Supercomputing and Computation

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Linear Algebra


The aim of the Numerical Linear Algebra research program is developing key numerical linear algebra techniques in support of large-scale computational science applications of importance to the Office of Science. The project is developing algorithms that minimize data movement and global synchronization in preparation for exascalescale computing that will have an impact on applications in fusion, materials, and nuclear energy. The technology roadmapspredict power and data movement will be important issues in the path to exascale computing. The project re-evaluates and adapts out-of-core (or external memory) algorithms and the latest development in communication avoiding algorithm to minimize data movement and communication for numerical linear algebra. In the near future, the parallel out-of-core algorithms such as LU, QR, and Cholesky factorization can be adapted to minimize the amount of costly data movement between GPU and CPU. This would allow efficient solution of significant problems that are larger than available GPU device memory on the Cray XK6 Titan Supercomputer.

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