Deploy Luxion KeyShot on a virtual machine

Virtual Machines
Virtual Network

This article briefly describes the steps for running Luxion KeyShot on a virtual machine (VM) that's deployed on Azure. It also presents the performance results of running KeyShot on Azure.

KeyShot is a standalone, real-time ray tracing and global illumination program that's used to create 3D renderings, animations, and interactive visuals. It uses photon mapping, an extension of ray tracing, which makes simulation of global illumination in complex scenes more efficient. KeyShot has the following capabilities:

  • 3D-paint enabled, so users can directly paint or stamp bump textures, colors, roughness, specularity, refractivity, and opacity.
  • Provides physics simulation that allows users to record the physics of an object and apply it as a keyframe animation.
  • Allows control over gravity, friction, and bounciness and the ability to adjust the time, quality, and keyframes per second.

KeyShot customers include product and industrial designers, vehicle design companies, jewelers, and architects. It's ideal for the automotive and manufacturing industries.

Why deploy KeyShot on Azure?

  • Modern and diverse compute options to align to your workload's needs
  • The flexibility of virtualization without the need to buy and maintain physical hardware
  • Rapid provisioning
  • Fast compute capabilities for GPU-intensive workloads

Architecture

Diagram that shows an architecture for deploying KeyShot.

Download a Visio file of this architecture.

Components

Compute sizing and drivers

Performance tests of KeyShot on Azure used NVadsA10_v5 and NC4as_T4_v3 series VMs running Windows. KeyShot 11 was used in these tests. The following table provides details about the VMs.

VM size vCPU Memory (GiB) Temporary storage SSD (GiB) GPU partition GPU memory (GiB) Maximum data disks
Standard_NV12ads_A10_v5 12 110 360 1/3 8 4
Standard_NV18ads_A10_v5 18 220 720 1/2 12 8
Standard_NV36ads_A10_v5 36 440 720 1 24 16
Standard_NV36adms_A10_v5 36 880 720 1 24 32
Standard_NV72ads_A10_v5 72 880 1,400 2 48 32
Standard_NC64as_T4_v3 64 440 2,880 4 64 32

Required drivers

To take advantage of the GPU capabilities of NVadsA10_v5 and NC4as_T4_v3 series VMs, you need to install NVIDIA GPU drivers.

To use AMD processors on NVadsA10_v5 and NC4as_T4_v3 series VMs, you need to install AMD drivers.

KeyShot installation

Before you install KeyShot, you need to deploy and connect a VM, install an eligible Windows 10 or Windows 11 image, and install the required NVIDIA and AMD drivers.

For information about eligible Windows images, see How to deploy Windows 10 on Azure and Use Windows client in Azure for dev/test scenarios.

For information about deploying the VM and installing the drivers, see Run a Windows VM on Azure.

For information about installing KeyShot, see the KeyShot website.

KeyShot performance results

Three test case models were used to test the performance of KeyShot on Azure:

Watch configurator

Figure that shows the watch configurator.

Resolution: 3,556 x 2,000 pixels

Ring configurator

Figure that shows the watch configurator.

Resolution: 3,556 x 2,000 pixels

Door configurator

Figure that shows the watch configurator.

Resolution: 3,556 x 2,000 pixels

Performance results for NVads_A10_v5 series

The following sections present the performance results for each model. Rendering times are shown in seconds, for three sample sizes.

Watch configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NV12ads_A10_v5 12 vCPU 365 728 813
Standard_NV12ads_A10_v5 1/3 GPU 48.44 95.89 191
Standard_NV18ads_A10_v5 1/2 GPU 29.47 58.93 116
Standard_NV36ads_A10_v5 1 GPU 13.98 27.97 55.94
Standard_NV36adms_A10_v5 1 GPU 12.98 25.98 51.95
Standard_NV72ads_A10_v5 2 GPU 6.99 13.98 28.47

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the watch configurator on the NVads_A10 VM.

Ring configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NV12ads_A10_v5 12 vCPU 1,244 2,445 4,908
Standard_NV12ads_A10_v5 1/3 GPU 117 234 459
Standard_NV18ads_A10_v5 1/2 GPU 62.95 125 248
Standard_NV36ads_A10_v5 1 GPU 27.98 55.94 111
Standard_NV36adms_A10_v5 1 GPU 24.98 48.94 99.4
Standard_NV72ads_A10_v5 2 GPU 13.48 26.96 53.45

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the ring configurator on the NVads_A10 VM.

