Konstantin Isupov
Contact info:
Department of Electronic Computing Machines, Vyatka State University,
39 Moskovskaya St., Kirov, 610000, Russia.
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About Me:
About Me:
I am graduated from the Vyatka State University, Russia, in 2010. I received the PhD degree in computer science in 2014. Currently, I am holding assistant professor and senior researcher positions at the Vyatka State University.
Research interests:
Research interests:
High performance computing,
GPU computing, CUDA,
Computer arithmetic,
Residue number system,
Multiple-precision computation.
Profiles:
Profiles:
Publications:
Publications:
Copyright Notice: The documents below are provided as a means of timely dissemination of information and are intended for personal, non-commercial use only. All other uses of the materials, such as reposting or reprinting, require the explicit permission of the copyright holder. Copyrights are held by the authors or by the publishers (IEEE, Elsevier, Springer, etc.).
2022:
2022:
K. Isupov, "Multiple-precision sparse matrix–vector multiplication on GPUs," Journal of Computational Science, vol. 61, p. 101609, 2022. [Crossref][PDF - 50 days' free access]
2021:
2021:
K. Isupov and I. Babeshko, "JAD-Based SpMV Kernels Using Multiple-Precision Libraries for GPUs," in Communications in Computer and Information Science, 2021, vol. 1510, pp. 148-161. [Crossref]
K. Isupov, "An overview of high-performance computing using the residue number system," Program Systems: Theory and Applications, vol. 12, no. 2(49), pp. 137–192, 2021. (In Russian). [Crossref] [PDF]
K. Isupov, "High-performance computation in residue number system using floating-point arithmetic," Computation, vol. 9, no. 2, article no. 9, 2021. [Crossref][PDF]
K. Isupov, I. Babeshko, A. Krutikov "Implementation of multiple precision sparse matrix-vector multiplication on CUDA using ELLPACK format," J. Phys.: Conf. Ser., vol. 1828, article no. 012013, 2021. [Crossref][PDF]
K. Isupov and V. Knyazkov, " Computing the Sparse Matrix-Vector Product in High-Precision Arithmetic for GPU Architectures," in Communications in Computer and Information Science, 2021, vol. 1413, pp. 334–345. [Crossref]
K. Isupov, V. Knyazkov, I. Babeshko, and A. Krutikov, "Implementation and performance evaluation of multiple precision sparse matrix-vector multiplication on CUDA using the residue number system," Problems of informatics, no 1, pp 49-64, 2021. (in Russian). [Crossref]
2020:
2020:
K. Isupov, "Using floating-point intervals for non-modular computations in residue number system," IEEE Access, vol. 8, pp. 58603–58619, 2020. [Crossref][PDF]
K. Isupov, V. Knyazkov, and A. Kuvaev, "Design and implementation of multiple-precision BLAS level 1 functions for graphics processing units ," Journal of Parallel and Distributed Computing, vol. 140, pp. 25–36, 2020. [Crossref]
K. Isupov and V. Knyazkov, "Multiple-precision BLAS library for graphics processing units," in Communications in Computer and Information Science, 2020, vol. 1331, pp. 37–49. [Crossref] [PDF]
K. Isupov and V. Knyazkov, "Efficient GPU implementation of multiple-precision addition based on residue arithmetic ," International Journal of Advanced Computer Science and Applications, vol. 11, no. 9, pp. 1–8, 2020. [Crossref][PDF ]
K. Isupov and V. Knyazkov, "Multiple-precision matrix-vector multiplication on graphics processing units ," Program Systems: Theory and Applications, vol. 11, no. 3(46), pp. 61–84, 2020. [Crossref] [PDF]
K. Isupov, "Performance Data of Multiple-Precision Scalar and Vector BLAS Operations on CPU and GPU," Data in Brief, vol. 30, article no. 105506, 2020. [Crossref][PDF]
2019:
2019:
K. Isupov, A. Kuvaev, and V. Knyazkov, "Data-parallel high-precision multiplication on graphics processing units," in Communications in Computer and Information Science, 2019, vol. 1129, pp. 15–25. [Crossref]
K. Isupov and A. Kuvaev, "Multiple-precision scaled vector addition on graphics processing unit," in Lecture Notes in Computer Science, 2019, vol. 11657, pp. 179–186. [Crossref]
2018:
2018:
K. Isupov and A. Kuvaev, "Multiple-precision summation on hybrid CPU-GPU platforms using RNS-based floating-point representation ," in Proceedings of the 2018 International Conference on Engineering and Telecommunication (EnT-MIPT), Moscow, Russia, Nov. 2018, pp. 153–157. [Crossref]
K. Isupov and V. Knyazkov, "Interval estimation of relative values in residue number system," Journal of Circuits, Systems and Computers, vol. 27, no. 1, p. 1850004, 2018. [Crossref][PDF]
K. Isupov, V. Knyazkov, and A. Kuvaev, “Efficient scaling in RNS using interval estimations,” Computational Technologies, vol. 23, no. 3, pp-39-57, 2018. (In Russian). [Crossref][PDF]
K. Isupov and A. Kuvaev, “High-precision parallel floating-point multiplication on CPU and GPU,” Herald of computer and information technologies, no. 5, pp. 42-50, 2018. (In Russian). [Crossref][PDF]
2017:
2017:
K. Isupov, V. Knyazkov, and A. Kuvaev, "Fast power-of-two RNS scaling algorithm for large dynamic ranges," in Proceedings of the 2017 IVth International Conference on Engineering and Telecommunication (EnT), Moscow, Russia, Nov. 2017, pp. 135-139. [Crossref] [PDF]
K. Isupov, A. Kuvaev, M. Popov, and A. Zaviyalov, "Multiple-precision residue-based arithmetic library for parallel CPU-GPU architectures: Data types and features," in Lecture Notes in Computer Science, vol. 10421, pp. 196-204, 2017. [Crossref][PDF]
2016:
2016:
K. Isupov and V. Knyazkov, "RNS-based data representation for handling multiple-precision integers on parallel architectures," in Proceedings of the 2016 International Conference on Engineering and Telecommunication (EnT), Moscow, Russia, Nov. 2016, pp. 76-79. [Crossref][PDF]
K. Isupov, V. Knyazkov, A. Kuvaev, and M. Popov, "Parallel computation of normalized Legendre polynomials using graphics processors," in Communications in Computer and Information Science, 2016, vol. 687, pp. 172-184. [Crossref][PDF]
2015:
2015:
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