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symposium on parallel graphics and visualization

作者： Yu, HF Ma, KL Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

This paper presents two parallel I/O methods for the visualization of time-varying volume data in a high-performance computing environment. We discuss the interplay between the parallel renderer, I/O strategy, and file system, and show the results of our study on the performance of the I/O strategies with and without MPI parallel I/O support. The targeted application is earthquake modeling using a large 3D unstructured mesh consisting of one hundred millions cells. Our test results on the HP/Cornpaq AlphaServer operated at the Pittsburgh Supercomputing Center demonstrate that the I/O methods effectively remove the I/O bottlenecks commonly present in time-varying data visualization, and therefore help significantly lower interfrarne delay. This high-performance visualization solution allows scientists to explore their data in the temporal, spatial, and visualization domains at high resolution. Such new explorability, likely not presently available to most computational science groups, will help lead to many new insights into the modeled physical and chemical processes. (c) 2005 Elsevier B.V. All rights reserved.

关键词： high-performance computing massively parallel supercomputing MPI scientific visualization parallel I/O parallel rendering time-varying data volume rendering

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Visual analysis of multivariate state transition graphs

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2006年第5期12卷 685-692页

作者： Pretorius, A. Johannes van Wijk, Jarke J. Tech Univ Eindhoven Dept Math & Comp Sci NL-5600 MB Eindhoven Netherlands

We present a new approach for the visual analysis of state transition graphs. We deal with multivariate graphs where a number of attributes are associated with every node. Our method provides an interactive attribute-based clustering facility. Clustering results in metric, hierarchical and relational data, represented in a single visualization. To visualize hierarchically structured quantitative data, we introduce a novel technique: the bar tree. We combine this with a node-link diagram to visualize the hierarchy and an arc diagram to visualize relational data. Our method enables the user to gain significant insight into large state transition graphs containing tens of thousands of nodes. We illustrate the effectiveness of our approach by applying it to a real-world use case. The graph we consider models the behavior of an industrial wafer stepper and contains 55 043 nodes and 289 443 edges.

关键词： graph visualization multivariate visualization interactive clustering state spaces transition systems finite state machines

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Performance Study of SIMD Programming Models on Intel Multicore Processors

Performance Study of SIMD Programming Models on Intel Multic...

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26th ieee International parallel and Distributed Processing symposium (IPDPS) / Workshop on High Performance data Intensive Computing

作者： Kristof, Peter Yu, Hongtao Li, Zhiyuan Tian, Xinmin Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA Intel Corp Mobile Comp & Compilers Santa Clara CA USA

ISBN: (纸本)9780769546766

Modern multicore hardware employs a variety of parallel execution units, including multiple CPU cores for executing multiple threads simultaneously, vector units such as the Intel SIMD on the CPU cores, as well as GPU-like processing arrays. Availability of such unprecedented level of parallelism on main-stream computers offers an enormous potential to enable a new generation of computation-intensive nontraditional applications. On the other hand, how to best harness the hardware parallelism presents a new challenge to application programmers, language designers and compiler developers. In this paper, we evaluate the impact of several different parallel execution models, especially the new SIMD vectorization methods, supported by the latest Intel ICC compiler (version 12.1), using three computation-intensive nontraditional parallel applications as the test workload. Unlike traditional numerical programs, these applications use highly irregular data structures and therefore present nontrivial challenges to effective use of SIMD vector units. The first application is a game engine architecture requiring real-time performance. The second application involves a kd-tree traversal, which is typical to the state-of-the-art 3D ray-tracing applications. The last application processes data for large-scale weather visualization system in the order of tens of minutes. We compare the execution time of these codes using different SIMD models supported by ICC in conjunction with parallel threading under TBB and OpenMP.

关键词： Intel ICC compiler parallel programming SIMD optimization computer graphics

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Robust Tracing and visualization of Heterogeneous Microvascular Networks

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2019年第4期25卷 1760-1773页

作者： Govyadinov, Pavel A. Womack, Tasha Eriksen, Jason L. Chen, Guoning Mayerich, David Univ Houston Dept Comp Sci Houston TX 77031 USA Univ Houston Dept Pharmacol & Pharmaceut Sci Houston TX 77031 USA Univ Houston Dept Elect & Comp Engn Houston TX 77031 USA

Advances in high-throughput imaging allow researchers to collect three-dimensional images of whole organ microvascular networks. These extremely large images contain networks that are highly complex, time consuming to segment, and difficult to visualize. In this paper, we present a framework for segmenting and visualizing vascular networks from terabyte-sized three-dimensional images collected using high-throughput microscopy. While these images require terabytes of storage, the volume devoted to the fiber network is approximate to 4 percent of the total volume size. While the networks themselves are sparse, they are tremendously complex, interconnected, and vary widely in diameter. We describe a parallel GPU-based predictor-corrector method for tracing filaments that is robust to noise and sampling errors common in these data sets. We also propose a number of visualization techniques designed to convey the complex statistical descriptions of fibers across large tissue sections-including commonly studied microvascular characteristics, such as orientation and volume.

