FINGER: A Symbolic System for Automatic Generation of Numerical Programs in Finite Element Analysis
Journal of Symbolic Computation
Parallel multischeme computation
Journal of Scientific Computing
A tool box for compiler construction
CC '90 Proceedings of the third international workshop on Compiler compilers
Iterated Runge-Kutta methods on parallel computers
SIAM Journal on Scientific and Statistical Computing
TOOLS 7 Proceedings of the seventh international conference on Technology of object-oriented languages and systems
Continuous System Modeling
Operating Systems Theory
Data Structures and Algorithms
Data Structures and Algorithms
Synthesis of Mathematical-Modeling Software
IEEE Software
High-level Mathematical Modeling And Programming
IEEE Software
An Empirical Study of Fortran Programs for Parallelizing Compilers
IEEE Transactions on Parallel and Distributed Systems
A Loop Transformation Theory and an Algorithm to Maximize Parallelism
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Variant Handling, Inheritance and Composition in the ObjectMath Computer Algebra Environment
DISCO '93 Proceedings of the International Symposium on Design and Implementation of Symbolic Computation Systems
High-level Mathematical Modeling And Programming
IEEE Software
Automatic parallelization of simulink applications
Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization
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For a long time efficient use of parallel computers has been hindered by dependencies introduced in software through low-level implementation practice. In this paper we present a programming environment and language called Object-Math (Object oriented Mathematical language for scientific computing), which aims at eliminating this problem by allowing the user to represent mathematical equation-based models directly in the system. The system performs analysis of mathematical models to extract parallelism and automatically generates parallel code for numerical solution.In the context of industrial applications in mechanical analysis, we have so far primarily explored generation of parallel code for solving systems of ordinary differential equations (ODEs), in addition to preliminary work on generating code for solving partial differential equations. Two approaches to extracting parallelism have been implemented and evaluated: extracting parallelism at the equation system level and at the single equation level, respectively. We found that for several applications the corresponding systems of equations do not partition well into subsystems. This means that the equation system level approach is of restricted general applicability. Thus, we focused on the equation-level approach which yielded significant parallelism for ODE systems solution. For the bearing simulation applications we present here, the achieved speedup is however critically dependent on low communication latency of the parallel computer.