In situ ray tracing and computational steering for interactive blood flow simulation

Mazzeo, Marco; Manos, Steven; Coveney, Peter V.

doi:10.1016/j.cpc.2009.10.013

Cited by 12 publications

(17 citation statements)

References 16 publications

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“…Our isosurfacing algorithm requires an insignificant memory footprint but triangle caches larger than the current ones can improve performance drastically. When multiple rays per pixel must be generated, it may be profitable to reorganize the subdomains prior to rendering so as to improve load balancing, for example, in a shuffled fashion as suggested by Mazzeo et al (2010) and Kobayashi et al (1988).…”

Section: (B) Benchmarksmentioning

confidence: 99%

“…We adopt the binary communication pattern presented previously by us (Mazzeo et al 2010) to assemble the subimages and produce the final one.…”

Section: (Iv) Image Compositingmentioning

confidence: 99%

“…Moreover, the two caches share data whenever possible. Ray-voxel traversal is accelerated by the algorithmic optimizations previously described by us (Mazzeo et al 2010). …”

Section: (Iii) Ray Traversal On-the-fly Isosurface Extraction and Trmentioning

confidence: 99%

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Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment

Saksena

Mazzeo

Zasada

et al. 2010

Phil. Trans. R. Soc. A.

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We present very large-scale rheological studies of self-assembled cubic gyroid liquid crystalline phases in ternary mixtures of oil, water and amphiphilic species performed on petascale supercomputers using the lattice-Boltzmann method. These nanomaterials have found diverse applications in materials science and biotechnology, for example, in photovoltaic devices and protein crystallization. They are increasingly gaining importance as delivery vehicles for active agents in pharmaceuticals, personal care products and food technology. In many of these applications, the self-assembled structures are subject to flows of varying strengths and we endeavour to understand their rheological response with the objective of eventually predicting it under given flow conditions. Computationally, our lattice-Boltzmann simulations of ternary fluids are inherently memory-and data-intensive. Furthermore, our interest in dynamical processes necessitates remote visualization and analysis as well as the associated transfer and storage of terabytes of time-dependent data. These simulations are distributed on a highperformance grid infrastructure using the application hosting environment; we employ a novel parallel in situ visualization approach which is particularly suited for such computations on petascale resources. We present computational and I/O performance benchmarks of our application on three different petascale systems.

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Section: (B) Benchmarksmentioning

confidence: 99%

“…We adopt the binary communication pattern presented previously by us (Mazzeo et al 2010) to assemble the subimages and produce the final one.…”

Section: (Iv) Image Compositingmentioning

confidence: 99%

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Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment

Saksena

Mazzeo

Zasada

et al. 2010

Phil. Trans. R. Soc. A.

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“…To date, HEMELB has been successfully applied to the simulation of blood flow in healthy brain vasculature as well as in the presence of ICAs. Particular attention has been paid in obtaining and presenting simulation results in a clinically meaningful way [18]. HEMELB uses the lattice Boltzmann method for fluid dynamics [20] as it allows efficient implementations in large-scale high-performance computing infrastructures.…”

Section: Hemelbmentioning

confidence: 99%

Impact of blood rheology on wall shear stress in a model of the middle cerebral artery

et al. 2013

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One contribution of 25 to a Theme Issue 'The virtual physiological human: integrative approaches to computational biomedicine'. Perturbations to the homeostatic distribution of mechanical forces exerted by blood on the endothelial layer have been correlated with vascular pathologies, including intracranial aneurysms and atherosclerosis. Recent computational work suggests that, in order to correctly characterize such forces, the shear-thinning properties of blood must be taken into account. To the best of our knowledge, these findings have never been compared against experimentally observed pathological thresholds. In this work, we apply the three-band diagram (TBD) analysis due to Gizzi et al. (Gizzi et al. 2011 Three-band decomposition analysis of wall shear stress in pulsatile flows. Phys. Rev. E 83, 031902. (doi:10. 1103/PhysRevE.83.031902)) to assess the impact of the choice of blood rheology model on a computational model of the right middle cerebral artery. Our results show that, in the model under study, the differences between the wall shear stress predicted by a Newtonian model and the well-known Carreau-Yasuda generalized Newtonian model are only significant if the vascular pathology under study is associated with a pathological threshold in the range 0.94-1.56 Pa, where the results of the TBD analysis of the rheology models considered differs. Otherwise, we observe no significant differences.

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“…The lightweight client allows a researcher or clinician to steer HemeLB in realtime, where physical parameters of the vascular system along with various visualization properties can be adjusted in real-time (rotation, zoom, color mapping, opacity etc.). From the computational lab at University College London to the Ranger cluster, 25 frames per second was readily achievable [14]. The scalability of the algorithm results in realtime rendering capabilities, even for high-resolution datasets.…”

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confidence: 99%

Science on the TeraGrid

Katz¹,

Callaghan²,

Harkness³

et al. 2010

CMST

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Abstract:The TeraGrid is an advanced, integrated, nationally-distributed, open, user-driven, US cyberinfrastructure that enables and supports leading edge scientific discovery and promotes science and technology education. It comprises supercomputing resources, storage systems, visualization resources, data collections, software, and science gateways, integrated by software systems and high bandwidth networks, coordinated through common policies and operations, and supported by technology experts. This paper discusses the TeraGrid itself, examples of the science that is occurring on the TeraGrid today, and applications that are being developed to perform science in the future. Key words: computational science applications, high performance computing, grid computing, production grid infrastructure *Steven Manos was a Research Fellow at University College London while this work was conducted CMST SI(1) 81-97 (2010 82effort to build and deploy the world's largest, fastest, most comprehensive, distributed infrastructure for general scientific research. The initial TeraGrid was homogeneous and very "griddy", with users foreseen to be running on multiple systems, both because their codes could run "anywhere", and because in some cases, multiple systems would be needed to support the large runs that were desired. The software that made up the TeraGrid was a set of identical packages on all systems. The TeraGrid has since expanded in capability and number of resource providers. This introduced heterogeneity and thus added complexity to the grid ideals of the initial DTF, as the common software no longer could be completely identical. This led to the concept of common interfaces, with potentially different software underneath the interfaces. Additionally, the users of national center supercomputers were merged into TeraGrid, which led to TeraGrid increasing its focus on supporting these users and their traditional parallel/batch usage modes. The TeraGrid is freely available for US researchers, with allocations determined by a peer-review mechanism. The TeraGrid resources are generally at least 50% dedicated to TeraGrid. Roughly similar to the TeraGrid in terms of a continental-scale set of resources with a focus on HPC users is DEISA/PRACE in Europe, which is a set of national resources with some fractions provided to a set of European users, again determined through a review process. An alternative type of infrastructure is one that is more focused on high throughput computing (HTC), initially in high-energy physics, but increasingly in other domains as well. Filling this role in the US is Open Science Grid (OSG), and in Europe, Enabling Grids for E-sciencE (EGEE), which has recently been transformed into the European Grid Infrastructure (EGI). This paper discusses the TeraGrid itself (Section II), examples of the interesting current uses of the TeraGrid cyberinfrastructure for science (Section III), and examples of applications that are being developed to perform science on the TeraGrid in the future (Section IV) 1 . ...

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In situ ray tracing and computational steering for interactive blood flow simulation

Cited by 12 publications

References 16 publications

Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment

Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment

Impact of blood rheology on wall shear stress in a model of the middle cerebral artery

Science on the TeraGrid

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