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Scientific Programming
Volume 5, Issue 1, Pages 15-24

SPINET: A Parallel Computing Approach to Spine Simulations

Peter G. Kropf,1 Edgar F. A. Lederer,2 Thomas Steffen,3 Karl Guggisberg,4 Jean-Guy Schneider,4 and Peter Schwab4

1Department of Computer Science, Laval University, Quebec City, Canada
2Institute of Computer Science, University of Basel, Switzerland
3Orthopaedic Research Laboratory, Division of Orthopaedic Surgery, McGill University, Montreal, Canada
4Institute of Computer Science and Applied Mathematics, University of Berne, Switzerland

Received 18 November 1994; Accepted 18 September 1995

Copyright © 1996 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Research in scientitic programming enables us to realize more and more complex applications, and on the other hand, application-driven demands on computing methods and power are continuously growing. Therefore, interdisciplinary approaches become more widely used. The interdisciplinary SPINET project presented in this article applies modern scientific computing tools to biomechanical simulations: parallel computing and symbolic and modern functional programming. The target application is the human spine. Simulations of the spine help us to investigate and better understand the mechanisms of back pain and spinal injury. Two approaches have been used: the first uses the finite element method for high-performance simulations of static biomechanical models, and the second generates a simulation developmenttool for experimenting with different dynamic models. A finite element program for static analysis has been parallelized for the MUSIC machine. To solve the sparse system of linear equations, a conjugate gradient solver (iterative method) and a frontal solver (direct method) have been implemented. The preprocessor required for the frontal solver is written in the modern functional programming language SML, the solver itself in C, thus exploiting the characteristic advantages of both functional and imperative programming. The speedup analysis of both solvers show very satisfactory results for this irregular problem. A mixed symbolic-numeric environment for rigid body system simulations is presented. It automatically generates C code from a problem specification expressed by the Lagrange formalism using Maple.