nvidia grid for vdi: how to design and monitor your...

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BETTER DATA. BETTER DECISIONS. Session S4686 - NVIDIA GRID for VDI How To Design And Monitor Your Implementation Presenters: Florian Becker [email protected] - @florianbecker Sr. Director Strategic Alliances Ben Murphy [email protected] - @TheBenMurphy Sr. Applications Engineer

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Page 1: NVIDIA GRID for VDI: How To Design And Monitor Your ...on-demand.gputechconf.com/.../S4686-nvidia-grid-vdi... · NVIDIA GRID for VDI: How To Design And Monitor Your Implementation

BETTER DATA. BETTER DECISIONS. ℠

Session S4686 - NVIDIA GRID for VDI How To Design And Monitor Your Implementation

Presenters:

Florian Becker – [email protected] - @florianbecker

Sr. Director Strategic Alliances

Ben Murphy – [email protected] - @TheBenMurphy

Sr. Applications Engineer

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Agenda

• Desktop and App Virtualization

• Virtualization Challenges and Top10 mistakes

• Implementation Best Practices

• Accurate Desktop and GPU Assessments

• vGPU Planning

• Post Deployment Monitoring

• Q&A

Copyright 2014 Lakeside Software, Inc. 2

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Desktop and App Virtualization

“Desktop virtualization is software technology that separates the desktop environment and associated application software from the physical client device that is used to access it.”

Copyright 2014 Lakeside Software, Inc. 3

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Desktop and App Virtualization

Key Concepts

• Centralization of Apps and Data

• High performance remoting protocols

• Fewer instances to manage

Benefits

• “Secure by Design”

• Device independence

• Reduction of cost / complexity

Copyright 2014 Lakeside Software, Inc. 4

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Desktop and App Virtualization Challenges

• 3D Apps - > GPU Virtualization!

• Environments often not built with knowledge of user needs and behavior

• Transition is difficult

Copyright 2014 Lakeside Software, Inc. 5

No virtualization project has ever been successful unless it is based on sound data and actual user needs.

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Top 10 Virtualization Mistakes according to Citrix Article CTXS126190 (2012)

• 10. Failure to consider network impact • 9. Lack of user profile strategy • 8. Lack of App Virtualization Strategy • 7. Improper Resource Allocation • 6. Failure to optimize Anti Virus • 5. Failure to manage boot storms • 4. Failure to optimize virtual desktops • 3. Insufficient Cache • 2. Improper Controller Configuration • 1. Improper Storage Design

Copyright 2014 Lakeside Software, Inc. 6

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Implementation Best Practices

Copyright 2014 Lakeside Software, Inc. 7

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Desktop Transformation Methodology

Copyright 2014 Lakeside Software, Inc. 8

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Desktop Transformation Assessment

• Determine Business Priorities

• Group Users that drive common requirements • Resource Consumption?

• Application Sets?

• Location / Network?

• Security?

• Business Impact?

• Determine “Time to Value”

• Make a plan

Copyright 2014 Lakeside Software, Inc. 9

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Traditional Methods • Error Prone

• Time Consuming

10 Copyright 2014 Lakeside Software, Inc.

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GPU Virtualization

• Dedicated GPU • Shared GPU

Copyright 2014 Lakeside Software, Inc. 11

Page 12: NVIDIA GRID for VDI: How To Design And Monitor Your ...on-demand.gputechconf.com/.../S4686-nvidia-grid-vdi... · NVIDIA GRID for VDI: How To Design And Monitor Your Implementation

Popular Virtualization Technologies

Copyright 2014 Lakeside Software, Inc. 12

Page 13: NVIDIA GRID for VDI: How To Design And Monitor Your ...on-demand.gputechconf.com/.../S4686-nvidia-grid-vdi... · NVIDIA GRID for VDI: How To Design And Monitor Your Implementation

vGPU Profiles

Copyright 2014 Lakeside Software, Inc. 13

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Copyright 2014 Lakeside Software, Inc. 14

Quadro K6000 2880 CUDA cores

12GB

Quadro K5000 1536 CUDA cores

4GB

Quadro K4000 768 CUDA cores

3GB

Quadro K2000 384 CUDA cores

2GB

Quadro K600 192 CUDA cores

1GB

Quadro 410 192 CUDA cores

512MB

GRID K2 2x 1536 CUDA cores

2x 4GB

GRID K1 4x 192 CUDA cores

4x 4GB

GPU Passthrough

NVIDIA

Graphics

Cards

GRID K260Q 768 CUDA cores avg

and 2 GB per user

GRID K240Q 384 CUDA cores avg

and 1GB per user

GRID vGPU

GRID K140Q 192 CUDA cores avg

and 1GB per user

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Using Lakeside SysTrack for virtual GPU Assessments

Copyright 2014 Lakeside Software, Inc. 15

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SysTrack Technology

Copyright 2014 Lakeside Software, Inc. 16

Systems

Infrastructure

Agent-based with service User mode (no kernel mode) Silent to user Offline and Online 1000 data points per second 1% CPU, 40-50 MB in mem

60 – 80 MB JET/SQL Lite DB Only 100 KB per system

uploaded per day Scalable to 1 Million Systems

Platforms

SysTrack’s Business Intelligence is built on a massively scalable, patented data mining infrastructure of distributed systems

Intelligence

SysT

rack

Inventory

Software

Hardware

User Experience

Health

Application Faults

Performance

Management

Security

Change Control

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Technology Implementation

• Agent-based • Based on TCP/IP • Utilizes local Jet or SQL database

on each leaf node managed system • Only 100K of storage per leaf node

condensed upward to top level • Less than 0.5% CPU utilization • ~ 20 MB user-mode memory • Less than 100 kB/day network per

endpoint • Runs as a service with no kernel

components (cannot blue screen system)

Copyright 2014 Lakeside Software, Inc. 17

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Demo

Copyright 2014 Lakeside Software, Inc. 18

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Go and See

• S4278 - How to Virtualize 3D Workstations? High-End Graphics for VDI in 10 Easy Steps • Mayunk Jain (Citrix Systems, Inc.)

• Praveen Prakash (Citrix Systems, Inc.)

• Wednesday, March 26th

• Room LL20D (double check!)

Copyright 2014 Lakeside Software, Inc. 19

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Next Steps – Q & A

• Engage a Lakeside Partner, your NVIDIA solutions architect or your virtualization vendor to perform an assessment

• Visit us on the web www.lakesidesoftware.com

• Contact us • [email protected]

[email protected]

Copyright 2014 Lakeside Software, Inc. 20