Parallel visualization of seismic wave propagation (original) (raw)

A Parallel Visualization Pipeline for Terascale Earthquake Simulations

Proceedings of the ACM/IEEE SC2004 Conference, 2004

This paper presents a parallel visualization pipeline implemented at the Pittsburgh Supercomputing Center (PSC) for studying the largest earthquake simulation ever performed. The simulation employs 100 million hexahedral cells to model 3D seismic wave propagation of the 1994 Northridge earthquake. The time-varying dataset produced by the simulation requires terabytes of storage space. Our solution for visualizing such terascale simulations is based on a parallel adaptive rendering algorithm coupled with a new parallel I/O strategy which effectively reduces interframe delay by dedicating some processors to I/O and preprocessing tasks. In addition, a 2D vector field visualization method and a 3D enhancement technique are incorporated into the parallel visualization framework to help scientists better understand the wave propagation both on and under the ground surface. Our test results on the HP/Compaq AlphaServer operated at the PSC show that we can completely remove the I/O bottlenecks commonly present in time-varying data visualization. The high-performance visualization solution we provide to the scientists allows them to explore their data in the temporal, spatial, and variable domains at high resolution. The new high-resolution explorability, likely not available to most computational science groups, will help lead to many new insights.

I/O strategies for parallel rendering of large time-varying volume data

2004

visualization. This high-performance visualization solution we provide to the scientists allows them to explore their data in the temporal, spatial, and visualization domains at high resolution. This new high-resolution explorability, likely not presently available to most computational science groups, will help lead to many new insights.

Parallel rendering of volumetric data set on distributed‐memory architectures

1993

Abstract A solution is proposed to the problem of interactive visualization and rendering of volume data. Designed for parallel distributed memory MIMD architectures, the volume rendering system is based on the ray tracing (RT) visualization technique, the Sticks representation scheme (a data structure exploiting data coherence for the compression of classified data sets), the use of a slice-partitioning technique for the distribution of the data between the processing nodes and the consequent ray-data-flow parallelizing strategy.

Experiences on Parallel Visualization of Volume Datasets

2007

Abstract This paper describes the work undertaken by our group on RT {based and projective {based parallel algorithms for direct volume visualization. It introduces the reader to direct visualization techniques and describes the parallel solutions we have designed to increase the interactivity of volume rendering.

Data-parallel, volume-rendering algorithms

The Visual Computer, 1995

Images generated from volumetric datasets are increasingly being used in many biomedical disciplines, archeology, geology, high energy physics, computational chemistry, computational fluid dynamics, meteorology, astronomy, computer aided design, environmental sciences, and many others.

A parallel multiresolution volume rendering algorithm for large data visualization

Parallel Computing, 2005

We present a new parallel multiresolution volume rendering algorithm for visualizing large data sets. Using the wavelet transform, the raw data is first converted to a multiresolution wavelet tree. To eliminate the data dependency between processors at run-time, and achieve load-balanced rendering, we design a novel algorithm to partition the tree and distribute the data along a hierarchical space-filling curve with error-guided bucketization. Further optimization is achieved by storing reconstructed data at pre-selected tree nodes for each processor based on the available storage resources to reduce the overall wavelet reconstruction cost. At run time, the wavelet tree is first traversed according to the user-specified error tolerance. Data blocks of different resolutions that satisfy the error tolerance are then decompressed and rendered to compose the final image in parallel. Experimental results showed that our algorithm can reduce the run-time communication cost to a minimum and ensure a well-balanced workload among processors when visualizing gigabytes of data with arbitrary error tolerances.

A distributed memory algorithm for volume rendering

Scalable High-Performance …, 1994

Three-dimensional arrays of digital data representing spatial volumes are generated from such diverse elds as the geosciences, space exploration and astrophysics, medical imaging, computational uid dynamics, molecular modeling, microelectronic eld modeling and computer simulation. With current advances in imaging devices and high performance computing, more and more applications will generate volumetric data in the near future. This paper presents a new distributed memory algorithm for volume rendering in a message-passing environment. The algorithm, which uses a slab technique for data partitioning, is a hybrid between the ray-casting and cell projection approaches for volumetric rendering. The results of some scaling experiments using ParaSoft Express on an Intel Paragon at the University of South Carolina are also presented.

Parallel Volume Rendering for Ocean Visualization in a Cluster of PCs

2004

Volume rendering techniques can be very useful in geographical information systems to provide meaningful and visual information about the surface and the interior of 3D datasets. For ocean visualization, in particular, volume rendering techniques improve the analysis of the ocean inner structure, by generating visual information about, e.g., its temperature, salinity, velocity and mass. The rendering of huge datasets, however, is a computationally intensive task and, in order to achieve interactive visualization times, a high-performance computational system is fundamental. Although parallel machines have been successful in providing interactive times, most recent efforts have been directed towards a more cost-effective solution: implementing volume rendering algorithms on clusters of PCs. This platform has low-cost and can be easily upgraded. Parallel rendering applications, however, usually suffer from high load imbalance during the execution. In this paper, we propose a low-cost and high-performance system for ocean visualization in a cluster of PCs, DPZSweep. Our solution spreads the computation over the cluster and provides dynamic load balancing with a low overhead. Our experimental results show that when we included the load balancing algorithms, DPZSweep obtained up to 95% of parallel efficiency in 16 processors.

Large Scale Parallel Simulation and Visualization of 3D Seismic Wavefield Using the Earth Simulator

2004

Recent developments of the Earth Simula- tor, a high-performance parallel computer, has made it possible to realize realistic 3D simulations of seismic wave propagations on a regional scale including higher frequencies. Paralleling this development, the deploy- ment of dense networks of strong ground motion instru- ments in Japan (K-NET and KiK-net) has now made it possibleto directlyvisualizeregional seismicwave prop- agation