Door configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NV12ads_A10_v5 12 vCPU 786 1,573 3,223
Standard_NV12ads_A10_v5 1/3 GPU 188 375 747
Standard_NV18ads_A10_v5 1/2 GPU 123 247 492
Standard_NV36ads_A10_v5 1 GPU 54.97 110 220
Standard_NV36adms_A10_v5 1 GPU 42.45 81.42 162
Standard_NV72ads_A10_v5 2 GPU 26.97 43.97 87.43

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the door configurator on the NVads_A10 VM.

Performance results for NC64as_T4_v3

The following sections present the performance results for each model. Rendering times are in seconds, for three sample sizes.

Watch configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NC64as_T4_v3 64 vCPU 66.92 133 268
Standard_NC64as_T4_v3 1 GPU1 32.98 66.93 133
Standard_NC64as_T4_v3 2 GPU1 17.48 34.48 68.43
Standard_NC64as_T4_v3 3 GPU1 12.49 23.98 47.95
Standard_NC64as_T4_v3 4 GPU 9.98 18.96 37.46

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the watch configurator on the NC64as_T4 VM.

Ring configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NC64as_T4_v3 64 vCPU 260 509 1,008
Standard_NC64as_T4_v3 1 GPU1 88.91 169 334
Standard_NC64as_T4_v3 2 GPU1 49.95 93.4 180
Standard_NC64as_T4_v3 3 GPU1 36.48 66.43 126
Standard_NC64as_T4_v3 4 GPU 30.96 54.45 101

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the ring configurator on the NC64as_T4 VM.

Door configurator

VM size CPU/GPU Rendering
time, 256
Rendering
time, 512
Rendering
time, 1024
Standard_NC64as_T4_v3 64 vCPU 139 273 547
Standard_NC64as_T4_v3 1 GPU1 102 203 406
Standard_NC64as_T4_v3 2 GPU1 52.44 104 208
Standard_NC64as_T4_v3 3 GPU1 35.96 70.93 140
Standard_NC64as_T4_v3 4 GPU 27.47 53.96 106

1 In these cases, the number of GPUs was artificially limited. This VM has four GPUs.

This graph shows the relative speed increases as the CPU/GPU increases:

Graph that shows the relative speed increase for the door configurator on the NC64as_T4 VM.

Azure cost

The following tables provide elapsed times in hours. To compute the total cost, multiply these times by the Azure VM hourly costs for NVads_A10_v5 and NCas_T4_v3 VMs. For the current hourly costs, see Windows Virtual Machines Pricing.

Only model running time (wall-clock time) is considered for these cost calculations. Application installation time isn't considered. The calculations are indicative. The actual numbers depend on the size of the model.

You can use the Azure pricing calculator to estimate the costs for your configuration.

NVads_A10_v5 series

This table shows elapsed times, in hours, for running all three models.

Sample size 12-core CPU 1/3 GPU 1/2 GPU 1 GPU 1 GPU (36adms* VM) 2 GPU
256 0.665 0.098 0.060 0.027 0.022 0.013
512 1.318 0.196 0.120 0.054 0.043 0.024
1024 2.484 0.388 0.238 0.107 0.087 0.047

* This number refers to a Standard_NV36adms_A10_v5 VM configuration.

NCAST4_V3 series

This table shows elapsed times, in hours, for running all three models.

Sample size 64-core CPU 1 GPU 2 GPU 3 GPU 4 GPU
256 0.129 0.062 0.033 0.024 0.019
512 0.254 0.122 0.064 0.045 0.035
1024 0.506 0.243 0.127 0.087 0.068

Summary

  • Luxion KeyShot 11 was successfully tested on NVads_A10_v5 and NC64as_T4_v3 VMs.
  • The GPU technology in KeyShot 11 provides excellent processing power on Azure.
  • Depending on the complexity of the model, the performance improvement as you increase CPU/GPU varies.

Contributors

This article is maintained by Microsoft. It was originally written by the following contributors.

Principal authors:

Other contributors:

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Next steps