Open Access
Issue |
A&A
Volume 672, April 2023
|
|
---|---|---|
Article Number | A83 | |
Number of page(s) | 20 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202346015 | |
Published online | 04 April 2023 |
- Agarwal, P. K. 2017, in A Journey Through Discrete Mathematics: A Tribute to Jiří Matoušek, eds. M. Loebl, J. Nešetřil, & R. Thomas (Cham: Springer International Publishing), 1 [Google Scholar]
- Alexandrescu, A. 2017, in Leibniz International Proceedings in Informatics (LIPIcs), 75, 16th International Symposium on Experimental Algorithms (SEA 2017), 24, eds. C. S. Iliopoulos, S. P. Pissis, S. J. Puglisi, & R. Raman (Dagstuhl, Germany: Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik), 24:1 [Google Scholar]
- Alonso, D. 2012, ArXiv e-prints [arXiv:1210.1833] [Google Scholar]
- Bentley, J.L. 1975, Commun. ACM, 18, 509 [CrossRef] [Google Scholar]
- Bernardeau, F., Colombi, S., Gaztañaga, E., & Scoccimarro, R. 2002, Phys. Rep., 367, 1 [Google Scholar]
- Blumofe, R. D. & Leiserson, C. E. 1999, J. ACM, 46, 720 [CrossRef] [Google Scholar]
- Chandler, D. 1987, Introduction to Modern Statistical Mechanics (Oxford University Press) [Google Scholar]
- Chhugani, J., Kim, C., Shukla, H. et al. 2012, in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC ’12 (Washington, DC, USA: IEEE Computer Society Press) [Google Scholar]
- Curtin, R. R, Cline, J. R., Slagle, N. P. et al. 2013a, J. Mach. Learn. Res., 14, 801 [Google Scholar]
- Curtin, R. R., March, W. B., Ram, P., et al. 2013b, ArXiv e-prints [arXiv:1304.4327] [Google Scholar]
- da Fonseca, G. D., & Mount, D. M. 2010, Comput. Geometry, 43, 434 [NASA ADS] [CrossRef] [Google Scholar]
- Dawson, K. S, Schlegel, D. J., Ahn, C. P. et al. 2013, AJ, 145, 10 [CrossRef] [Google Scholar]
- Dawson, K. S., Kneib, J.-P., Percival, W. J., et al. 2016, AJ, 151, 44 [Google Scholar]
- de Berg, M., Cheong, O., van Kreveld, M., & Overmars, M. 2008, Computational Geometry: Algorithms and Applications, 3rd edn. (Berlin, Heidelberg: Springer), 386 [Google Scholar]
- DESI Collaboration (Aghamousa, A., et al.) 2016, ArXiv e-prints [arXiv:1611.00036] [Google Scholar]
- Dolatshah, M., Hadian, A., & Minaei-Bidgoli, B. 2015, ArXiv e-prints [arXiv:1511.00628] [Google Scholar]
- Dolence, J., & Brunner, R. J. 2008, in The 9th LCI International Conference on High-Performance Clustered Computing [Google Scholar]
- Donoso, E. 2019, MNRAS, 487, 2824 [NASA ADS] [CrossRef] [Google Scholar]
- Fog, A. 2022, The Microarchitecture of Intel, AMD and VIA CPUs: An Optimization Guide for Assembly Programmers and Compiler Makers [Google Scholar]
- Friedman, J. H., Bentley, J. L., & Finkel, R. A. 1977, ACM Trans. Math. Softw., 3, 209 [Google Scholar]
- Gärtner, B. 1999, in Algorithms – ESA’ 99, ed. J. Nešetřil (Berlin, Heidelberg: Springer), 325 [CrossRef] [Google Scholar]
- Golub, G., & Van Loan, C. 2013, Matrix Computations, Johns Hopkins Studies in the Mathematical Sciences (Johns Hopkins University Press) [Google Scholar]
- Hearin, A. P., Campbell, D., Tollerud, E., et al. 2017, AJ, 154, 190 [Google Scholar]
