On Distributed Processing Applications in Finite Element Analysisby Edward J. Plaskacz, Argonne Natl Lab, Argonne, IL, USA,
Martin R. Ramirez, Argonne Natl Lab, Argonne, IL, USA,
Sanjeev Gupta, Argonne Natl Lab, Argonne, IL, USA,
Abstract: Computer architectures may be classified by the relationship between their instruction and data streams (SISD, SIMD, MISD, MIMD) and the locality of memory (shared, local). Distributed computing is an emerging parallel technology centering around the LM-MIMD hardware model. Computational platforms falling in this category are network-connected workstations and bus-connected local-memory processors. A methodology for implementing nonlinear finite element analysis on a homogeneous distributed processing network is discussed. The method can also be extended to heterogeneous networks comprised of different machine architectures provided that they have a mutual communication interface. The development environment for the present prototype was comprised of two distributed processing platforms: a Sun sparestation network and an 8-node Intel Touchstone i860 MIMD machine - each platform was used individually. The domain is decomposed serially in a preprocessor. Separate input files are written for each subdomain. These files are read in by local copies of the program executable operating in parallel. Communication between processors is addressed utilizing synchronous message passing. The basic kernel of message passing is the exchange of internal forces which is analogous to the interaction that physical bodies undergo when subjected to internal forces. Results show a best case speedup of 1.95 (97.5% efficiency) for the Intel hypercube using 2 i860 processors and 1.93 (96.5% efficiency) using 2 SUN sparestations on the ethernet network.
Subject Headings: Data processing | Finite element method | Architecture | Distribution functions | Nonlinear finite element analysis | Equipment and machinery | Hydrologic data
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