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S7583
3D interior design and realistic
rendering with Iray, Quadro
VCA and VR
Ankit PATEL– NVIDIA Senior product manager
Jonathan MERLET– 3DVIA rendering specialist
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You want to refurnish your interior
…but how can you visualize the possibilities ?
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Realistic rendering in design process
Iray integration and architecture
What’s next
Plan
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Example in construction work
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Our goal
Give the user a nice view of his project
• Fast (a few minutes)
• Cheap (a handful of dollars)
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The problems
• Users not rendering experts
• Lighting often sub optimal
• Arbitrary scenes
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So…
• « Push button » interface
• Automatic adjustments (exposition)
• Biaised rendering with Iray Interactive
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Iterations
Max Quality
Photoreal
Interactive
99% Quality – 3470 it. – 3m46s 99% Quality – 65470 it – 4h30
Quality
Biased rendering
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User renderings examples
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Some customer reactions
« It’s really interesting, it allows you to project yourself
when you buy a house »
« It’s nice, it nearly looks like real life pictures »
« It looks really great ! »
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360 Stereo rendering
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360 Stereo rendering
• One image for each eye
• Depth effect in VR headset/cardboard
• Visualisable in browser (krpano), Facebook
• More expensive and sligthly trickier
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360 Stereo rendering
• Facebook 360 example
• Krpano example
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Realistic rendering in design process
Iray integration and architecture
What’s next
Plan
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VIDEO
Home by me presentation
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Demonstration
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A bird’s eye view of the architecture
Client
Cloud
Storage
Webservice
+ DB
Message
Queue
Load balancing
and conversion
worker
Rendering
cluster
1. Upload scene
2. Request3. Post
message
4. Pick
message
5. Get scene
6. Dispatch
8. Get image 7. Upload image
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Current state
• 200,000 renderings in 14 months
• 7 month and a half of compute time
• But load isn’t regular, and increasing…
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Rendering workers
Before
• Independent Amazon g2.8x instances which did conversion + rendering
Now
• VCA cluster + load balancing worker
• Amazon instances if too much load
• VCA 4x faster than Amazon instance
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VCA presentation
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HardwareRequired
● 8 x P6000 professional graphics boards
● 1 x Mellanox ConnectX-3 Infiniband FDR
Minimum
● 2 x Intel Xeon E5 CPUs (40 HT cores)
● 256 GB system memory
● 1TB of SSD storage (2x 512GB)
● 1 x 1 GigE network interface
● Power supply sufficient to accommodate components and
headroom for burst power needs
● System enclosure with mechanicals and thermal
management capable of accommodating components
without performance degrading
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Quadro VCA Software ● VCA Manager - cluster management software
○ for Interactive cluster rendering
○ for launching 3rd party apps
● Iray Queue Manager - Iray batch rendering
○ Same UI and features as Iray Server
● NVIDIA Rendering Software
○ Iray 2015.3 and newer
○ OptiX 4.0 or newer
○ Iray Cache manager
● Linux CentOS 7.2
● NVIDIA Quadro driver
1yr VCA software subscription license
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WAN (10/100 Mbps)
Infiniband (56 Gbps)
Node (1)
Master
GPU
CPU
Node (2)
Slave 1
GPU
CPU
Node (3)
Slave 2
GPU
CPU
Node (n)
Slave n
GPU
CPU
Load balancing
and conversion
worker
Cloud
Storage
6. Dispatch
Client7. Upload image 8. Get image
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VCA Certified Partner Program
Rigorous NVIDIA test SW
Select NVIDIA Tesla and Quadro GPUs
NVIDIA Partner Network
Enterprise support
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Global AvailabilityVCA Certified Partners
AMERICAS
EMEA
ASIA PACIFIC
GLOBAL
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Realistic rendering in design process
Iray integration and architecture
What’s next
Plan
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Image, 360, then…
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Light baking
• Render light maps in Iray, display in WebGL
• Realistic real time static scene (no modification possible)
• Visible in a VR headset
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Iray irradiance probes
Samples luminosity from an hemisphere
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Main steps
Unwrap the mesh to compute texture coordinates
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Main steps
From the texture coordinates, compute probes normals/positions
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Main steps
Render light map with Iray irradiance probes and save in RGBE
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Main steps
Render in WebGL with auto exposure and tonemapping
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Light baking
Demonstration
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The challenges
• Unwrapping an arbitrary mesh is hard
• « Good » tonemapping is subjective
• Only for view independent lighting
• Less computation, more textures
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Noise reduction
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Noise reduction
• Low lighting => noise
• Solved by more iterations, but add cost
• Use Nvidia deep learning trained denoiser
• Trained on 1000 3DVIA scenes
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Low number of iterations
Time : 1’08’’
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High number of iterations
Time : 6’
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Low number of iterations + denoiser
Denoising pass :
< 100ms
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Next steps
• Improve light baking
• Continue partnership with Nvidia on denoiser
• Explore other applications (Inspirationnal, mdl in real time)
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http://home.by.me
Questions ?
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