- Hornbeck, H. 2020, ArXiv e-prints [arXiv:2001.09253] [Google Scholar]
- Intel Corporation 2022, Intel 64 and IA-32 Architectures Optimization Reference Manual [Google Scholar]
- Jarvis, M. 2015, Astrophysics Source Code Library [record ascl:1508.007] [Google Scholar]
- Landy, S. D. & Szalay, A. S. 1993, ApJ, 412, 64 [NASA ADS] [CrossRef] [Google Scholar]
- Larsson, T. 2008, in Linköping Electronic Conference Proceedings, 34, Proceedings of the Annual SIGRAD Conference, Stockholm, 27 [Google Scholar]
- Lueker, G. S. 1978, in 19th Annual Symposium on Foundations of Computer Science (sfcs 1978), 28 [CrossRef] [Google Scholar]
- March, W. B., Connolly, A. J., & Gray, A. G. 2012, in Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’12 (New York, NY, USA: Association for Computing Machinery), 1478 [CrossRef] [Google Scholar]
- Moore, A. W. 2000, in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, UAI’00 (San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.), 397 [Google Scholar]
- Moore, A.W., Connolly, A. J., Genovese, C., et al. 2001, in Mining the Sky, eds. A. J. Banday, S. Zaroubi, & M. Bartelmann, 71 [CrossRef] [Google Scholar]
- Omohundro, S. M. 1989, Five Balltree Construction Algorithms, Tech. Rep. TR-89-063, International Computer Science Institute [Google Scholar]
- Pedregosa, F., Varoquaux, G., Gramfort, A. et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
- Peebles, P. J. E., & Hauser, M. G. 1974, ApJS, 28, 19 [NASA ADS] [CrossRef] [Google Scholar]
- Pen, U.-L., Zhang, T., van Waerbeke, L., et al. 2003, ApJ, 592, 664 [NASA ADS] [CrossRef] [Google Scholar]
- Philcox, O. H. E., Slepian, Z., Hou, J., et al. 2022, MNRAS, 509, 2457 [Google Scholar]
- Ponce, R., Cárdenas-Montes, M., Rodríguez-Vázquez, J. J., Sánchez, E., & Sevilla, I. 2012, in Astronomical Data Analysis Software and Systems XXI, eds. P. Ballester, D. Egret, & N. P. F. Lorente, ASP Conf. Ser., 461, 73 [NASA ADS] [Google Scholar]
- Reid, B., Ho, S., Padmanabhan, N. et al. 2016, MNRAS, 455, 1553 [NASA ADS] [CrossRef] [Google Scholar]
- Ritter, J. 1990, in Graphics Gems, ed. A. S. Glassner (San Diego: Morgan Kaufmann), 301 [CrossRef] [Google Scholar]
- Rohin, Y. 2018, Astron. Comput., 25, 149 [NASA ADS] [CrossRef] [Google Scholar]
- Sinha, M., & Garrison, L. H. 2020, MNRAS, 491, 3022 [Google Scholar]
- Sleator, D. D. & Tarjan, R. E. 1985, J. ACM, 32, 652 [CrossRef] [Google Scholar]
- Slepian, Z., & Eisenstein, D. J. 2015, MNRAS, 454, 4142 [NASA ADS] [CrossRef] [Google Scholar]
- Springel, V. 2005, MNRAS, 364, 1105 [Google Scholar]
- Szapudi, I., & Szalay, A. S. 1997, ArXiv e-prints [arXiv:astro-ph/9704241] [Google Scholar]
- Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Methods, 17, 261 [Google Scholar]
- Welzl, E. 1991, in New Results and New Trends in Computer Science, ed. H. Maurer (Berlin, Heidelberg: Springer Berlin Heidelberg), 359 [Google Scholar]
- Zhang, L. L., & Pen, U.-L. 2005, New A, 10, 569 [NASA ADS] [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.