Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP

Okuyan, Erhan; Güdükbay, Uğur

doi:10.1007/s11227-013-1004-x

Cited by 14 publications

(5 citation statements)

References 16 publications

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“…Our implementation utilizes multicore CPU hardware. We can achieve almost linear speed-ups [36]; i.e., 3.0-to 3.5-fold speed-ups for quad-core CPUs.…”

Section: Volume and Surface Renderingmentioning

confidence: 93%

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MaterialVis: Material visualization tool using direct volume and surface rendering techniques

Okuyan

Güdükbay

Bulutay

et al. 2014

Journal of Molecular Graphics and Modelling

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a b s t r a c tVisualization of the materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called MaterialVis. Unlike the existing tools, MaterialVis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. MaterialVis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, MaterialVis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography.

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“…Our implementation utilizes multicore CPU hardware. We can achieve almost linear speed-ups [36]; i.e., 3.0-to 3.5-fold speed-ups for quad-core CPUs.…”

Section: Volume and Surface Renderingmentioning

confidence: 93%

“…It does not require any auxiliary data such as neighboring information. Its execution flow and memory access patterns are mostly uniform, making it ideal for parallel implementations [36]. Our implementation utilizes multicore CPU hardware.…”

Section: Volume and Surface Renderingmentioning

confidence: 99%

MaterialVis: Material visualization tool using direct volume and surface rendering techniques

Okuyan

Güdükbay

Bulutay

et al. 2014

Journal of Molecular Graphics and Modelling

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“…Given that k0 has been set to 4 (k0 = 4) and filter-order set to 3, we obtain the two outputs Yestimated [4] and Yestimated [5] and their DFGs in Figure 2. We can now globally assess the parallel potential of the target program.…”

Section: : }mentioning

confidence: 99%

“…A wide range of applications [1][2][3] have already been suggested within parallel implementations. Some parallelizations are carried out also using the semiautomatic platforms and the annotations/directives oriented frameworks like CUDA and OpenMP [4][5][6][7]. Although semiautomatic tools are often used for parallel implementation, they are not as easily applicable as it appears [8].…”

Section: Introductionmentioning

confidence: 99%

Incremental Banerjee test conditions committing for robust parallelization framework

Debbi¹,

Bakhti²

2018

Turk J Elec Eng & Comp Sci

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This paper describes the design of an automatic parallelization framework. The kernel supplied at its front end was suggested as an instrument for parallel potential assessment. It was used to measure the maximum achievable speedups in the major set of the CHStone benchmark suite programs. In such framework, we suggested the liberation of parallelism incrementally. We proposed a data dependency heuristic-based transformation method to make true dependences dissociation. We generated an internal representation (IR 2), where the Banerjee test conditions are met. Two among three of Banerjee test conditions came to be committed. In shared memory many/multicore platforms, the third condition could be satisfied by privatization. We would be able to choose the safe and the opportune pairwise (mapping-privatization) scheme among a number of threads mapping scenarios that become available in the IR 2 structure. Instrumentation on a subset of CHStone benchmark was carried out as a validity proof of our proposal, and the results confirmed that our framework kernel is robust.

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“…A raycasting algorithm similar to the one described in [4,6] is used. The algorithm is multi-core parallelized as described in [5].…”

Section: Summary Of Revisionsmentioning

confidence: 99%

BilKristal 4.0: A tool for crystal parameters extraction and defect quantification

Okuyan

Okuyan²

2015

Computer Physics Communications

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In this paper, we present a revised version of BilKristal 3.0 tool. Raycast screenshot functionality is added to provide improved visual analysis. We added atomic distance analysis functionality to assess crystalline defects. We improved visualization capabilities by adding high level cut function definitions. Discovered bugs are fixed and small performance optimizations are made. © 2015 Elsevier B.V. All rights reserved

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Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP

Cited by 14 publications

References 16 publications

MaterialVis: Material visualization tool using direct volume and surface rendering techniques

MaterialVis: Material visualization tool using direct volume and surface rendering techniques

Incremental Banerjee test conditions committing for robust parallelization framework

BilKristal 4.0: A tool for crystal parameters extraction and defect quantification

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