Image-Space-Parallel Direct Volume Rendering on a Cluster of PCs (original) (raw)
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IEEE Transactions on Parallel and Distributed Systems, 2007
In this work, image-space-parallel direct volume rendering (DVR) of unstructured grids is investigated for distributed-memory architectures. A hypergraph-partitioning-based model is proposed for the adaptive screen partitioning problem in this context. The proposed model aims to balance the rendering loads of processors while trying to minimize the amount of data replication. In the parallel DVR framework we adopted, each data primitive is statically owned by its home processor, which is responsible from replicating its primitives on other processors. Two appropriate remapping models are proposed by enhancing the above model for use within this framework. These two remapping models aim to minimize the total volume of communication in data replication while balancing the rendering loads of processors. Based on the proposed models, a parallel DVR algorithm is developed. The experiments conducted on a PC cluster show that the proposed remapping models achieve better speedup values compared to the remapping models previously suggested for image-space-parallel DVR.
Journal of Parallel and Distributed Computing, 2007
Object space (OS) parallelization of an efficient direct volume rendering algorithm for unstructured grids on distributed-memory architectures is investigated. The adaptive OS decomposition problem is modeled as a graph partitioning (GP) problem using an efficient and highly accurate estimation scheme for view-dependent node and edge weighting. In the proposed model, minimizing the cutsize corresponds to minimizing the parallelization overhead due to the data communication and redundant computation/storage while maintaining the GP balance constraint corresponds to maintaining the computational load balance in parallel rendering. A GP-based, view-independent cell clustering scheme is introduced to induce more tractable view-dependent computational graphs for successive visualizations. As another contribution, a graphtheoretical remapping model is proposed as a solution to the general remapping problem and is used in minimization of the cell-data migration overhead. The remapping tool RM-MeTiS is developed by modifying the GP tool MeTiS and is used in partitioning the remapping graphs. Experiments are conducted using benchmark datasets on a 28-node PC cluster to evaluate the performance of the proposed models.
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 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.
Implementation of Cell-Projection Parallel Volume Rendering with Dynamic Load Balancing
A parallel volume rendering system for unstructured grid volume data is proposed in this paper. By implementing the mechanism for dynamic load balancing into the system, the authors solve the issue of load imbalance due to the view dependency and run-time features of early ray termination. An experimental implementation of the system achieved a 4.32-times performance improvement.
Image-Space Decomposition Algorithms for Sort-First Parallel Volume Rendering of Unstructured Grids
The Journal of Supercomputing, 2000
Twelve adaptive image-space decomposition algorithms are presented for sort-rst parallel direct volume rendering (DVR) of unstructured grids on distributed-memory architectures. The algo- rithms are presented under a novel taxonomy based on the dimension of the screen decomposition, the dimension of the workload arrays used in the decomposition, and the scheme used for workload-array creation and querying the workload of a
Performance Analysis of a 3D Parallel Volume Rendering Application on Scalable Tiled Displays
Current high-speed general-purpose networks, such as 1Gigabit/10Gibabit networks, are fast enough to handle the demanding tasks of routing streams of graphics primitives. Systems built with such networks and off-the-shelf GPUs and PCs, are being used to provide graphics clusters, which are more economical than expensive graphics supercomputers. Further, the current trend in building high-resolution display systems is to tightly couple inexpensive LCD/TFT monitors to provide a large-scale high-resolution display system for detailed scientific visualizations with an increased pixel density, such as the GeoWall (3) or Lightning-2 (9). The graphics clusters can drive the large-scale high- resolution display systems to possibly replace the limited output resolution of standard devices such as monitors and video projectors. A graphics cluster with new display technology and off-the-shelf, inexpensive components has made possible affordable large-scale high-resolution display systems. In t...
Giga-Scale Multiresolution Volume Rendering on Distributed Display Clusters
Lecture Notes in Computer Science, 2011
Visualizing the enormous level of detail comprised in many of today's data sets is a challenging task and demands special processing techniques as well as a presentation on appropriate display devices. Desktop computers and laptops are often not suited for this task because data sets are simply too large and the limited screen size of these devices prevents users from perceiving the entire data set and severely restricts collaboration. Large high-resolution displays that combine the images of multiple smaller devices to form one large display area have proven to be an adequate solution to the ever-growing quantity of available data.
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.
Volume Rendering using Grid Computing for Large-Scale Volume Data
2010
Abstract In this paper, we propose a volume rendering method using grid computing for large-scale volume data. Grid computing is attractive because medical institutions and research facilities often have a large number of idle computers. A large-scale volume data is divided into sub-volumes and the sub-volumes are rendered using grid computing. When using grid computing, different computers rarely have the same processor speeds. Thus the return order of results rarely matches the sending order.