"Parallel Algorithms for Sparse Matrices in an Industrial Optimization Software"
, Serie Internationaler Universitätslehrgang Informatics: Engineering & Management (ISI Hagenberg), 7-2008
Parallel Algorithms for Sparse Matrices in an Industrial Optimization Software
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Optimization problems have an important role in industry, and the finite element method is a popular solution to solve optimization problems numerically. The finite element method rely on linear algebra, high performance linear equation solvera are there important topic in applied science. In this thesis, we study the high performance forward/backward substitution method by means of parallel computing.We implement various solutions and benchmark each of them in detail on two computers with different hardware architectures; one is a shared memory multicore machine, and the other one is a multicore machine with virtual shared memory machine. We tried two programming models, MPI and POSIX threading, and find the difference of these programming models by run benchmarks on two computers. We achieve good speedup by integrating some solutions.