388 research outputs found
Computational Methods in Science and Engineering : Proceedings of the Workshop SimLabs@KIT, November 29 - 30, 2010, Karlsruhe, Germany
In this proceedings volume we provide a compilation of article contributions equally covering applications from different research fields and ranging from capacity up to capability computing. Besides classical computing aspects such as parallelization, the focus of these proceedings is on multi-scale approaches and methods for tackling algorithm and data complexity. Also practical aspects regarding the usage of the HPC infrastructure and available tools and software at the SCC are presented
Folding@home: achievements from over twenty years of citizen science herald the exascale era
Simulations of biomolecules have enormous potential to inform our
understanding of biology but require extremely demanding calculations. For over
twenty years, the Folding@home distributed computing project has pioneered a
massively parallel approach to biomolecular simulation, harnessing the
resources of citizen scientists across the globe. Here, we summarize the
scientific and technical advances this perspective has enabled. As the
project's name implies, the early years of Folding@home focused on driving
advances in our understanding of protein folding by developing statistical
methods for capturing long-timescale processes and facilitating insight into
complex dynamical processes. Success laid a foundation for broadening the scope
of Folding@home to address other functionally relevant conformational changes,
such as receptor signaling, enzyme dynamics, and ligand binding. Continued
algorithmic advances, hardware developments such as GPU-based computing, and
the growing scale of Folding@home have enabled the project to focus on new
areas where massively parallel sampling can be impactful. While previous work
sought to expand toward larger proteins with slower conformational changes, new
work focuses on large-scale comparative studies of different protein sequences
and chemical compounds to better understand biology and inform the development
of small molecule drugs. Progress on these fronts enabled the community to
pivot quickly in response to the COVID-19 pandemic, expanding to become the
world's first exascale computer and deploying this massive resource to provide
insight into the inner workings of the SARS-CoV-2 virus and aid the development
of new antivirals. This success provides a glimpse of what's to come as
exascale supercomputers come online, and Folding@home continues its work.Comment: 24 pages, 6 figure
Molecular simulations and visualization: introduction and overview
Here we provide an introduction and overview of current progress in the field of molecular simulation and visualization, touching on the following topics: (1) virtual and augmented reality for immersive molecular simulations; (2) advanced visualization and visual analytic techniques; (3) new developments in high performance computing; and (4) applications and model building
Numerical simulation of cellular blood flow
In order to simulate cellular blood, a coarse-grained spectrin-link (SL) red blood cell (RBC) membrane model is coupled with a lattice-Boltzmann (LB) based suspension solver. The LB method resolves the hydrodynamics governed by the Navier--Stokes equations while the SL method accurately models the deformation of RBCs under numerous configurations. This method has been parallelized using Message Passing Interface (MPI) protocols for the simulation of dense suspensions of RBCs characteristic of whole blood on world-class computing resources.
Simulations were performed to study rheological effects in unbounded shear using the Lees-Edwards boundary condition with good agreement with rotational viscometer results from literature. The particle-phase normal-stress tensor was analyzed and demonstrated a change in sign of the particle-phase pressure from low to high shear rates due to RBCs transitioning from a compressive state to a tensile state in the flow direction. Non-Newtonian effects such as viscosity shear thinning were observed for shear rates ranging from 14-440 inverse seconds as well as the strong dependence on hematocrit at low shear rates. An increase in membrane bending energy was shown to be an important factor for determining the average orientation of RBCs, which ultimately affects the suspension viscosity. The shear stress on platelets was observed to be higher than the average shear stress in blood, which emphasizes the importance of modeling platelets as finite particles.
