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- W2118536731 abstract "We describe the FeasNewt mesh-quality optimization benchmark. The performance of the code is dominated by three phases - gradient evaluation, Hessian evaluation and assembly, and sparse matrix-vector products - that have very different mixtures of floating-point operations and memory access patterns. The code includes an optional runtime data- and iteration-reordering phase, making it suitable for research on irregular memory access patterns. Mesh-quality optimization (or mesh smoothing) is an important ingredient in the solution of nonlinear partial differential equations (PDEs) as well as an excellent surrogate for finite-element or finite-volume PDE solvers." @default.
- W2118536731 created "2016-06-24" @default.
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- W2118536731 date "2006-10-11" @default.
- W2118536731 modified "2023-09-25" @default.
- W2118536731 title "The feasNewt benchmark" @default.
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- W2118536731 doi "https://doi.org/10.1109/iiswc.2005.1526011" @default.
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