Advances in High-Performance GPU Ray Tracing for Physics

Transcription

Advances in High-Performance GPU Ray Tracing
for Physics-Based Simulation
Christiaan Gribble & Lee A. Butler
GPU Technology Conference
21 March 2013
Introductions
Christiaan Gribble
Alexis Naveros
SURVICE Engineering
SURVICE Engineering
[email protected]
[email protected]
Lee A. Butler
Mark Butkiewicz
US Army Research Laboratory
SURVICE Engineering
[email protected]
[email protected]
SURVICE Engineering
• Support DoD community
• Focus on combat systems
– Safety
– Survivability
– Effectiveness
• 400+ employees
• 10 locations nationally
US Army Research Laboratory
• US Army RDECOM
– Corporate laboratory
– 2000 civilian employees
• Directorates
– SLAD
– Army Research Office
– Many others
• Still in the Top 500 list
Agenda
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Application domains
Technical motivation
Rayforce GPU ray tracing engine
Cognition-Driven Simulation
Visual Simulation Laboratory
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• Ballistic penetration
• Radio frequency propagation
• Thermal radiative transport
• High-energy particle transport
Application domains
Application domains
Optical rendering
Non-optical rendering
Interval computation
Interval generation
• Difficult or impossible
– Negative epsilon hacks
– Missed/repeated hits
• Performance impacts
– Traversal restart
– Operational overhead
Interval generation
Interval generation
Rayforce
• Programmable ray tracing engine
• Designed for NVIDIA GPUs
• High performance
– Modern techniques
– Novel acceleration structure
– Multiple traversal algorithms
Rayforce
Rayforce
State-of-the-art ray tracing
• Leverages modern techniques
– Ray packets
– Frustum tracing
• Exploits hardware features
– SIMD processing (v2.1)
– Architecture-specific optimizations
Proven techniques bolster
high performance
– Ray packets
– Frustum tracing
high performance
– Ray packets
– Frustum tracing
high performance
Acceleration structure
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kd-tree
Binary Space Partitioning tree
Regular grid
Bounding Volume Hierarchy
Acceleration structure
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kd-tree
Binary Space Partitioning tree
Regular grid
Bounding Volume Hierarchy
Graph-based spatial indexing
• Efficient
– Uses memory very carefully
– Improves cache performance
– Reduces memory bandwidth
• Flexible
• Scalable
• Efficient
• Flexible
– Several traversal algorithms
– Minimal overhead
– User-configurable pipelines
• Scalable
• Efficient
• Flexible
• Scalable
– Handles complex scenes
– Performance depends only
on complexity along a ray
Traversal algorithms
• First-hit
– Nearest intersected primitive?
– Visibility/bounce rays
• Any-hit
• Multi-hit
• First-hit
• Any-hit
– Is any primitive intersected?
– Shadow/ambient occlusion rays
• Multi-hit
• First-hit
• Any-hit
• Multi-hit
– Which primitives are intersected?
– Transparency & non-optical
rendering
Performance – tests
Coherent workloads
• vis
– first-hit visibility
– N · V shading
• x-ray
– all multi-hit intersections
– alpha blending
Incoherent workloads
• ao
– 32 AO rays/intersection
• kajiya
– shadows + 2 diffuse bounces
Coherent workloads
• vis
– N · V shading
• x-ray
– alpha blending
• ao
• kajiya
Coherent workloads
• vis
– N · V shading
• x-ray
– alpha blending
• ao
• kajiya
Coherent workloads
• vis
– N · V shading
• x-ray
– alpha blending
• ao
• kajiya
Performance – scenes
ktank
1M tris
conference
282K tris
san miguel
10M tris
Images rendered at 1024x768 pixels on a NVIDIA GeForce GTX 690
Performance – results
1000
Coherent workloads
800
600
400
200
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Mrps
vis
x-ray
ao
kajiya
Just for Fun …
1400
1200
1000
• 1920x1080 vs 1024x768
• Single hit
• No color, Lambertian only
800
600
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Mrps
vis
Multi-hit traversal
• Which primitives are intersected?
– One or more, & possibly all
– Ordered by t-value along ray
• Core operation in Rayforce
• Critical to interval generation
• Applications
Multi-hit traversal
– Avoids negative epsilon hacks
– Alleviates traversal restart
• Applications
Multi-hit traversal
– Handles bad geometry gracefully
– Enables early exit
• Applications
Multi-hit traversal
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Which primitives are intersected?
Core operation in Rayforce
Critical to interval generation
Applications
– Physically based simulation
– Order-independent transparency
– …
Naïve multi-hit
1 function TRAVERSE(root, ray)
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INITIALIZE(hitList)
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node  root
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while VALID(node) do
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if !EMPTY(node) then
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for tri in node do
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if INTERSECT(tri, ray) then
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hitData  (t-value, u, v, …)
