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At least 109 records · Page 6

Implementation of Distributed Memory Computing in MOSAIC to Enable Large 3D Simulations of Irradiated Concrete

The concrete biological shield (CBS) of light-water reactors protects workers and the surrounding environment by absorbing neutron and gamma irradiation emitted from the reactor core. The radiation dose increases with the CBS’s operational time and, in the long term, becomes significant enough to raise the question of irradiation effects on concrete—and particularly on the structural integrity of the CBS. Irradiation-induced damage has been identified as one of the main degradation mechanisms in the CBS. Neutron radiation causes the swelling of aggregate-forming minerals at different rates and amplitudes depending on the mineral’s nature. Silicate-bearing minerals such as quartz are particularly sensitive to neutron radiation and experience up to 17.8% volumetric expansion. Aggregates comprise several minerals with different orientations and are, therefore, subject to cracking as a result of mismatch strains. Additionally, the swelling of aggregates creates significant stresses in the surrounding cement paste matrix, which also results in crack formation. In parallel with the collection of characterization and irradiation test data, development of modeling and simulation tools for irradiated concrete is ongoing with the support of the US Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) program. This effort resulted in the development and application of the fast-Fourier transform (FFT)–based code Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) at Oak Ridge National Laboratory.

61 RADIATION PROTECTION AND DOSIMETRY↗

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Choudhary, Alok Nidhi↗

A single-assignment language in a distributed memory multiprocessor

The implementation of the single-assignment programming language SISAL (McGraw et al., 1985) on a Symult 2010 parallel computer is described. The advantages of single-assignment languages over imperative languages in a multiprocessor environment are reviewed; the characteristics of SISAL are summarized; the program-graph generation and dynamic data partitioning procedures are explained; and the application of SISAL in constructing a concurrent iterative multigrid algorithm is discussed in detail and illustrated with diagrams.

Evripidou, P.↗

Mapping implicit spectral methods to distributed memory architectures

Spectral methods were proven invaluable in numerical simulation of PDEs (Partial Differential Equations), but the frequent global communication required raises a fundamental barrier to their use on highly parallel architectures. To explore this issue, a 3-D implicit spectral method was implemented on an Intel hypercube. Utilization of about 50 percent was achieved on a 32 node iPSC/860 hypercube, for a 64 x 64 x 64 Fourier-spectral grid; finer grids yield higher utilizations. Chebyshev-spectral grids are more problematic, since plane-relaxation based multigrid is required. However, by using a semicoarsening multigrid algorithm, and by relaxing all multigrid levels concurrently, relatively high utilizations were also achieved in this harder case.

Overman, Andrea L.↗

Parallel execution of a three-dimensional, chemically reacting, Navier-Stokes code on distributed-memory machines

This paper describes the parallel version of the three-dimensional, chemically reacting, computational fluid dynamics (CFD) code, SPARK. This work was performed on the Intel iPSC/860-based parallel computers. The SPARK code utilizes relatively simple explicit numerical algorithms, but models complex chemical reactions. The code solves the equations over a regular structured mesh so a simple dam decomposition is used to assign work to the individual processors. The explicit nature of the algorithm, combined with the computational intensity of the chemistry calculations, results in a very low communication-to-computation ratio when compared to typical CFD codes. The efficiency of the parallel code is examined and shown to be about 65 percent when the problem size is scaled with the number of processors. Two low-angle wall-jet injection cases are solved to demonstrate the capability of the parallel code for solving large problems efficiently.

Otto, John C.↗

Parallel grid generation algorithm for distributed memory computers

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Moitra, Stuti↗

Equation solvers for distributed-memory computers

A large number of scientific and engineering problems require the rapid solution of large systems of simultaneous equations. The performance of parallel computers in this area now dwarfs traditional vector computers by nearly an order of magnitude. This talk describes the major issues involved in parallel equation solvers with particular emphasis on the Intel Paragon, IBM SP-1 and SP-2 processors.

Storaasli, Olaf O.↗

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

Dynamic mesh adaption on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load imbalance among processors on a parallel machine. This paper describes the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution cost is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35% of the mesh is randomly adapted. For large-scale scientific computations, our load balancing strategy gives almost a sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remapper yields processor assignments that are less than 3% off the optimal solutions but requires only 1% of the computational time.

Biswas, Rupak↗

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

Dynamic mesh adaptation on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load inbalances among processors on a parallel machine. This paper described the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution coast is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35 percent of the mesh is randomly adapted. For large scale scientific computations, our load balancing strategy gives an almost sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remappier yields processor assignments that are less than 3 percent of the optimal solutions, but requires only 1 percent of the computational time.

Biswas, Rupak↗

Computation of Coupled Thermal-Fluid Problems in Distributed Memory Environment

The thermal-fluid coupling problems are very important to aerospace and engineering applications. Instead of analyzing heat transfer and fluid flow separately, this study merged two well-accepted engineering solution methods, SINDA for thermal analysis and FDNS for fluid flow simulation, into a unified multi-disciplinary thermal fluid prediction method. A fully conservative patched grid interface algorithm for arbitrary two-dimensional and three-dimensional geometry has been developed. The state-of-the-art parallel computing concept was used to couple SINDA and FDNS for the communication of boundary conditions through PVM (Parallel Virtual Machine) libraries. Therefore, the thermal analysis performed by SINDA and the fluid flow calculated by FDNS are fully coupled to obtain steady state or transient solutions. The natural convection between two thick-walled eccentric tubes was calculated and the predicted results match the experiment data perfectly. A 3-D rocket engine model and a real 3-D SSME geometry were used to test the current model, and the reasonable temperature field was obtained.

Wei, H.↗

A Portable 3D FFT Package for Distributed-Memory Parallel Architectures

A parallel algorithm for 3D FFTs is implemented as a series of local 1D FFTs combined with data transposes. This allows the use of vendor supplied (often fully optimized) sequential 1D FFTs. The FFTs are carried out in-place by using an in-place data transpose across the processors.

fast Fourrier transform FFT parallel processing↗