An efficient parallel immersed boundary algorithm using a pseudo-compressible fluid solver

We propose an efficient algorithm for the immersed boundary method on distributed-memory architectures, with the computational complexity of a completely explicit method and excellent parallel scaling. The algorithm utilizes the pseudo-compressibility method recently proposed by Guermond and Minev [Comptes Rendus Mathematique, 348:581-585, 2010] that uses a directional splitting strategy to discretize the incompressible Navier-Stokes equations, thereby reducing the linear systems to a series of one-dimensional tridiagonal systems. We perform numerical simulations of several fluid-structure interaction problems in two and three dimensions and study the accuracy and convergence rates of the proposed algorithm. For these problems, we compare the proposed algorithm against other second-order projection-based fluid solvers. Lastly, the strong and weak scaling properties of the proposed algorithm are investigated

Holistic Characterization of Parallel Programming Models in a Distributed Memory Environment

The popularity of cluster computing has increased focus on usability, especially in the area of programmability. Languages and libraries that require explicit message passing have been the standard. New languages, designed for cluster computing, are coming to the forefront as a way to simplify parallel programming. Titanium and Fortress are examples of this new class of programming paradigms. This work holistically characterizes these languages and contrasts them with the standard model of parallel programming, and presents benchmark results of small computational kernels written in these languages and models

Distributed immersed boundary simulation in Titanium

Abstract. The immersed boundary method is a general technique for modeling elastic boundaries immersed within a viscous, incompressible fluid. The method has been applied to several biological and engineering systems, including large scale models of the heart and cochlea. These simulations have the potential to improve our basic understanding of the biological systems they model and aid in the development of surgical treatments and prosthetic devices. Despite the popularity of the immersed boundary method and the desire to scale the problems to accurately capture the details of the physical systems, parallelization for large scale distributed memory machine has proven challenging. The primary reason is a classic locality and load balance tradeoff that arises in distributing the immersed boundary data structure across processors. In this paper we describe a parallelized algorithm for the immersed boundary method that is designed for scalability on distributed memory multiprocessors and clusters of SMPs. It is implemented using the Titanium language, a Java-based high performance scientific computing. Our software package, called IB, takes advantage of the object-oriented features of Titanium to provide a framework for simulating immersed boundaries that separates the generic immersed boundary method code from the specific application features that define the immersed boundary structure and the forces that arise from those structures. Our results demonstrate the scalability of our design and the feasibility of large scale immersed boundary computations with the IB package. 1