB

Execute GPU

workload

Transfer output to sys-mem

Transfer image to sys-mem

Encode Packetize

& transmit

CPU GPU CPU

Capture Display

Encode

• Increased CPU workload

• Limited Scalability

• Multiple Memory Transfers

9

Load App

GPU BASED CAPTURE & ENCODE PIPELINE Execute

CPU workload

Load GPU data in FB

Execute GPU

workload

Capture Display

Packetize &

transmit Encode Encode Load GPU

data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode Encode Load GPU data in FB

Execute GPU

workload

Capture Display

Encode

• CPU workload offloaded to GPU

• Increased Scalability

• Reduced Memory Transfers

CPU GPU

10

CHALLENGES IN PERFORMANCE BENCHMARKING

Selection of Workloads/Applications

Automation

Performance Metrics

Scaling

11

BENCHMARKING FRAMEWORK VIEWPLANNER

Simplicity: Ease of use - Simple Web Interface

Expandability: Easily Add New Workloads

Elasticity: Ease of Scaling with View and VP

12

BENCHMARKING WITH VIEWPLANNER

Select the Workload Applications

Provision the desired number of Desktop Virtual Machines with View and ViewPlanner

Automatically Launch the Horizon Clients to Connect with the Desktops

Automatically Start the workload on each of the desktop VMs

Measure the Response times on the remote clients

Do the analysis on Response Times and Resource Utilization

Do the Scaling Experiments

13

VMWARE VIEWPLANNER

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USER EXPERIENCE AND RESOURCE UTILIZATION

User Experience in ViewPlanner is defined by

Frames per Second

Response Times

Measuring Resource Utilization Nvdia-smi

GPU Utilization

Built-in VMware vSphere Tools CPU Utilization

Memory Usage

Network Statistics

IO Statistics

15

PERFORMANCE METRICS MEASUREMENT

Ramp down Steady State Ramp up

For accurate results, the scores are computed

in the Steady State Range.

Exclude the Ramp Up & Ramp Down Iteration

results.

16

PARTNERS AND CUSTOMERS Using ViewPlanner

17

KNOWLEDGE WORKLOAD TEST RESULTS

18

Remote Display Protocol

Blast Extreme / PCoIP

Storage

SuperMicro SYS-2027GR-TRFH

Intel Xeon E5- 2690 v2 @ 3.00GHz + 2 x Nvidia GRID K1

20 cores (2 x 10-core socket) Intel IvyBridge

256 GB RAM

SuperMicro SYS-2028GR-TRT Intel Xeon E5-2698 v3 @ 2.30GHz + 2 x Nvidia GRID M60

32 cores (2 x 16-core socket) Intel Haswell

256 GB RAM

Virtual Client VMs

• 64-bit Win7 (SP1)

• 4vCPU, 4 GB RAM

• View Client 4.0

Virtual VDI desktop VMs

• 64-bit Win7 (SP1)

• 6vCPU, 14 GB RAM, 50GB HD

• Horizon View 7.0 agent

NVIDIA TEST SETUP

19

ADOBE PHOTOSHOP OPENGL WORKLOAD OVERVIEW

20

Scaling 1VM to 48 VMs

ADOBE PHOTOSHOP OPENGL WORKLOAD WORKLOAD

3D intensive app

21

AUTOCAD BENCHMARK – USER EXPERIENCE METRIC

• Assuming user experience is FPS on our NVIDIA AutoCAD benchmark

• Only one measurement at the moment

• For AutoCAD anything higher than 20 FPS is awesome but users generally don’t notice the difference once you exceed 30 FPS.

• But once you drop below 10 FPS, the software is going to feel very sluggish and become unusable by the time you hit 5 FPS.

• 20 fps above is good – Autodesk claim this is minimum UX threshold.

• Below 10fps – sluggish

• 5 fps – unusable

22

AUTOCAD WORKLOAD HOST UTILIZATION

• The AutoCAD benchmark doesn’t show rapid pixels moving or doesn’t contains huge pixels on the screen, NVEnc encoder didn’t utilize(around 50% during all benchmark)

• Both case Blast Extreme(NVEnc GPU) and PCoIP enabled hosts are show similar CPU host utilization

• Very different case compare with ESRI ArcGIS

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Host CPU utilization, NVEnc vs PCoIP Total 10913 vs 10570 : Very similar

nvenc pcoip NvEnc Encoder

Low

er

is b

ett

er

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AUTOCAD WORKLOAD 32 VM GPU UTILIZATION

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Uti

lizat

ion

%

Time

GPU utilization GPU memory utilization

24

BLAST EXTREME(GPU) AVERAGE FPS (UX)

• The host DOES NOT saturate CPU resource 100% with 32 VMs current launching we can scale more than 32. Planning testing go further.

• GPU isn’t bottleneck for scaling.

36.81 36.49

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

NvEnc(build3) PCoIP

FPS

AutoCAD AVG FPS, M60-1Q 32VMs Blast Extreme(GPU) vs PCoIP

Hig

her

is b

ett

er

Minimum fps for UX

25

Remote Display Protocol

Blast Extreme / PCoIP

Storage

Dell R730 – Intel Haswell CPUs + 2 x NVidia GRID M60

24 cores (2 x 12-core socket) E5-2680 V3

384 GB RAM

Dell R730 – Intel Haswell CPUs + 2 x NVidia GRID M60

24 cores (2 x 12-core socket) E5-2680 V3

384 GB RAM

Virtual Client VMs

• 64-bit Win7 (SP1)

• 1 vCPU, 2 GB RAM,

• View Client 4.0

Virtual VDI desktop VMs

• 64-bit Win7 (SP1)

• 2vCPU, 4 GB RAM, 40GB HD

• Horizon View 7.0 agent

VMware Test-bed for NVIDIA GRID on Horizon View

26

REMOTE DISPLAY PROTOCOLS IN HORIZON

VMware's Remote Display Protocol Blast Extreme

Based on a Standard

H.264

Exploits NVIDIA GPU Capabilities for Encoding

Clients can use any GPU or CPU for decoding.

