Large Scale Distributed GPU-Based Visualization Framework

Visualization Behind the Image

TACC staff enhanced NVIDIA's CUDA Isosurfacer to perform twice as fast by using one-third of the GPU memory, and enabling efficient overlapping of GPU operations with I/O operations and sort-last image compositing to achieve high throughput, in-core rendering. The enhanced isosurfacer achieves an approximate speedup for 4.5x over CPU-based visualization methods on a 2048^3 scalar volume. The images show enstrophy data, isosurfaced using the modified NVIDIA CUDA isosurfacer. It was created using 64 nodes of Longhorn. It took 2.5 minutes to isosurface 935M triangles, 68G cells, which correspond to 256 GB of data. Additionally, it took 9 seconds to render the images on 128 GPUs. The two frames show the assignment of data to process by color.

Authors

TACC

Greg Abram
Byungil Jeong
Greg P. Johnson
Paul Navratil
Kelly Gaither


Texas A&M University

Diego Donzis


Georgia Institute of Technology

P.K. Yeung