Algorithms and Data Structures for Numerical Computations with Automatic Precision Estimation
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Abstract
We introduce data structures and algorithms to count numerical inaccuracies arising from usage of floating numbers described in IEEE 754. Here we describe how to estimate precision for some collection of functions most commonly used for array manipulations and training of neural networks. For highly optimized functions like matrix multiplication, we provide a fast estimation of precision and some hint how the estimation can be strengthened.
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Shucheng Chi, Ran Duan, Tianle Xie, and Tianyi Zhang. Faster min-plus product for monotone instances. In Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, pages 1529–1542, 2022. https://doi.org/10.1145/3519935.3520057
Jana Cslovjecsek, Friedrich Eisenbrand, Michal Pilipczuk, Moritz Venzin, and Robert Weismantel. Efficient sequential and parallel algorithms for multistage stochastic integer programming using proximity. arXiv preprint arXiv:2012.11742, 2020. https://doi.org/10.48550/arXiv.2012.11742
Yuzhou Gu, Adam Polak, Virginia Vassilevska Williams, and Yinzhan Xu. Faster monotone min-plus product, range mode, and single source replacement paths. arXiv preprint arXiv:2105.02806, 2021. https://doi.org/10.48550/arXiv.2105.02806
Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Rı́o, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, and Travis E. Oliphant. Array programming with NumPy. Nature, 585(7825):357–362, September 2020. https://doi.org/10.1038/s41586-020-2649-2
Igor V. Netay. Influence of digital fluctuations on behavior of neural networks. Indian Journal of Artificial Intelligence and Neural Networking (IJAINN), 3:1–7, December 2022. DOI: 10.54105/ijainn.A1061.123122
Mohanty, S., & Sahoo, B. (2020). Parallel Algorithms for Discovering Planted (l, d) Motif. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 4, pp. 1452–1461). https://doi.org/10.35940/ijitee.d1521.029420
Mustafa Basthikodi, Ahmed Rimaz Faizabadi, Waseem Ahmed, HPC Based Algorithmic Species Extraction Tool for Automatic Parallelization of Program Code. (2019). In International Journal of Recent Technology and Engineering (Vol. 8, Issue 2S3, pp. 1004–1009). https://doi.org/10.35940/ijrte.b1188.0782s319
Kumar, P., & Rawat, S. (2019). Implementing Convolutional Neural Networks for Simple Image Classification. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 2, pp. 3616–3619). https://doi.org/10.35940/ijeat.b3279.129219
Young, L., York, J. R., & Kil Lee, B. (2023). Implications of Deep Compression with Complex Neural Networks. In International Journal of Soft Computing and Engineering (Vol. 13, Issue 3, pp. 1–6). https://doi.org/10.35940/ijsce.c3613.0713323
Magapu, H., Krishna Sai, M. R., & Goteti, B. (2024). Human Deep Neural Networks with Artificial Intelligence and Mathematical Formulas. In International Journal of Emerging Science and Engineering (Vol. 12, Issue 4, pp. 1–2). https://doi.org/10.35940/ijese.c9803.12040324