Software-defined Visualization, High-Fidelity Visualization: OpenSWR and OSPRay

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Software-defined Visualization, High-Fidelity
Visualization: OpenSWR and OSPRay
Ingo Wald, Tech Lead Software-defined and High-Fidelity Visualization, Intel

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 Introduction
– Software-defined and High-Fidelity Visualization
 The OpenSWR ("SWR") software rasterizer
 The OSPRay Ray Tracing Engine for Vis-style Rendering
– Motivation and Goals
– Capabilities
– Getting started with OSPRay
Outline

A) This talk is about rendering for visualization
– Not about rendering for games, movies, etc …
… but rather, for scientific visualization (+engineering, …)
(in particular, in HPC Environments)
– Not about general "vis" (which is about more than rendering)
… but rather, only the rendering part of it
Before we start ….
Models courtesy Florida International
University, Tim Sandstrom (NASA), and
Carsten Kutzner (MPI BioChemistry)

A) This talk is about rendering for visualization
B) It's about interactive, but exclusively CPU-based rendering
– All rendering performed exclusively on the CPU(s)
– "No GPUs were harmed while making this talk…"
Before we start ….

 “Software-defined Visualization” (SDVis)
– Basic idea: Do the rendering on the CPU
 Turn “rendering” into a compute problem, then use a CPU solution
– Lots of demand for it
 Many HPC systems don’t have GPUs, and don’t want any
– Lots of opportunity in doing it
 E.g., full access to host memory, in situ, scalability, …
 “High-fidelity Visualization” (HiFi Vis)
– Enabling advanced rendering (ray tracing) for Vis
 Better “understanding” of model
 More flexibility in how to do the vis (volume rendering, transparency…)
 Better performance
SDVis and Hi-Fi Vis

Vision: Scalable, Flexible Vis Rendering that Runs Anywhere!
Standalone Laptops or Workstations
Big Memory Nodes or Rendering
Focused Clusters
Large Compute+Vis clusters with
Local or Remote Clients
Cloud or
Network

 … scalability in image quality
 … scalability in model size
 … scalability in render cost
HiFi-Vis: SDVis, plus …
Data set provided by Florida International University

Software Defined Visualization:
How can we get there?

 Option I: Build on existing APIs (OpenGL)
– Immediately works with any existing vis tool, vis app, …
– Zero adoption cost.
– But: Limited to whatever existing API can do (High-Fi !?)
 Option II: Build s/t new that’s not limited by legacy baggage
– Can build it exactly the way one wants it
– Can better adapt to changed demands & opportunities
– But: “some” effort to enable existing apps to use it
Software-defined Visualization: How?

 Option I: Build on existing APIs (OpenGL)
– Immediately works with any existing vis tool, vis app, …
– Zero adoption cost.
– But: Limited to whatever existing API can do (High-Fi !?)
The “OpenSWR” Software Rasterizer
 Option II: Build s/t new that’s not limited by legacy baggage
– Can build it exactly the way one wants it
– Can better adapt to changed demands & opportunities
– But: “some” effort to enable existing apps to use it
The “OSPRay” Ray Tracing library
Software-defined Visualization: How?

The “OpenSWR” Software Rasterizer

 Goal: Drop-in replacement of OpenGL (like Mesa, but faster)
– Implements subset of OpenGL as required for vis apps
 Primary targets today are ParaView* and VisIt
– Within this feature set: “drop-in” with existing apps
 No re-compilation necessary, just point LD_LIBRARY_PATH
 High performance through threading and vectorization
– Target Intel© AVX/AVX2 enabled Intel© Xeon© CPUs
– Available free of charge
 Early version available Open Source: http://OpenSWR.github.io
 Eventually: upstream to Mesa
The “SWR” Software Rasterizer

 Current Effort: Upstream into Mesa
– Current in closed "alpha 2" stage (hand-picked testers)
Application
Mesa3D OpenGL* API Layer
gallium state tracker
llvmpipe driver
OpenSWR driver
OpenSWR Core
Vertex/Fragment Shader Cores

 Current Effort: Upstream into Mesa
– Current in closed "alpha 2" stage (hand-picked testers)
Far more general use of OpenGL (version up to 3.x)
– But: STILL primarily focused on vis apps
(this is NOT intended to drive your favorite 3D shooter!)

