An Efficient LRnLA Algorithm and Data Structure for Manycore and Multicore Computers with Hierarchical Cache
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Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-38864-4_3
Reference23 articles.
1. Bailey, P., Myre, J., Walsh, S.D., Lilja, D.J., Saar, M.O.: Accelerating lattice Boltzmann fluid flow simulations using graphics processors. In: International Conference on Parallel Processing, ICPP 2009, pp. 550–557. IEEE (2009). https://doi.org/10.1109/ICPP.2009.38
2. Endo, T.: Applying recursive temporal blocking for stencil computations to deeper memory hierarchy. In: 2018 IEEE 7th Non-volatile Memory Systems and Applications Symposium (NVMSA), pp. 19–24. IEEE (2018)
3. Geier, M., Schönherr, M.: Esoteric twist: an efficient in-place streaming algorithms for the lattice Boltzmann method on massively parallel hardware. Computation 5(2), 19 (2017). https://doi.org/10.3390/computation5020019
4. Krüger, T., Kusumaatmaja, H., Kuzmin, A., Shardt, O., Silva, G., Viggen, E.M.: The lattice Boltzmann method. Springer 10(978-3), 4–15 (2017)
5. Lehmann, M., Krause, M.J., Amati, G., Sega, M., Harting, J., Gekle, S.: Accuracy and performance of the lattice Boltzmann method with 64-bit, 32-bit, and customized 16-bit number formats. Phys. Rev. E 106(1), 015,308 (2022)
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