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Improved Solver Settings for 3D Exploding Wire Simulations in ALEGRA

Doney, Robert; Siefert, Christopher S.; Niederhaus, John H.

We are interested in simulating a variety of problems in 3 dimensions (3D) featuring large electric currents. While 2D simulations have been quite informative, cylindrical symmetry may interfere with a problem’s relevant physics. Specifically, all objects in the domain behave as if they are extruded 360°—turning particles into hoops. In dealing with electrical current, this can have serious ramifications on the current pathways. In 3D (r, φ, z) currents can adjust their pathways anywhere along those 360 degrees given the right conditions; however, in 2D (r, z) those pathways can be completely choked off because an insulating hoop, rather than a particle, is present.

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TYPE Other Report YEAR 2016
DOIOSTI

Ifpack2 User's Guide 1.0

Prokopenko, Andrey V.; Siefert, Christopher S.; Hu, Jonathan J.; Hoemmen, Mark F.; Klinvex, Alicia M.

This is the definitive user manual for the I FPACK 2 package in the Trilinos project. I FPACK 2 pro- vides implementations of iterative algorithms (e.g., Jacobi, SOR, additive Schwarz) and processor- based incomplete factorizations. I FPACK 2 is part of the Trilinos T PETRA solver stack, is templated on index, scalar, and node types, and leverages node-level parallelism indirectly through its use of T PETRA kernels. I FPACK 2 can be used to solve to matrix systems with greater than 2 billion rows (using 64-bit indices). Any options not documented in this manual should be considered strictly experimental .

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TYPE SAND Report YEAR 2016
DOIOSTI

Reducing Communication Costs for Sparse Matrix Multiplication within Algebraic Multigrid

Ballard, Grey B.; Hu, Jonathan J.; Siefert, Christopher S.

We consider the sequence of sparse matrix-matrix multiplications performed during the setup phase of algebraic multigrid. In particular, we show that the most commonly used parallel algorithm is often not the most communication-efficient one for all of the matrix-matrix multiplications involved. By using an alternative algorithm, we show that the communication costs are reduced (in theory and practice), and we demonstrate the performance benefit for both model (structured) and more realistic unstructured problems on large-scale distributed-memory parallel systems. Our theoretical analysis shows that we can reduce communication by a factor of up to 5.4 for a model problem, and we observe in our empirical evaluation communication reductions of factors up to 4.7 for structured problems and 3.7 for unstructured problems. These reductions in communication translate to run-time speedups of up to factors of 2.3 and 2.5, respectively.

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TYPE SAND Report YEAR 2015
DOIOSTI
Results 51–75 of 134
Results 51–75 of 134