Hagen-Poiseuille flow simulations were performed in rigid vessels for investigating the change in cell-depleted layer thickness with shear rate, the FĂĄhraeus-Linqvist effect, and the process of platelet margination. The process of platelet margination was shown to be sensitive to platelet shape. Specifically, it is shown that lower aspect ratio particles migrate more rapidly than thin disks. Margination rate is shown to increase with hematocrit, due to the larger number of RBC-platelet interactions, and with the increase in suspending fluid viscosity.PhDCommittee Chair: Aidun, Cyrus; Committee Member: Bader, David; Committee Member: Ku, David; Committee Member: Neitzel, Paul; Committee Member: Yoganathan, Aji
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Modeling Cardiovascular Hemodynamics Using the Lattice Boltzmann Method on Massively Parallel Supercomputers
Accurate and reliable modeling of cardiovascular hemodynamics has the potential to improve understanding of the localization and progression of heart diseases, which are currently the most common cause of death in Western countries. However, building a detailed, realistic model of human blood flow is a formidable mathematical and computational challenge. The simulation must combine the motion of the fluid, the intricate geometry of the blood vessels, continual changes in flow and pressure driven by the heartbeat, and the behavior of suspended bodies such as red blood cells. Such simulations can provide insight into factors like endothelial shear stress that act as triggers for the complex biomechanical events that can lead to atherosclerotic pathologies. Currently, it is not possible to measure endothelial shear stress in vivo, making these simulations a crucial component to understanding and potentially predicting the progression of cardiovascular disease. In this thesis, an approach for efficiently modeling the fluid movement coupled to the cell dynamics in real-patient geometries while accounting for the additional force from the expansion and contraction of the heart will be presented and examined. First, a novel method to couple a mesoscopic lattice Boltzmann fluid model to the microscopic molecular dynamics model of cell movement is elucidated. A treatment of red blood cells as extended structures, a method to handle highly irregular geometries through topology driven graph partitioning, and an efficient molecular dynamics load balancing scheme are introduced. These result in a large-scale simulation of the cardiovascular system, with a realistic description of the complex human arterial geometry, from centimeters down to the spatial resolution of red-blood cells. The computational methods developed to enable scaling of the application to 294,912 processors are discussed, thus empowering the simulation of a full heartbeat. Second, further extensions to enable the modeling of fluids in vessels with smaller diameters and a method for introducing the deformational forces exerted on the arterial flows from the movement of the heart by borrowing concepts from cosmodynamics are presented. These additional forces have a great impact on the endothelial shear stress. Third, the fluid model is extended to not only recover Navier-Stokes hydrodynamics, but also a wider range of Knudsen numbers, which is especially important in micro- and nano-scale flows. The tradeoffs of many optimizations methods such as the use of deep halo level ghost cells that, alongside hybrid programming models, reduce the impact of such higher-order models and enable efficient modeling of extreme regimes of computational fluid dynamics are discussed. Fourth, the extension of these models to other research questions like clogging in microfluidic devices and determining the severity of co-arctation of the aorta is presented. Through this work, a validation of these methods by taking real patient data and the measured pressure value before the narrowing of the aorta and predicting the pressure drop across the co-arctation is shown. Comparison with the measured pressure drop in vivo highlights the accuracy and potential impact of such patient specific simulations. Finally, a method to enable the simulation of longer trajectories in time by discretizing both spatially and temporally is presented. In this method, a serial coarse iterator is used to initialize data at discrete time steps for a fine model that runs in parallel. This coarse solver is based on a larger time step and typically a coarser discretization in space. Iterative refinement enables the compute-intensive fine iterator to be modeled with temporal parallelization. The algorithm consists of a series of prediction-corrector iterations completing when the results have converged within a certain tolerance. Combined, these developments allow large fluid models to be simulated for longer time durations than previously possible.Engineering and Applied Science
3D time-varying simulations of Ca2+ dynamics in arterial coupled cells: A massively parallel implementation
Preferential locations of atherosclerotic plaque are strongly associated with the areas of low wall shear stress and disturbed haemodynamic characteristics such as flow detachment, flow recirculation and oscillatory flow. The areas of low wall shear stress are also associated with the reduced production of adenosine triphosphate in the endothelial layer, as well as the resulting reduced production of inositol trisphosphate (IP3). The subsequent variation in Ca2+ signalling and nitric oxide synthesis could lead to the impairment of the atheroprotective function played by nitric oxide. In previous studies, it has been suggested that the reduced IP3 and Ca2+ signalling can explain the correlation of atherosclerosis with induced low WSS and disturbed flow characteristics. The massively parallel implementation described in this article provides insight into the dynamics of coupled smooth muscle cells and endothelial cells mapped onto the surface of an idealised arterial bifurcation. We show that variations in coupling parameters, which model normal and pathological conditions, provide vastly different smooth muscle cell Ca2+ dynamics and wave propagation profiles. The extensibility of the coupled cells model and scalability of the implementation provide a solid framework for in silico investigations of the interaction between complex cellular chemistry and the macro-scale processes determined by fluid dynamics
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