S9814 HOW GPU-ACCELERATED VIRTUAL WORKSTATIONS ENABLE MOBILITY AND - - PowerPoint PPT Presentation

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S9814 HOW GPU-ACCELERATED VIRTUAL WORKSTATIONS ENABLE MOBILITY AND - - PowerPoint PPT Presentation

S9814 HOW GPU-ACCELERATED VIRTUAL WORKSTATIONS ENABLE MOBILITY AND COLLABORATION FOR AUTODESK APPLICATIONS WHO ARE WE? Jimmy Rotella Andrew Schilling Jeremy Stroebel Sr. Solutions Architect Chief Infrastructure Officer Director of IT


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S9814 – HOW GPU-ACCELERATED VIRTUAL WORKSTATIONS ENABLE MOBILITY AND COLLABORATION FOR AUTODESK APPLICATIONS

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WHO ARE WE?

Jimmy Rotella

  • Sr. Solutions Architect

Nvidia

Andrew Schilling

Chief Infrastructure Officer CannonDesign

Jeremy Stroebel

Director of IT Browning Day Mullins Dierdof Architects

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CANNONDESIGN

  • 1,100 employees
  • 19 locations
  • Named to Fast Company’s 2019 Most

Innovative Companies List

  • #4 Position in 2018 Architect 50

Rankings

  • #6 Global Health Firm

SFMO - “Single Firm, Multi Office”

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BROWNING DAY MULLINS DIERDORF ARCHITECTS

  • 55+ employees
  • 1 office (Indianapolis, IN)
  • Architecture, Landscape

Architecture, Interior Design, and Planning Firm

  • Founded in 1967
  • Won over 150 design awards

locally and nationally

Indianapolis, IN

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CONFIGURATIONS AT A GLANCE

CannonDesign BDMD

Host Platform Cisco B200 M4 Blade Servers Dell R740 servers Nvidia GPU 1x Tesla P6 per host 4-5x Tesla P4s per host Hypervisor Stack Vmware Horizon on ESXi XenDesktop on XenServer Nvidia Virtual GPU Software Quadro Virtual Data Center Workstation Quadro Virtual Data Center Workstation Nvidia vGPU profiles 1gb, 2gb, 4gb 2 GB (P4-2Q) CPU 2-12 vCPU @ 2.6 GHz per guest 4 vCPU @ 3.0 GHz per guest RAM 8GB – 48GB per guest 12-16 GB per guest Storage 256GB – 512GB on NetApp SSD Dell Compellent SC4020 Hybrid

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WHO ARE WE?

Jimmy Rotella

  • Sr. Solutions Architect

Nvidia

Andrew Schilling

Chief Infrastructure Officer CannonDesign

Jeremy Stroebel

Director of IT Browning Day Mullins Dierdof Architects

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GPU PROFILER

  • CPU Utilization
  • GPU Utilization
  • Frame Buffer Utilization
  • RAM Utilization
  • Video Encode
  • Video Decode

https://github.com/JeremyMain/GPUProfiler/releases

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M10 T4 P4 P40 P6 V100

GPU 4 NVIDIA Maxwell GPUs 1 NVIDIA Turing GPU 1 NVIDIA Pascal GPU 1 NVIDIA Pascal GPU 1 NVIDIA Pascal GPU 1 NVIDIA Volta GPU CUDA Cores 2,560 (640 per GPU) 2,560 2,560 3,840 2,048 5,120 Memory Size 32 GB GDDR5 (8 GB per GPU) 16 GB GDDR6 8 GB GDDR5 24 GB GDDR5 16 GB GDDR5 32 GB HBM2 Max vGPU instances 32 16 8 24* 16 32* vGPU Profiles 1 GB, 2 GB, 4 GB, 8 GB 1 GB, 2 GB, 4 GB, 8 GB, 16 GB 1 GB, 2 GB, 4 GB, 8 GB (1 GB, 2 GB) 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 24 GB 1 GB, 2 GB, 4 GB, 8 GB, 16 GB (1 GB, 2 GB) 4 GB, 8 GB, 16 GB, 32 GB Form Factor PCIe 3.0 Dual Slot (rack servers) PCIe 3.0 Single Slot (rack servers) PCIe 3.0 Single Slot (rack servers) PCIe 3.0 Dual Slot (rack servers) MXM (blade servers) PCIe 3.0 Dual Slot (rack servers) Max Power 225W 70W 75W 250W 90W 250W Thermal passive passive passive passive bare board passive

USER DENSITY

Optimized

BLADE

Optimized

PERFORMANCE

Optimized

NVIDIA TESLA DATA CENTER GPU HARDWARE

Maxwell, Pascal, Volta & Turing GPUs supported

MULTI-USE

Optimized

*mileage will vary

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NVIDIA T4 FOR VIRTUALIZATION

Powering 3D Professional Virtual Workstations

GPU Architecture Turing CUDA Cores 2,560 Tensor Cores 320 Memory Size 16 GB vGPU Profiles 1 GB, 2 GB, 4 GB, 8 GB, 16 GB Form Factor PCIe 3.0 single slot Power 70 W Thermal Passive

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Jimmy Rotella jrotella@nvidia.com Andrew Schilling aschilling@cannondesign.com Jeremy Stroebel jstroebel@bdmd.com