The scalability in terms of the time and the energy for several matrix factorizations on a multicore machine

• Autorzy: Bylina Beata , Piekarz Monika

Identyfikatory

DOI

10.15439/2023F3506

• Języki publikacji: EN

Abstrakty

EN

Scalability is an important aspect related to time and energy savings on modern multicore architectures. In this paper, we investigate and analyze scalability in terms of time and energy. We compare the execution time and consumption energy of the LU factorization (without pivoting) and Cholesky, both with Math Kernel Library (MKL) on a multicore machine. In order to save the energy of these multithreaded factorizations, the dynamic voltage and frequency scaling (DVFS) technique was used. This technique allows the clock frequency to be scaled without changing the implementation. An experimental scalability evaluation was performed on an Intel Xeon Gold multicore machine, depending on the number of threads and the clock frequency. Our test results show that scalability in terms of the execution time expressed by the Speedup metric has values close to a linear function with an increase in the number of threads. In contrast, scalability in terms of the energy consumed expressed by the Greenup metric has values close to a logarithmic function with an increase in the number of threads. Both kinds of scalability depend on the clock frequency settings and the number of threads.

Słowa kluczowe

EN

measurement; energy consumption; time-frequency analysis; correlation; multicore processing; scalability; instruction set

PL

pomiar; zużycie energii; analiza czasowo-częstotliwościowa; korelacja; przetwarzanie wielordzeniowe; skalowalność

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2023
• Tom: Vol. 35
• Strony: 895--900
• Opis fizyczny: Bibliogr. 9 poz., tab., wykr.

Twórcy

autor

Bylina Beata

• Maria Curie-Skłodowska University in Lublin Pl. M. Curie-Skłodowskiej 5, 20-031 Lublin, Poland

• https://orcid.org/0000-0002-1327-9747

autor

Piekarz Monika

• Maria Curie-Skłodowska University in Lublin Pl. M. Curie-Skłodowskiej 5, 20-031 Lublin, Poland

• https://orcid.org/0000-0002-3457-9335

Bibliografia

• [1] Intel Math Kernel Library, 2014. http://software.intel.com/enus/articles/intel-mkl/.
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• [4] B. Bylina and M. Piekarz. Time–energy correlation for multithreaded matrix factorizations. Energies, 16, 08 2023. 10.3390/en16176290.
• [5] J. W. Demmel. Applied Numerical Linear Algebra. SIAM, 1997. 10.1137/1.9781611971446.
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• [7] K. Khan, M. Hirki, T. Niemi, J. Nurminen, and Z. Ou. RAPL in action: Experiences in using RAPL for power measurements. ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 3, 01 2018. 10.1145/3177754.
• [8] Y. Ngoko and D. Trystram. Scalability in parallel processing. In S. K. Prasad, A. Gupta, A. L. Rosenberg, A. Sussman, and C. C. Weems, editors, Topics in Parallel and Distributed Computing, Enhancing the Undergraduate Curriculum: Performance, Concurrency, and Programming on Modern Platforms, pages 79–109. Springer, 2018. 10.1007/978-3-319-93109-8_4.
• [9] M. Weiser, B. Welch, A.J. Demers, and S. Shenker. Scheduling for reduced cpu energy. 1st OSDI, pages 13–23, 11 1994.

Uwagi

1. Thematic Tracks Short Papers

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).