Software Rasterizer in Action
Data: Texas Advanced Computing Center

Software Rasterizer Performance

Performance: OpenSWR vs MESA* LLVMpipe
Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark* and MobileMark*, are
measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other
information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more
information go to http://www.intel.com/performance.
• Intel® Xeon® E5-2699 v3 Processor 2 x 18 cores, 2.3 GHz
• ParaView 4.3.1
• OpenSWR “alpha 2”

Performance: OpenSWR vs. GPU

21
Node count 1
Platform Intel Cottonwood Pass
CPU Xeon DP Haswell-EP E5-2699 v3 LGA2011 2.3GHz 45MB 145W
Dual socket 18 core
RAM 128 GB total
8*16GB 2133MHz Reg ECC DDR4
BIOS Vendor: Intel Corporation
Version: SE5C610.86B.01.01.0005.101720141054
Release Date: 10/17/2014
BIOS Configuration: default
Hard drive INTEL SSDSA2M160G2GC
1x160 GB SATA SSD
NVIDIA Co-Processor NVIDIA* GeForce* GTX* Titan X
3072 CUDA Cores
12GB memory
Software Details:
CUDA Version 7.0.28
OptiX Version 3.8.0
NVIDIA Driver Version 346.46
OS / Kernel CentOS release 6.6 / 2.6.32-504.23.4.el6.x86_64
Performance Test Configuration
Intel Confidential* Other names and brands may be claimed as the property of others.

 Why is SWR so fast?
– How could SW ever be competitive w/ a discrete GPU?
A) Lots of optimizations: threading, vectorization (AVX/AVX2)
B) Vis is not games
 Vis SW not tuned for specific GPUs as games are; no tuning/hacks
 Different workload: fewer shading, larger data, PCI/driver speed,…
 GPUs often far from “peak performance” in Vis workloads
C) Trends in vis actually in favor of SW rendering
 No PCI transfer needed, larger data, …
SWR Performance

OSPRay – A Ray Tracing based
Rendering Library for High-Fidelity
Visualization

 Basic Idea: Bring ray tracing to visualization
– Enable shadows, ambient occlusion, large models,….
High-Fidelity Visualization

Slide courtesy Paul Navratil, TACC (Siggraph 2013).
Visualization by Carson Brownlee, TACC, using GLURay and Embree
High-Fidelity Vis Example:
“Florida Ground Water Core Sample”

 Slide courtesy Paul Navratil, TACC (Siggraph 2013).
High-Fidelity Vis Example:
“Florida Ground Water Core Sample”
Slide courtesy Paul Navratil, TACC (Siggraph 2013).

 Important: This is about more than just “pretty pictures”
– Better Insight through advanced rendering features
 Better pictures, but for the purpose of improving insight
– Give vis tools more flexibility in what they can render
 Volumes, transparency, non-polygonal geometry, complex models, …
– Performance
 Yes, we want to be faster than OpenGL (for vis apps and vis problems)

– Performance
The biiiig question: Can we ever get this fast enough?
With a ray tracer???

 The “Embree” Ray Tracing Kernels [Wald et al 2014]
– High-performance kernels for CPU Ray Tracing operations
– Provides very(!) high RT perf on Intel© Xeon© and Intel© Xeon Phi™
Parenthesis: Embree
 see dedicated "Embree" talk by Sven Woop in separate session
(I'm just stealing his performance numbers here…)
[Wald et al. Embree – A Kernel Framework for Efficient CPU Ray Tracing, ACM Trans. Graphics, 33(4), 2014]

Build Performance for Static Scenes
40 41 45
32.3 31.7 35.1
0
50
100
150
Intel® Xeon® E5-2699 v3
Processor
2 x 18 cores, 2.3 GHz
Intel® Xeon Phi™ 7120
Coprocessor
61 cores, 1.28 GHz
30
MillionTriangles/Second
SAH Build (high quality)

Build Performance for Dynamic Scenes
112 108 105
160.1
140.4
162.1
0
50
100
150
Processor
Coprocessor
61 cores, 1.28 GHz
31
MillionTriangles/Second
Morton Build

Ray Tracing Performance (incl. Shading)
107.2
129.6 134.98
64.96
75.36
82.62
29.472 35.04 38.76
0
20
40
60
80
100
120
140
Processor
Coprocessor
61 cores, 1.28 GHz
NVIDIA® GeForce®
GTX™ Titan X
Coprocessor
12 GB RAM
32
MillionRays/Second

 The “Embree” Ray Tracing Kernels [Wald et al 2014]
– High-performance kernels for CPU Ray Tracing operations
– Provides very(!) high RT perf on Intel© Xeon© and Intel© Xeon Phi™
see separate talk by Sven Woop
 Performance in absolute terms (typical dual-Xeon© WS)
– Traversal perf. order 100+M rays/sec
– BVH construction order 100+M tris/sec
Parenthesis: Embree
(actual numbers depend on CPU type, model size, shading cost, etc – see paper or Sven Woop's talk for more details)
[Wald et al 2004]: Embree – A Kernel Framework for Efficient CPU Ray Tracing; Wald, et al; ACM Transactions on Graphics 33(4), 2014

– Performance
Now: Can we get this fast enough?
With a ray tracer?

