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Adaptive Computations for Fluids in Biological Systems
Project Leader:Kathy Yelick, UC Berkeley
Project Manager:Kathy Yelick, UC Berkeley

figure shows the flow pattern in a thin section through the model heart

Heart Simulations Using the Immersed Boundary Method

This figure shows the flow pattern in a thin section through the model heart. The flow pattern is represented by streamlines that are calculated from the 3-D velocity field at the instant shown. Flow passes from the left atrium, through the mitral valve (top center of the figure), and into the left ventricle. The aortic valve (upper left) is closed at this moment.

The purpose of the Adaptive Computations alpha project is to develop easy-to-use software tools to simulate fluid flow in biological systems such as the human heart. Heart simulations play an important role in understanding both healthy and diseased hearts. Simulations can also be used in the development of prosthetic devices, such as artificial heart valves, less invasive surgeries, and education.

Considerable computation on high-performance systems is needed to conduct this research. For example, one simulation of a single heartbeat required 100 CPU-hours on a Cray T90. That simulation used the immersed boundary method, which models a biological system as a set of elastic fibers within an incompressible fluid. This simulation method is best known for its use to simulate fluid flow in the human heart by developers Charles Peskin and David McQueen, mathematics professors at New York University (NYU)and co-winners of the 1994 Cray Research Leadership Award for Breakthrough Computational Science. The immersed boundary method has been used to simulate platelet coagulation during clotting, embryo growth, insect flight, and other biological systems.

To port the code to the IBM Blue Horizon at the San Diego Supercomputer Center (SDSC), participants use the Titanium language and compiler, communication and cache optimizations developed by the Titanium group, and new scalable solver technology from New York University. A parallel implementation will enable the method to be used for much more demanding problems.

The past year saw the first implementation of the immersed boundary method that runs on distributed-memory, parallel platforms using Titanium. The Titanium version of the software (TIBM) is based on a generic version of the method, which separates application-specific features into modules, making it easier to maintain and extend them.

Participants also instantiated the generic code with the features necessary to simulate the heart, as well as software to partition the heart model input across processors and to change the file format to make it consistent with the generic software and improve the I/O performance. In addition, Peskin’s group developed an OpenGL version of the heart visualization software to replace the previous implementation that relied on SGI’s proprietary graphics library.

The full heart model has been run on several parallel machines, including Blue Horizon, a Cray T3E at the National Energy Research Scientific Computing Center (NERSC), an SGI Origin at the National Center for Supercomputing Applications, and the Millennium cluster at UC Berkeley. These runs have demonstrated the portability of Titanium.

The primary goal for the coming year is to improve the performance of the TIBM code, support a second application, and add features necessary for applications other than the heart. The target application is to model a collapsible tube, which exhibits patterns of oscillation under certain conditions, but for which the physics is not understood. This is needed to understand how arteries behave when a blood pressure cuff is applied and how accurately that measurement corresponds to actual pressure in the artery. Researchers at NYU are developing the artery model, and the UC Berkeley group will help add the model to the TIBM code. The alpha project team also will explore the use of the Active Data Repository to support the analysis of 3-D data sets from cardiac blood flow studies.

Monte Carlo Cellular Microphysiology on the Grid

Protein Folding in a Distributed Computing Environment

Bioinformatics Infrastructure for Large-Scale Analyses


Scalable Visualization Toolkits for Brains to Bays

Telescience for Advanced Tomography Applications

Multi-Component Models for Energy and the Environment

Adaptive Computations for Fluids in Biological Systems

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