关键词： Microvessel network tracking glyph visualization predictor-corrector segmantation spherical harmonics superquadrics KESM

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Toward Localized Topological data Structures: Querying the Forest for the Tree

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2020年第1期26卷 173-183页

作者： Klacansky, Pavol Gyulassy, Attila Bremer, Peer-Timo Pascucci, Valerio Univ Utah Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Livermore CA USA

Topological approaches to data analysis can answer complex questions about the number, connectivity, and scale of intrinsic features in scalar data. However, the global nature of many topological structures makes their computation challenging at scale, and thus often limits the size of data that can be processed. One key quality to achieving scalability and performance on modern architectures is data locality, i.e., a process operates on data that resides in a nearby memory system, avoiding frequent jumps in data access patterns. From this perspective, topological computations are particularly challenging because the implied data structures represent features that can span the entire data set, often requiring a global traversal phase that limits their scalability. Traditionally, expensive preprocessing is considered an acceptable trade-off as it accelerates all subsequent queries. Most published use cases, however, explore only a fraction of all possible queries, most often those returning small, local features. In these cases, much of the global information is not utilized, yet computing it dominates the overall response time. We address this challenge for merge trees, one of the most commonly used topological structures. In particular, we propose an alternative representation, the merge forest a collection of local trees corresponding to regions in a domain decomposition. Local trees are connected by a bridge set that allows us to recover any necessary global information at query time. The resulting system couples (i) a preprocessing that scales linearly in practice with (ii) fast runtime queries that provide the same functionality as traditional queries of a global merge tree. We test the scalability of our approach on a shared-memory parallel computer and demonstrate how data structure locality enables the analysis of large data with an order of magnitude performance improvement over the status quo. Furthermore, a merge forest reduces the memory overhead compare

关键词： Merge tree parallel computation topology

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Hypervolume visualization: A challenge in simplicity

Hypervolume visualization: A challenge in simplicity

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ieee symposium on Volume visualization

作者： Bajaj, CL Pascucci, V Rabbiolo, G Schikore, DR Univ Texas Dept Comp Sci Austin TX 78712 USA

ISBN: (纸本)1581131054

Hyper-volume visualization is designed to provide simple and fully explanatory images that give comprehensive insights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical approaches like isocontouring and animation of slices of no data. We completely abandon (for core simplicity) rendering techniques, such as hidden surface removal or lighting or radiosity, that enhance three dimensional realism and concentrate on the real-time display of images that highlight structural (topological) features of the no dataset (holes, tunnels, cavities, depressions, extrema, etc). Hyper-volume visualization on the one hand is a generalization of direct parallel projection methods in volume rendering. To achieve efficiency (and real-time performance on a graphics workstation) we combine the advantages of (i) a hierarchical representations of the hyper-volume data for multiresolution display and (ii) generalized object space splatting combined with texture-mapped graphics hardware acceleration. The development of a system that implements display techniques for multidimensional datasets requires careful design of both algorithms and user interfaces that scale linearly with the dimension of the input geometric space. This is a major challenge since straightforward generalizations of standard techniques that are suitable for display of 3D data yield exceedingly intricate interfaces. For example, a view manipulation graphical user interface is usually based on a rotation of the object about Cartesian rotation axes, with possibly unit quaternions internal representations for the rotation group. Unfortunately the number of independent rotation axes grows quadratically with dimension(three in 3D to six in 4D to ten in 5D to fifteen in 6D space). Going back to the basics of parallel projections, we develop an alternat

关键词： Graphical user interfaces

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A hardware-assisted hybrid rendering technique for interactive volume visualization

A hardware-assisted hybrid rendering technique for interacti...

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ieee / ACM SIGGRAPH symposium on Volume visualization and graphics, VolVis 2002

作者： Wilson, B. Ma, Kwan-Liu McCormick, P.S. Comput. Sci. Dept. California Univ. DavisCA United States Advanced Computing Laboratory Los Alamos National Laboratory United States

ISBN: (纸本)0780376412

The scientific simulation and three-dimensional imaging systems in use today are producing large quantities of data that range from gigabytes to petabytes in size. Direct volume rendering, using hardware-based three-dimensional textures, is a common technique for interactively exploring these data sets. The most serious drawback of this approach is the finite amount of available texture memory. In this paper we introduce a hybrid volume rendering technique based on the use of hardware texture mapping and point-based rendering. This approach allows us to leverage the performance of hardware-based volume rendering and the flexibility of a point-based rendering to generate a more efficient representation that makes possible interactive exploration of large-scale data using a single PC. © 2002 ieee.

