Parallel Volume Rendering for Large Scientific Data

PARALLEL VOLUME RENDERING FOR LARGE SCIENTIFIC DATA by Thomas Fogal University of New Hampshire, December, 2011 Data sets of immense size are regularly generated by large scale computing resources. Even among more traditional methods for acquisition of volume data, such as MRI and CT scanners, data which is too large to be effectively visualized on standard workstations is now commonplace. One solution to this problem is to employ a 'visualization cluster,' a small to medium scale cluster dedicated to performing visualization and analysis of massive data sets generated on larger scale supercomputers. These clusters are designed to fulfill a different need than traditional supercomputers, and therefore their design mandates different hardware choices, such as increased memory, and more recently, graphics processing units (GPUs). While there has been much previous work on distributed memory visualization as well as GPU visualization, there is a relative dearth of algorithms which effectively use GPUs at a large scale in a distributed memory environment. In this work, we study a common visualization technique in a GPU-accelerated, distributed memory setting, and present performance characteristics when scaling to extremely large data sets.

[1]  Kwan-Liu Ma,et al.  Massively parallel volume rendering using 2-3 swap image compositing , 2008, HiPC 2008.

[2]  Renato Pajarola,et al.  Eurographics Symposium on Parallel Graphics and Visualization (2007) Direct Send Compositing for Parallel Sort-last Rendering , 2022 .

[3]  Alan Heirich,et al.  Dynamic load balancing for parallel volume rendering , 2006 .

[4]  Kwan-Liu Ma,et al.  A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets y , 2022 .

[5]  Ulrich Neumann,et al.  Accelerating Volume Reconstruction With 3D Texture Hardware , 1994 .

[6]  Greg Humphreys,et al.  Chromium: a stream-processing framework for interactive rendering on clusters , 2002, SIGGRAPH.

[7]  Tom Duff,et al.  Compositing digital images , 1984, SIGGRAPH.

[8]  Robert B. Ross,et al.  End-to-End Study of Parallel Volume Rendering on the IBM Blue Gene/P , 2008, 2009 International Conference on Parallel Processing.

[9]  Kwan-Liu Ma,et al.  Parallel volume rendering using binary-swap compositing , 1994, IEEE Computer Graphics and Applications.

[10]  Vason P. Srini,et al.  Adaptive and Scalable Load Balancing Scheme for Sort-Last Parallel Volume Rendering on GPU Clusters , 2005 .

[11]  Rüdiger Westermann,et al.  Acceleration techniques for GPU-based volume rendering , 2003, IEEE Visualization, 2003. VIS 2003..

[12]  E. Wes Bethel,et al.  MPI-hybrid Parallelism for Volume Rendering on Large, Multi-core Systems , 2010, EGPGV@Eurographics.

[13]  Kenneth Moreland,et al.  Sort-last parallel rendering for viewing extremely large data sets on tile displays , 2001, Proceedings IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics (Cat. No.01EX520).

[14]  Jens H. Krüger,et al.  Tuvok, an Architecture for Large Scale Volume Rendering , 2010, VMV.

[15]  Rüdiger Westermann,et al.  Efficiently using graphics hardware in volume rendering applications , 1998, SIGGRAPH.

[16]  Marc Levoy,et al.  Efficient ray tracing of volume data , 1990, TOGS.

[17]  Brian Cabral,et al.  Accelerated volume rendering and tomographic reconstruction using texture mapping hardware , 1994, VVS '94.

[18]  Jean-Michel Dischler,et al.  Multi-GPU Sort-Last Volume Visualization , 2008, EGPGV@Eurographics.

[19]  M. Berger,et al.  Adaptive mesh refinement for hyperbolic partial differential equations , 1982 .

[20]  Thomas Ertl,et al.  for Graphics-Hardware-based Cluster Systems , 2006 .

[21]  Thomas Ertl,et al.  Hierarchical Visualization and Compression of Large Volume Datasets Using GPU Clusters , 2004, EGPGV.

[22]  Nelson L. Max,et al.  A contract based system for large data visualization , 2005, VIS 05. IEEE Visualization, 2005..

[23]  Nelson L. Max,et al.  Optical Models for Direct Volume Rendering , 1995, IEEE Trans. Vis. Comput. Graph..

[24]  Robert Latham,et al.  End-to-End Study of Parallel Volume Rendering on the IBM Blue Gene/P , 2009, 2009 International Conference on Parallel Processing.

[25]  Henry Fuchs,et al.  A sorting classification of parallel rendering , 1994, IEEE Computer Graphics and Applications.

[26]  Jens H. Krüger,et al.  Large data visualization on distributed memory multi-GPU clusters , 2010, HPG '10.

[27]  Charles D. Hansen,et al.  A data distributed, parallel algorithm for ray-traced volume rendering , 1993 .

[28]  William M. Hsu.  Segmented ray casting for data parallel volume rendering , 1993 .

[29]  Renato Pajarola,et al.  Cross-segment load balancing in parallel rendering , 2011, EGPGV '11.