Jeremy Main シニアソリューションアーキテクト GRID

GRID Technical SessionvGPU Sizing

First ConsiderationsUnderstand the existing non-VDI environment and workloads

Workstation model, CPU generation, CPU speed, memory, storage

GPU(s) used, how it was selected or upgraded

Applications used, number of displays, special input devices

Capture system and GPU performance data and review with user

Provide a data-driven recommendation to gain acceptance

Segment users GPU requirements and size appropriately

First ConsiderationsServer-rendered FPS vs. remotely delivered FPS

Define the per-user network bandwidth requirements

Explain the impact of 30 FPS vs. 60 FPS delivered framerates

Start with a less dense vGPU profile and access user performance

Increase density until performance does not meet acceptance tests

Require acceptance testing with real workloads not benchmarks

Log and monitor GPU utilization on host

Agree on metrics, don’t use subjective criteria…

Understanding your ApplicationsCPU, memory and storage requirements

GPU rendering and frame buffer requirements

“perfmon” on existing workstation or GPU pass-through VM

Memory -> Available MBytes

Processor -> % Processor Time

NVIDIA_GPU

% GPU Usage

Total Memory (MB)

Available Memory (MB)

Catia V5-6R2012 K5000

Try to limit the number of slides you use

Keep text to a minimum

Instead, speak more to your audience (engage them with anecdotes/enthusiasm/eye contact)

Try not to read your points verbatim; bullet points should be used for key points only

Use images/graphics to help convey your message

Catia V5-6R2012 K5000Application not using all of the CPU cores

GPU utilization is low

GPU memory use is low

1GB vGPU profile

Catia V5-6R2012 K600Application not using all of the CPU cores

GPU utilization is low

GPU memory use is low

1GB vGPU profile

Siemens NX 10 K5000

Siemens NX 10 K5000Application using more of the CPU cores in some operations

GPU utilization is low

GPU memory use is low

1GB vGPU profile

Siemens NX 10 K600Application using more of the CPU cores in some operations

GPU utilization is low

GPU memory use is low

1GB vGPU profile

SPECviewperf12 K5000

GPU Utilization

0

50

100

% CPU

% GPU

BenchmarksPush GPU capabilities to their limits

and may be heavily dependent on

single thread performance

ApplicationsModeling operations and view

manipulation consist of periods of

activity and inactivity

0

50

100

% CPU

% GPU

Monitoring vGPUWithin the VM “NVIDIA_GPU” counter, “% GPU Usage” is not supported

Monitor at hypervisor-level using nvidia-smi command

$ nvidia-smi --query-gpu=¥

timestamp,name,pci.bus_id,driver_version,pstate,¥

pcie.link.gen.max,pcie.link.gen.current,temperature.gpu,¥

utilization.gpu,utilization.memory,memory.total,¥

memory.free,memory.used --format=csv -l 5

Prepend with “timeout –t” with the number of seconds to run

Monitoring protocol HDX3D-Pro FPSwmic /NameSpace:¥¥root¥citrix¥hdx Path Citrix_VirtualChannel_Thinwire_Enum Get Component_Fps /every:5

Verify consistent frame rate delivery based on XenDesktop policy parameters

Monitoring protocol PCoIP FPSPerfmon: PCoIP Session Imaging Statistics -> Imaging Encoded Frames/Sec