 For years, main limit was not how fast we can trace rays
Is ray tracing fast enough for interactive?
http://www.kitware.com/media/html/RenderedRealismAtNearlyRealTimeRates.html
This is from 2010!

 For years, main limit was not how fast we can trace rays
 … but how fast we could build BVHs (Manta in ParaView: “hours”…)

 For years, main limit was not how fast we can trace rays ….
 … but how fast we could build BVHs (Manta in ParaView: “hours”…)
 Today, with Embree (on modern workstation) :
– Traversal performance of many (100+) million rays/sec
 Enough for most simple vis-like shading
– BVH build performance in many (100+) million tris/sec
 That’s faster than Mesa can raster these triangles!
 But: Need this in “higher-level” form than “ray shooting API”
 OSPRay

– It’s a library, with a low-level, C-style API
 #include <ospray/ospray.h> and link to libospray[_mic].so
 Then do things like
“OSPGeometry mesh = ospNewTriangleMesh(…)”
 … or “ospRenderFrame(fb,renderer);”
What is OSPRay?

– It primarily targets visualization-style rendering
 It’s not trying to compete with GPUs in games …
... nor with global illumination renderers in production rendering
 “High-fidelity” is an option, but not required
(a ray tracer can do OpenGL-style simple shading, too!)
 Focus on visualization-relevant capabilities (volume rendering,
large data, data-parallel rendering, etc)… NOT on "pretty pictures"
What is OSPRay?

– It’s for vis-style rendering
 We’re not trying to reinvent VTK etc …
… but rather, to enable them for SDVis and HiFi-Vis
What is OSPRay?

– It’s for vis-style rendering
– It aims at being a workhorse for vis-tools like VisIt, ParaView…
 Most users shouldn’t even care about what’s inside
 Plan is to provide a free, open-source, high-fidelity alternative to GL
 Goal: If you think of writing a(/any!) vis-app, …
What is OSPRay?

 Project created about 2 years ago
– Based on previous (non-public) prototypes
– Approved for Open Source release Fall 2014
– “Pre-Alpha” first released at SC’14
 Currently in “Alpha” stage (v0.8.2)
– Intended for early integration into partner software
 Kitware ParaView*, VisIt, VMD, …
– Mostly feature-complete for single-node rendering
 Data-parallel extension under development (SC15?)
– Dove-tailing with TACC’s pvOSPRay (later)
 Giving out OSPRay-powered ParaView* to first early testers
OSPRay Status

 Internally, makes heavy use of Embree and ISPC
– All BVH traversal and construction done through embree
– All “SIMD-relevant code” written in ISPC
 OSPRay provides the “rendering layer” on top of Embree
– Frame Buffers, Geometry Types, Volume Types, Shading modes,
MPI and COI modes (where required), …
 Fully portable across Intel© SSE, AVX, AVX2, Xeon Phi™, …
 All ISA-specifics hidden by Embree and ISPC
OSPRay Internals (Brief)

OSPRay API
(what a programmer should know about OSPRay)

 OSPRay offers set of logical "objects"
– Frame Buffers
– Geometries (surfaces, can be intersect()'ed by a ray)
– Volumes (can be sample()'d by a volume integrator)
– Camera (generate primary rays)
– Renderers (shoot rays to compute pixel colors)
– Materials (store material/shading data used by renderers)
– Models (collection of all geometries, volumes, etc in a "scene")
– Textures
– …
OSPRay API

– Frame Buffers
– Geometries (surfaces, intersectable by a ray)
– Volumes (sample'able by a volume integrator)
– Camera (generate primary rays)
– Renderers (shoot rays to compute pixel colors)
– Materials (store material/shading data used by renderers)
– Models (collection of all geometries, volumes, etc in a "scene")
– Textures
– …
OSPRay API
Note: Many of these types are abstract, and can have specializations:
- "Geometry": could be triangle mesh geometry, sphere set geometry,
stream line geometry, …
- "Renderer": could be ray cast, ambient occlusion, direct volume
renderer, path tracer, …
Relatively easy to extend OSPRay w/ new object types
(mix of C++ and ISPC, but object-oriented design)

