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Waveguide-based Room Acoustics using Graphics Hardware. Niklas Röber, Martin Spindler, Maic Masuch University of Magdeburg. Outline. Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion. Motivation Waveguide meshes and sampling lattices

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Waveguide based room acoustics using graphics hardware

Waveguide-based Room Acoustics using Graphics Hardware

Niklas Röber, Martin Spindler, Maic Masuch

University of Magdeburg


Outline
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Outline1
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Research
Research

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Games Research Group – University of Magdeburg

    • Tools and techniques for future games

    • Non-photorealistic rendering and cinematography

    • Interactive digital storytelling and authoring techniques

  • Audiogames

    • 3D virtual auditory environments

    • Audiogames and augmented audio reality

    • Interactive audiobooks

    • Sound rendering and synthesis (3D, room acoustics)


Motivation
Motivation

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Audiogames and auditory displays

    • Non-realistic audio environment

    • High quality 3D sound and room acoustic simulations

  • Similarities between sound and light propagation

    • Sophisticated and fast algorithms to render visual scenes

  • Powerful graphics hardware

    • AMD 64 (~8GFlops) vs. nvidia 7900GTX (~250GFlops)

    • Very fast for parallelizable problems

    • Various GPGPU applications


Outline2
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Waveguide meshes

3D rectilinear waveguide node

Waveguide meshes

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Time domain finite difference models

  • Bi-linear delay lines arranged in a mesh like structure

  • Scattering junctions are of equal impedance

    • Sum of inputs = sum of outputs

    • Pressure equal at crossings

  • Modeling of boundary conditions

  • Limitations

    • Direction dependent dispersion error

    • Finite mesh resolution / sampling frequency


Optimal sampling
Optimal Sampling

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Hexagonal lattices have a higher packing density

  • More optimal sampling

    • Spherically band limited signals

    • Unit length increases to

    • less samples in 3D

    • 8 neighbors with 4 axes of propagation and 4 delay lines per node

  • Used in compression, scientific visualization and image processing


Bcc waveguide mesh
BCC Waveguide Mesh

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Update frequency with unit length

  • One BCC unit cell consist of 2 nodes and 8 delay lines

  • Frequency dispersion with max. error 4.7%, compared to 7.3% (3D CC) (Campos and Howard 2005)

  • Sampling efficiency


Outline3
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Gpu based implementation
GPU-based Implementation

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Implementation based on 3D textures, fragment shaders and framebuffer-objects (fbo)

  • Two 32-bit float textures (RGB)

    • Waveguide data (t-1, t) (R and B channel)

    • Geometry, material and boundary conditions (G channel)

  • Shader computes / samples texture using screen aligned slicing planes


Waveguide shader
Waveguide Shader

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

1 uniform float layer;

2 uniform vec3 stepX, stepY, stepZ;

3 uniform sampler3D tex;

4 vec3 pos = vec3(gl_TexCoord[0].xy, layer);

5

6 vec4 center = texture3D(tex, pos);

7 vec4 left = texture3D(tex, pos − stepX);

8 vec4 right = texture3D(tex, pos + stepX);

9 vec4 up = texture3D(tex, pos + stepY);

10 vec4 down = texture3D(tex, pos − stepY);

11 vec4 front = texture3D(tex, pos + stepZ);

12 vec4 back = texture3D(tex, pos − stepZ);

13

14 float ampl = left.r + right.r + up.r + down.r;

15 ampl += front.r + back.r;

16 ampl = ampl * 0.3333 − center.b;

17 gl_FragColor = vec4(ampl, center.g, center.r, 1.0);

Waveguide fragment shader (Cartesian Lattice)


Bcc implementation
BCC Implementation

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • BCC lattice decomposed into two CC textures

    • Base grid (R and G), offset grid (B and A) for t-1 and t

    • One additional 3D texture (geometry, boundary conditions)

  • BCC fragment shader

    • Indexing adjusted for two textures

    • Two nodes computed in one step

  • Overall less computations


Outline4
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Results and discussion
Results and Discussion

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Benchmarks 2D, 3D CC and 3D BCC

  • Software (CPU) and Hardware (GPU)

  • Comparison CC and BCC lattices

  • Examples:

    • Wavefield synthesis

    • Impulse responses (3D CC, 3D BCC)


Benchmarks 2d
Benchmarks 2D

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • AMD 64 4000+ single core PC with 1 GB main memory

  • nvidia GeForce 7800GT with PCIe interface


Benchmarks 3d
Benchmarks 3D

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

cp = withglCopyTexSubImage3D

ncp = withoutglCopyTexSubImage3D


Rectilinear vs hexagonal
Rectilinear vs. Hexagonal

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

CC

BCC


Wavefield synthesis
Wavefield Synthesis

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • 21 sound sources

    • Sine wave pulse

  • Anechoic walls (top, bottom, right)

  • Phase-rev.reflection (left, middle obstacle)


Impulse responses

CC

CC

BCC

BCC

Impulse Responses

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

Original sound (The Notwist)

Low-pass filtered

3D CC room acoustics

3D BCC room acoustics


Outline5
Outline

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Motivation

  • Waveguide meshes and sampling lattices

  • GPU-based implementation

  • Results and discussion

  • Summary and future work


Summary
Summary

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • Novel and fast technique for wave propagation using waveguide meshes

    • Exploiting powerful graphics hardware with build-in visualization

    • Up to 15–20 times faster

    • Additional improvements through hexagonal sampling

  • Open questions / problems:

    • CC vs. BCC (quality)

    • Missing 3D fbo extension


Future work
Future Work

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

  • GPU accelerated ray-acoustic simulations

    • Global illumination (phonon mapping, spherical harmonics, BRDF)

    • Raytracing (particles, raycasting)

  • Combination of GPU-based wave- and ray-acoustics

  • Evaluation of physics hardware (Ageia’s PPU)

    • Mass-spring system

    • Particles, raycasting


Thank you for your attention
Thank you for your attention!

Outline – Motivation – Waveguides and Sampling – GPU Implementation – Results – Conclusion

More Information:

games.cs.uni-magdeburg.de/acoustics

[email protected]


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