Fastsg
Fastsg: A Fast Routines Library for Sparse Grids. In a complex processor landscape dominated by multi-and many-core processors, simplifying programming plays a crucial role in enhancing developers’ productivity. One way is to use highly tuned library functions. In this paper we present fastsg, an optimized library for the sparse grid technique with support for dimensional truncation. With optimizations for best cache use and vectorization, we improve the performance on one processor core up to a factor of 10. Parallelization using OpenMP scales almost linearly on a 12-core system.
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References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
Sorted by year (- Hupp, Philipp; Jacob, Riko: A cache-optimal alternative to the unidirectional hierarchization algorithm (2016)
- Pfander, David; Heinecke, Alexander; Pflüger, Dirk: A new subspace-based algorithm for efficient spatially adaptive sparse grid regression, classification and multi-evaluation (2016)
- Nance, J.; Kelley, C. T.: A sparse interpolation algorithm for dynamical simulations in computational chemistry (2015)
- Wu, Yuanqing; Kowitz, Christoph; Sun, Shuyu; Salama, Amgad: Speeding up the flash calculations in two-phase compositional flow simulations - the application of sparse grids (2015)
- Buse, Gerrit; Pflüger, Dirk; Jacob, Riko: Efficient pseudorecursive evaluation schemes for non-adaptive sparse grids (2014)