REAL PERFORMANCE RESULTS WITH VMWARE HORIZON AND VIEWPLANNER - - PowerPoint PPT Presentation

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REAL PERFORMANCE RESULTS WITH VMWARE HORIZON AND VIEWPLANNER - - PowerPoint PPT Presentation

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April 4-7, 2016 | Silicon Valley REAL PERFORMANCE RESULTS WITH VMWARE HORIZON AND VIEWPLANNER Manvender Rawat, NVIDIA Jason K. Lee, NVIDIA Uday Kurkure, VMware Inc. Overview of VMware Horizon 7 and NVIDIA GRID 2.0 Overview of VMware View

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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

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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

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INTRODUCTION

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VMWARE HORIZON WITH NVIDIA GRID

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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

Hardware Virtualization Layer

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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

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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

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CPU BASED CAPTURE & ENCODE PIPELINE

Load App Execute CPU workload Load GPU data in FB Execute GPU workload Transfer

  • utput 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
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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

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CHALLENGES IN PERFORMANCE BENCHMARKING

Selection of Workloads/Applications Automation Performance Metrics Scaling

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BENCHMARKING FRAMEWORK VIEWPLANNER

Simplicity: Ease of use - Simple Web Interface Expandability: Easily Add New Workloads Elasticity: Ease of Scaling with View and VP

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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

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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
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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.

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PARTNERS AND CUSTOMERS

Using ViewPlanner

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KNOWLEDGE WORKLOAD TEST RESULTS

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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

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ADOBE PHOTOSHOP OPENGL WORKLOAD OVERVIEW

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Scaling 1VM to 48 VMs

ADOBE PHOTOSHOP OPENGL WORKLOAD WORKLOAD

3D intensive app

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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
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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
  • 10

20 30 40 50 60 70 80 90 100 23:10:57 23:11:59 23:13:01 23:14:03 23:15:05 23:16:07 23:17:09 23:18:11 23:19:12 23:20:14 23:21:16 23:22:18 23:23:20 23:24:22 23:25:24 23:26:25 23:27:27 23:28:29 23:29:31 23:30:33 23:31:35 23:32:37 23:33:39 23:34:40 23:35:42 23:36:44 23:37:46 23:38:48 23:39:50 23:40:52 23:41:54 23:42:56 23:43:58 23:45:00 23:46:02 23:47:04 23:48:06 23:49:08 23:50:10 23:51:12 23:52:14 23:53:16 23:54:18 23:55:20 23:56:22 23:57:23 23:58:25 23:59:27 0:00:29 0:01:31 0:02:32 0:03:34 0:04:36 0:05:37 0:06:39 0:07:41 0:08:43 0:09:45 0:10:46 0:11:48 0:12:50 0:13:51

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

nvenc pcoip NvEnc Encoder

Lower is better

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AUTOCAD WORKLOAD 32 VM GPU UTILIZATION

10 20 30 40 50 60 70 80 90 100 19:54:47 19:56:48 19:58:49 20:00:51 20:02:52 20:04:53 20:06:54 20:08:56 20:10:57 20:12:58 20:15:00 20:17:01 20:19:02 20:21:04 20:23:05 20:25:06 20:27:08 20:29:09 20:31:10 20:33:11 20:35:13 20:37:14 20:39:15 20:41:17 20:43:18 20:45:19 20:47:21 20:49:22 20:51:23 20:53:24 20:55:26 20:57:27 20:59:28 21:01:29 21:03:31 21:05:32 21:07:33 21:09:35 21:11:36 21:13:37 21:15:39 21:17:40 21:19:41 21:21:42 21:23:44 21:25:45 21:27:46 21:29:48 21:31:49 21:33:50

Utilization % Time

GPU utilization GPU memory utilization

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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

Higher is better

Minimum fps for UX

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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

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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

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KNOWLEDGE WORKER APPS

Knowledge Worker Applications in ViewPlanner 3.6 Office Apps: Word, Excel, PowerPoint, Outlook Adobe Acrobat Reader, Firefox, 7zip Windows Media Player

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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

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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

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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 Normalized Latencies wrt PCoIP Seconds #of VMs

GROUP A LATENCIES

Lower is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP

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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 Normalized Latencies wrt PCoIP Seconds #of VMs

GROUP B LATENCIES Lower is Better

BlastGPU BlastCPU PCoIP BlastGPU/PCoIP BlastCPU/PCoIP

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HEAVY VIDEO WORKLOAD

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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

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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

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 100 200 300 400 500 600 700 800 8 16 32 48 Normalized FPS wrt PCoIP Cumulative FPS #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 20 40 60 80 100 120 8 16 32 48 Normalized Average CPU Util. w rt PCoIP %CPU Utilization #of VMs

Average CPU Utilization

Lower is Better

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

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BLAST EXTREME WITH NVIDIA GPUS

TAKEWAYS

Better User Experience More Frames/Second Lower Latencies: Better Response Times Lower CPU Utilizatio Better Scalability

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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

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April 4-7, 2016 | Silicon Valley

THANK YOU

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

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SECTION DIVIDER OR TRANSITION SLIDE

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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
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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

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PHTOSHOP OPENGL WORKLOAD

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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