Highly Scalable Parallel Algorithms for Sparse Matrix Factorization
IEEE Transactions on Parallel and Distributed Systems
Salinas: a scalable software for high-performance structural and solid mechanics simulations
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
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Estimation of oil and gas reservoirs depends on the exact analysis of 3-D seismic images. For this, various kinds of seismic imaging techniques are used to image the subsurface geological structures. We introduce the SWEET algorithm which can calculate the traveltime and amplitude for Kirchhoff migration that is one of seismic imaging techniques. The SWEET algorithm is based on finite element method, and produces very big size linear equations with a huge number of right-hand side vectors. We propose the domain-wise multifrontal solver as the optimal solution method to implement the SWEET algorithm. The SWEET algorithm is successfully implemented and parallelized using our solver and the performance and scalability are shown. We will demonstrate the ability of our solver by solving the largest problem ever solved by direct solvers, and this will result in the highest quality seismic imaging of the 3-D SEG/EAGE salt model