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ADD(hitList, hitData)
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end if
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end for
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end if
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node  NEXT(node)
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Find all hits
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...
for hitData in hitList
if !USERHIT(ray, hitData) then
goto fini
end if
end for
label fini:
USEREND(ray)
end function
Process desired hits
Simple & effective, but
potentially slow
Rayforce multi-hit
1 function TRAVERSE(root, ray)
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node  root
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while VALID(node) do
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if !EMPTY(node) then
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SET(flags, INIT)
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while TRUE do
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INITIALIZE(hitList)
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for tri in node do
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if !DONE(hitMask, tri) then
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if INTERSECT(tri, ray) then
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hitData  (t-value, u, v, …)
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if ADD(hitList, hitData) then
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SET(flags, REPEAT)
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end if
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end if
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end if
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end for
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Find some hits
...
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if GET(flags) == (INIT & REPEAT) then
INITIALIZE(hitMask)
UNSET(flags, INIT)
end if
for hitData in hitList do
if !USERHIT(ray, hitData) then
goto fini
end if
if GET(flags) == REPEAT then
DONE(hitMask, hitData, TRUE)
end if
end for
Early exit
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Rayforce multi-hit
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if GET(flags) != REPEAT then
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break
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end if
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UNSET(flags, REPEAT)
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end while
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end if
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node  NEXT(node)
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end while
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label fini:
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USEREND(ray)
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Per-ray cleanup
Gains efficiency with
early exit
Early Exit Buys Performance
250
+39.05%
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+104.01%
Rayforce multi-hit
outperforms naïve
algorithm by 1.8x
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+91.00%
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ktank
conf
san miguel
Rayforce
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first-hit
Battle-tested techniques
Novel acceleration structure
Demonstration
Multi-hit ray traversalQuadro 3000M
Hand-tuned240
for Fermi
CUDACUDA Cores @ 900 MHz
Demonstrated high performance
GPU ray tracing
any-hit
multi-hit
Rayforce
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Modern techniques
Multi-hit ray traversal
Hand-tuned for CUDA
GPU ray tracing
first-hit
any-hit
multi-hit
Rayforce
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first-hit
Battle-tested techniques
Public LGPL v2.0
Multi-hit ray traversal
ofCUDA
Rayforce now
Hand-tuned for
GPU ray tracing
any-hit
multi-hit
release
available!
• Perform visualization during simulation
– As a by-product of computation
– As computation progress
• Key advantages
• Managed computation
• Key advantages
– Enables exploration & steering
– Drives understanding & confidence
– User Cognition must be managed:
• Too fast  details missed
• Too slow  disengage
• Key advantages
– Focus on most interesting features
– Avoid uninteresting parts of parameter
space
• A cross-platform, open-source
application framework
– Qt, OpenSceneGraph, & other
technologies
• The foundation used for several
CDS simulation applications
• A cross-platform, open-source
application framework
Public LGPL v2.0 release
of
VSL
now
available!
The foundation used for several
– Qt, OpenSceneGraph, & other
technologies
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CDS simulation applications
Get the software
Rayforce
Rayforce Website:
http://rayforce.net
Source code:
http://sourceforge.net/projects/rayforce
VSL
VSL Website:
http://vissimlab.org
Source code:
http://sourceforge.net/projects/vissimlab

Advances in High-Performance GPU Ray Tracing for Physics

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