Technology

Interactive
Visualization
Realtime
3D Graphics
Visual
Computing
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Although the era of technological evolution in the physical world has no end in sight, a second technological process has started just some years ago. The evolution of information technologies has begun to reach our mind and collective intelligence as changes in economy and society accelerate the demand on orientation in a complex world.

We focussed on specific fields in the landscape of information technologies that will play key roles for future developments. The successful integration of different technologies offers great challenges in designing and developing innovative applications.

Jetson TK1 Tegra Peformance Test with Nbody

Unboxing NVIDIA Jetson TK1 Mobile Supercomputer for embedded systems development running the popular Nbody CUDA SDK sample for performance tests with 8192 particles.

Screen recording made with Elgato Game Capture HD. Colors were inverted for white space optic. More information about Jetson TK1 development kit: https://developer.nvidia.com/jetson-tk1

Music: The Misery (Nu and Pauli vs Acid Remix)

Virtual universe simulation with CUDA (nbody)

This is a brute force Nbody implementation with ManagedCuda and SharpDX.
It runs on a Geforce Titan at 30fps with 61440 stars. Recorded with NVIDIA ShadowPlay. Particles are bloomed, use of a SkyBox made with SpaceScape.

AudioSmoke visual remix on surface – CUDA video processing and visualization

AudioSmoke is a realtime 3D visual computing application for massive particle visualization. This visual remix uses the original video art from AudioSmoke as an input source for the dynamic heightmapping method from the 2 Million Pixel Experiment to obtain a new visual style. This time the visualization is based on a tesselated surface instead of a point cloud.

AudioSmoke – 3.2M gravity particles in realtime 3D (DirectX + CUDA)

AudioSmoke is a realtime 3D visual computing application to visualize millions of particles under different force field conditions. CUDA is used for the parallel computation of the force field model. The particles react on sound input (FFT analysis) and can be explored interactively in 3D space. The video shows 32 million particles under different force fields and parameter settings.

GPUerror – propagation of error on a GPU revealing colorful structure in volume

By serendipity this visual computing experiment led to a visualization of colorful structures that evolve from the parallel propagation of errors on a graphics processing unit (GPU). We wanted to transfer color values in subsequent volume slices using an OpenCL kernel. Due to concurrent memory access this transfer operation was erroneous and produced interesting visual patterns in a point-based visualization. Meanwhile we fixed this “error” with another kernel but we wanted to share the initial results as a piece of visual computing art. The visual patterns reveal the structure of block-wise kernel execution on the GPU.

CUDA experiment III – 2 million pixel

This CUDA experiment maps a FULL-HD (1920×1080 @ 30 frames per second, MPEG2 compression) video source into 3D space. Each frame is processed in real-time on the GPU using CUDA. Each pixel in a frame (2.073.600 pixels per frame) is scaled by its luminance value and given the original color. The camera flight is realized with a 3D space navigator in real-time. This application is written in C# using DirectX 11, CUDA.NET and DirectShow.NET libraries. Benchmarks: GPU load is about 85% (GTX 260), GPU memory controller load 25%, CPU (i7-920) is at 20%.

The soundtrack is made by Ludwig Berger:
http://ludwigberger.com/

As slashcam.de reports, this application might be utilized for a quality check of video footage, like in a waveform monitor: http://www.slashcam.de/news/single/Echtzeit-3D-Waveform-Monitor-in-CUDA-8715.html

Interview in the NVIDIA CUDA Newsletter, Nov. 10, 2010
http://www.nvidia.com/content/newsletters/web/CUDA-Week-in-Review-Nov-10-10.html

CUDA experiment II – cell grid kernel

Experimental application in C# using CUDA for parallel computation. The grid is quite small sized, but the GPU does it’s work: 512×512 pixels are computed by a cell formula that calculates the difference between the average neighborhood and the current cell’s value. Kernel time is about 3-4 milliseconds, stressing the GPU (GTX 260) only at 2-4% load. The sound is added from an experiment for generating digital noise.

CUDA experiment I – sinus kernel

Experimental application in C# using CUDA for parallel computation. The grid is quite small sized, but the GPU does it’s work: 512×512 pixels are calculated by various sinus functions that use their output as input while cycling through time. Kernel time is about 3-4 milliseconds, stressing the GPU (GTX 260) only at 2-4% load. The sound is added from a similar experiment that uses visually generated sinus patterns.

Infinite Trees – Generative 3D System (OpenGL)

Infinite Trees is a generative system that renders a bifurcation process as a branching tree. This multithreaded system uses OpenGL for real-time 3D graphics and was implemented in C# with OpenTK and Mono (cross-platform). We used a geometry shader to render bezier curved branches. The system parameters are changed randomly to generate infinite variations of spatial tree structures.