关键词： Volume rendering

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Utilizing Many-Core Accelerators for Halo and Center Finding within a Cosmology Simulation 5

Utilizing Many-Core Accelerators for Halo and Center Finding...

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ieee 5th symposium on large data Analysis and visualization (LDAV)

作者： Sewell, Christopher Lo, Li-ta Heitmann, Katrin Habib, Salman Ahrens, James Los Alamos Natl Lab Los Alamos NM 87545 USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9781467385176

Efficiently finding and computing statistics about "halos" (regions of high density) are essential analysis steps for N-body cosmology simulations. However, in state-of-the-art simulation codes, these analysis operators do not currently take advantage of the shared-memory data-parallelism available on multi-core and many-core architectures. The Hybrid / Hardware Accelerated Cosmology Code (HACC) is designed as an MPI+X code, but the analysis operators are parallelized only among MPI ranks, because of the difficulty in porting different X implementations (e.g., OpenMP, CUDA) across all architectures on which it is run. In this paper, we present portable data-parallel algorithms for several variations of halo finding and halo center finding algorithms. These are implemented with the PISTON component of the VTK-m framework, which uses Nvidia's Thrust library to construct data-parallel algorithms that allow a single implementation to be compiled to multiple backends to target a variety of multi-core and many-core architectures. Finally, we compare the performance of our halo and center finding algorithms against the original HACC implementations on the Moonlight, Stampede, and Titan supercomputers. The portability of Thrust allowed the same code to run efficiently on each of these architectures. On Titan, the performance improvements using our code have enabled halo analysis to be performed on a very large data set (81923 particles across 16,384 nodes of Titan) for which analysis using only the existing CPU algorithms was not feasible.

关键词： D.1.3 [Software]: Programming Techniques ??? [Concurrent Prgm.] haloes Titan ARCHITECTURE Codes Cosmology FINDINGS thrust Portability algorithms data parallel

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VIScover: Visualizing, exploring, and analysing structured data - VAST 2009 flitter mini challenge award: Novel visualization of effect of rule application

VIScover: Visualizing, exploring, and analysing structured d...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Liebig, Thorsten Noppens, Olaf Von Henke, Friedrich Ulm University Derivo GmbH Germany Ulm University Germany

ISBN: (纸本)9781424452835

Today's challenging task in intelligent data processing is not to store large volumes of interlinked data but to visualize, explore, and understand its explicit or implicit relationships. Our solution to this is the VIScover system. VIScover combines semantic technologies with interactive exploration and visualization techniques able to analyze large volumes of structured data. We briefly describe our VIScover system and show its potential using the example of the VAST 2009 social network and geospatial data set. ©2009 ieee.

关键词： data visualization

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Portable and Composable Flow Graphs for In Situ Analytics 11

Portable and Composable Flow Graphs for In Situ Analytics

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ieee 11th symposium on large data Analysis and visualization (LDAV)

作者： Shudler, Sergei Petruzza, Steve Pascucci, Valerio Bremer, Peer-Timo Lawrence Livermore Natl Lab Livermore CA 94550 USA Utah State Univ Logan UT 84322 USA Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)9781665432832

Existing data analysis and visualization algorithms are used in a wide range of simulations that strive to support an increasing number of runtime systems. The BabelFlow framework has been designed to address this situation by providing users with a simple interface to implement analysis algorithms as dataflow graphs portable across different runtimes. The limitation in BabelFlow, however, is that the graphs are not easily reusable. Plugging them into existing in situ workflows and constructing more complex graphs is difficult. In this paper, we introduce LegoFlow, an extension to BabelFlow that addresses these challenges. Specifically, we integrate LegoFlow into Ascent, a flyweight framework for large scale in situ analytics, and provide a graph composability mechanism. This mechanism is an intuitive approach to link an arbitrary number of graphs together to create more complex patterns, as well as avoid costly reimplementations for minor modifications. Without sacrificing portability, LegoFlow introduces complete flexibility that maximizes the productivity of in situ analytics workflows. Furthermore, we demonstrate a complete LULESH simulation with LegoFlow-based in situ visualization running on top of Charm++. It is a novel approach for in situ analytics, whereby the asynchronous tasking runtime allows routines for computation and analysis to overlap. Finally, we evaluate a number of LegoFlow-based filters and extracts in Ascent, as well as the scaling behavior of a LegoFlow graph for Radix-k based image compositing.

关键词： Software and its engineering data flow architectures Human-centered computing visualization Scientific visualization

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