 All objects have "parameters"
– Think member variables
 E.g., "perspective" camera has "pos" (position), "dir", "up", …
– Objects' parameters can refer to other objects
 E.g., renderer will typically have handle to camera, model, …
 All object references internally ref-counted
OSPRay API

 Then:
– Application can create objects ...
OSPCamera cam = ospNewCamera("perspective")
OSPRay API

 Then:
… set their parameters …
ospSet3fv(cam,"pos",&appCamera->position);
ospSet3fv(cam,"dir",&appCamera->direction);
OSPRay API

 Then:
… set their parameters …
ospSet3fv(cam,"pos",&appCamera->position);
ospSet3fv(cam,"dir",&appCamera->direction);
… and "commit" the parameter changes
ospCommit(cam);
(changes won't take effect until committed)
OSPRay API

 Then: Rendering with OSPRay as simple as…
– Initialize OSPRay
– Set up the proper objects (camera, frame buffer, renderer, …)
– Properly parameterize (and commit!) those objects
– Render a frame
ospRenderFrame(fb,renderer, …);
– Get the frame buffer, and do something with it
void *fb = ospMapFrameBuffer(fb,…);
glDrawPixels(…, fb, …);
OSPRay API

OSPRay – Capabilities (v0.8.2)

– OSPRay support multiple “renderers” w/ different shading…
Capabilities: “High-Fidelity” Shading
FUI Ground Water Flow DataSet courtesy of Florida International University and TACC
With shadows (1 point light) With Ambient OcclusionTradidtional direct illumination only

– OSPRay support multiple “renderers” w/ different shading…
– … all the way up to "reasonably complete" path tracer
Model Courtesy Eastern Graphics and pCon.planner

Better shading can provide better visual cues about 3D shape
 Can help better understand the 3D shapeStream Lines model courtesy
Tim Sandstrom, NASA

Stream Lines model courtesy
Tim Sandstrom, NASA
Better shading can provide better visual cues about 3D shape
 Can help better understand the 3D shape

– Ray tracers naturally suited for large models (log model cost)
– Can fully use all of host’s memory (no GPU memory limit)
 Future: support data-parallel rendering (not yet avail in “alpha”)
 Even w/o data-parallel: hundreds of millions of prims no problem
Capabilities: Large Models
“FIU” model (8-80M triangles),
data courtesy Carson Brownlee, TACC, and
Florida International University
Boeing 777 model provided by and used with
permission of Boeing Corp.
340 million triangles, with Ambient Occlusion
“Richtmeyer-Meshkov Isosurface” model
(ParaView contour from 2k^3 volume)
~290M triangles, with Ambient Occlusion

Capabilities: Instancing
“XFrog” model courtesy Oliver Deussen, Univ Konstanz 1.5 billion (alpha-textured) triangles total
 Useful little “trick” often used in photorealistic rendering…

Capabilities: Instancing
 Useful little “trick” often used in photorealistic rendering…
 But also very useful in vis setting
• Use for complex "glyphs" (e.g., vector fields)
• Hierarchical scene manipulation
(instantly transform large number of prims w/o rebuilding)

– Ray tracer can trivially support non-polygonal geometry
Capabilities: Non-polygonal Geometry
Molecular Modelling: VMD “vesicle” model
Spheres + Cylinders + Triangles
Model courtesy Axel Kohlmeyer
Implicit(!) Iso-Surfaces in Unstructured Volume Dataset
Image courtesy Brad Rathke
Stream Lines
(Tim Sandstrom, NASA)
Materials Science: Particles (spheres)
KC Lau, Argonne National Lab)

– And of course, can easily mix-n-match it all together
 “VMD” example: cylinders, plus spheres, plus triangle meshes, ….
Capabilities: Non-polygonal Geometry
Model Courtesy
John Stone (UIUC)

– Volumes supported as first-class citizens
Volume Rendering
“Heptane” dataset (256^3 per time step). Data courtesy SCI Institute, University of Utah

“Large” is relative: We render directly out of host memory!
– Typical WS (or compute node)
today has 64-256GB
If it fits host mem it’s “easy"
Support for Large Volume Data
2k x 2k x 2k float (32 GB)
“Isotropic Turbulence” volume
(model courtesy Greg P Johnson and TACC)

Support for Large Volume Data
2k x 2k x 2k uint8 (8 GB)
“Richtmyer-Meshkov” volume
(model courtesy LLNL and TACC)
“Large” is relative: We render directly out of host memory!
– Typical WS (or compute node)
today has 64-256GB
If it fits host mem it’s “easy"

 OSPRay on TACC’s 80-display, 320MPixel Display Wall
– Note: actually rendering on (subset of) the display nodes
– Data-Distributed Rendering "under development"`
MPI Distributed Rendering

OSPRay – Performance

Performance: OSPRay (ray traced) vs GPU (OpenGL)
Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as
SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those
factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated
purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance.