Blast Extreme (GPU) : Blast GPU

Uses GPU assist for H264 Encoding

NVidia Tesla M60 Virtual Grid in Enterprise Cloud

Blast Extreme (CPU) : Blast CPU

Does not use hardware GPU assist for H264 Encoding

PCoIP and Microsoft RDP

CONFIDENTIAL 2

6

27

KNOWLEDGE WORKER APPS

Knowledge Worker Applications in ViewPlanner 3.6

Office Apps: Word, Excel, PowerPoint, Outlook

Adobe Acrobat Reader, Firefox, 7zip

Windows Media Player

28

VIEWPLANNER QOS METHODOLOGY

Operations are split in Groups

Group A:Interactive/fast-running CPU bound operations

User expects minimal latencies

E.g. Modifying Word, Excel Operations

Group B:Long-running slow IO bound operations

User can tolerate longer latencies

E.g. Saving PowerPoint, Zip/UnZip

QoS Criteria:

Group A:95th %ile : 0.70s ( <= 1.0 s)

Group B: 95th %ile: 2.3s ( <= 6.0s)

4/20/2016

29

VP MEASUREMENTS ON REMOTE CLIENTS

Measures True Remote User Experience

Measurements are done on remote clients

Latency Measurement

Each Operation’s Start Time and End Time are noted on the Remote Client as the Remote Client sees it.

Frames/Second Metric for Video Workload

Frames Seen by the remote client are counted

4/20/2016

30

KNOWLEDGE WORKER WORKLOAD

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.00 8.00 16.00 32.00 48.00 64.00

Norm

alized L

ate

ncie

s w

rt P

CoIP

Seconds

#of VMs

GROUP A LATENCIES Lower is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP

31

KNOWLEDGE WORKER WORKLOAD

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

1.00 8.00 16.00 32.00 48.00 64.00

Norm

alized L

ate

ncie

s w

rt P

CoIP

Seconds

#of VMs

GROUP B LATENCIES Lower is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP

32

HEAVY VIDEO WORKLOAD

33

NVIDIA GPU SPECIFICATIONS

NVidia GPU Tesla M60

H264 1080p30 Streams: 36

CUDA Cores: 4096/GPU(2x2048)

Concurrent Users/GPU: 2-32

VMware Testbed Configuration

vGPU Type: GRID M60-0q

GPUs/Board: 2

# of Boards: 2

CONFIDENTIAL 3

3

34

HEAVY VIDEO WORKLOAD Video 720P

2 Minute Duration,10 Iterations

Scaling

8 VMs to 48 VMs

Performance Metrics

Frames/Second

CPU Utilization

GPU

Decodes Video Streams

Encodes Blast Extreme Protocol

CONFIDENTIAL 3

4

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VIDEO WORKLOAD

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8 16 32 48

Norm

alized F

PS w

rt P

CoIP

Cum

ula

tive F

PS

#of VMs

Cumulative Frames/Second Higher is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP Linear (BlastGPU/PCoIP)

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VIDEO WORKLOAD

0.00

0.50

1.00

1.50

2.00

2.50

3.00

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8 16 32 48

Norm

alized A

vera

ge C

PU

Uti

l. w

rt

PC

oIP

%C

PU

Uti

lizati

on

#of VMs

Average CPU Utilization Lower is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP Linear (BlastGPU/PCoIP)

37

BLAST EXTREME WITH NVIDIA GPUS TAKEWAYS

Better User Experience

More Frames/Second

Lower Latencies: Better Response Times

Lower CPU Utilizatio

Better Scalability

38

RELATED SESSIONS

TUTORIAL S6595 - Benchmarking Graphics Intensive Application on VMware Horizon 6 Using NVIDIA GRID™ vGPUs by ManVender Rawat and Lan VU

S6198 - The Latest in High Performance Desktops with VMware Horizon and NVIDIA GRID™ vGPU by Pat Lee and Luke Wignall

April 4-7, 2016 | Silicon Valley

THANK YOU

JOIN THE NVIDIA DEVELOPER PROGRAM AT developer.nvidia.com/join

40

SECTION DIVIDER OR TRANSITION SLIDE

41

BLAST EXTREME WITH NVIDIA GPUS

Blast Extreme with NVIDIA GPUS

Better User Experience

More frames/seconds

Lower Latencies ( Better Response Times)

Lower CPU Utilization

Better Scalability

42

CONTENT SLIDE: 36 PT BLACK, TREBUCHET FONT BOLD, UP TO 2 LINES MAXIMUM

Body/bullet text no longer has a bullet icon

Use 20 pt font

No sub-bullets allowed

No more than five bullets; one idea per bullet

Example of highlighted text

Subtitle: 24 pt, one line maximum

43

PHTOSHOP OPENGL WORKLOAD

44

NVIDIA BLAST EXTREME ACCELERATION

• Reduces overall latency

• Offloads CPU workload to GPU

• Increases scalability

• Improves user experience

• Lowers N/W bandwidth demand

GRID GPU

3D

HW Encoder

Framebuffer

Apps Apps

Apps

Graphics

commands

Context/Display Capture

Render Target

Front Buffer

H.264 /

H.265

streams

Remote Client