OSPRay – Early Results

 OSPRay comes with several "proof of concept" sample apps
– Volume Viewer (with Seismic Data Module)
– Particle Model Viewer
– Polygonal Model Viewer(s)
 Currently being integrated into various apps
(remember - this is the ultimate goal for OSPRay!)
– Main focus today: VisIt and ParaView*
– VMD: “Soon”
– Plus several others … (some outside of classical vis)
 Will briefly show a few examples…
OSPRay: Early Results

– Two intentionally simple tools, mostly for testing
 Used for most of prev shown images …
 Useful tools, but not the core of what ospray is about
OSPRay Sample Model & Volume Viewers

– Representative of typical Oil-and-Gas Workload
 Volume data plus polygonal horizons, slices, large data, …
 Live demo shown at SC'15
Prototype “Seismic Data” Viewer
“Moroccan Basin” data courtesy
25 million triangle “horizons”
(rendered “into” volume)
Volume rendering
Arbitrary slicing
(can interactive move
even in 100GB volumes)

OSPRay for Particle Vis (Academia)
“Priya” model, “several million” particles
Model courtesy Argonne National Lab
– … even for truly large models

– … even for truly large models
Uintah “Detonation” model, ~1 billion particles
Model courtesy SCI Institute, Univ of Utah

“cosmic web” early universe model, ~12 billion particles (~1TB)
(rendered on a single 3TB quad-Intel© Xeon© E5 workstation)
[Wald et al, Ray Tracing large Particle Models using p-k-d Trees, IEEE SciVis,
to appear]
Model courtesy and Texas Advanced Computing Center

Early Integration Results: "pCon.planner"
Model and Image courtesy EasternGraphics
Eastern Graphics's "pCon.planner" software w/ OSPRay path trace renderer

Early Integration Results: ParaView*
Image courtesy Carson Brownlee (TACC)
Paraview “Contour” of full Richmyer-Meshkov dataset, w/ AO (Carson
Brownlee)

 Kitware's ParaView*: One of "the" tools for sci vis
– Builds heavily on the Visualization TookKit (VTK)
– Supports a "plugin" mechanism
 pvOSPRay: ospray renderer plugin into ParaView*
– Developed (in close collaboration) by Texas Advanced Computing
Center (TACC)
– Intercepts geometry draw calls from VTK, renders through OSPRay
– Prototypical volume rendering support
– All Open Source, currently in "Alpha-Testing" stage
https://github.com/TACC/pvOSPRay
Early Integration Results: ParaView*

Early Integration Results: VisIt*
Image courtesy Carson Brownlee (TACC)

 Talked about
– … High-fidelity visualization and software defined visualization
– … OpenSWR and OSPRay as milestones along this journey
– … early results from both
 If you want to play with it:
– SWR: http://www.openswr.org
– OSPRay: http://ospray.github.io (or http://www.ospray.org)
(In part, check out the “demo datasets” section)
– pvOSPRay: http://tacc.github.io/pvOSPRay
Summary

Questions?
(Oh, BTW: We are hiring!)
8/18/2015
80

 Models and illumination effects representative for
professional rendering environment
 Path tracer with different material types, different
light types, about 2000 lines of code
 Evaluation on typical Intel® Xeon® rendering
workstation* and Intel® Xeon Phi™ Coprocessor**
 Compare against state of the art GPU*** methods
(using OptiX™ 3.8.0 and CUDA® 7.0.28)
 Identical implementations in ISPC (Xeon®), ISPC
(Xeon Phi™), OptiX™ (GTX™ Titan X)
Embree Performance Methology
81
Imperial Crown of Austria
4.3M triangles
Bentley 4.5l Blower (1927)
2.3M triangles
Asian Dragon
7.3M triangles
* Dual Socket Intel® Xeon® E5-2699 v3 2x18 cores @ 2.30GHz ** Intel® Xeon Phi™ 7120, 61 cores @ 1.238 GHz *** NVIDIA® GeForce® GTX™ Titan X

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