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Article

Hardware/Software Solution for Low Power Evaluation of Tsunami Danger

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Institute of Automation and Electrometry SB RAS, 630090 Novosibirsk, Russia
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Institute of Computational Mathematics and Mathematical Geophysics SB RAS, 630090 Novosibirsk, Russia
*
Author to whom correspondence should be addressed.
Academic Editor: Aatmesh Shrivastava
J. Low Power Electron. Appl. 2022, 12(1), 6; https://doi.org/10.3390/jlpea12010006
Received: 13 November 2021 / Revised: 12 January 2022 / Accepted: 18 January 2022 / Published: 21 January 2022
(This article belongs to the Special Issue Low Power AI)
Carbon footprint reduction issues have been drawing more and more attention these days. Reducing the energy consumption is among the basic directions along this line. In the paper, a low-energy approach to tsunami danger evaluation is concerned. After several disaster tsunamis of the XXIst century, the question arises whether is it possible to evaluate in a couple of minutes the tsunami wave parameters, expected at the particular geo location. The point is that it takes around 20 min for the wave to approach the nearest coast after a seismic event offshore of Japan. Currently, the main tool for studying tsunamis is computer modeling. In particular, the expected tsunami height near the coastline, when a major underwater earthquake is detected, can be estimated by a series of numerical experiments of various scenarios of generation and the following wave propagation. Reducing the calculation time of such scenarios and the necessary energy consumption for this is the scope of this study. Moreover, in case of the major earthquake, the electric power shutdown is possible (e.g., the accident at the Fukushima nuclear power station in Japan on 11 May 2011), so the solution should be of low energy-consuming, preferably based at regular personal computers (PCs) or laptops. The way to achieve the requested performance of numerical modeling at the PC platform is a combination of efficient algorithms and their hardware acceleration. Following this strategy, a solution for the fast numerical simulation of tsunami wave propagation has been proposed. Most of tsunami researchers use the shallow-water approximation to simulate tsunami wave propagation at deep water areas. For software implementation, the MacCormack finite-difference scheme has been chosen, as it is suitable for pipelining. For hardware code acceleration, a special processor, that is, the calculator, has been designed at a field-programmable gate array (FPGA) platform. This combination was tested in terms of precision by comparison with the reference code and with the exact solutions (known for some special cases of the bottom profile). The achieved performance made it possible to calculate the wave propagation over a 1000 × 500 km water area in 1 min (the mesh size was compared to 250 m). It was nearly 300 times faster compared to that of a regular PC and 10 times faster compared to the use of a central processing unit (CPU). This result, being implemented into tsunami warning systems, will make it possible to reduce human casualties and economy losses for the so-called near-field tsunamis. The presented paper discussed the new aspect of such implementation, namely low energy consumption. The corresponding measurements for three platforms (PC and two types of FPGA) have been performed, and a comparison of the obtained results of energy consumption was given. As the numerical simulation of numerous tsunami propagation scenarios from different sources are needed for the purpose of coastal tsunami zoning, the integrated amount of the saving energy is expected to be really valuable. For the time being, tsunami researchers have not used the FPGA-based acceleration of computer code execution. Perhaps, the energy-saving aspect is able to promote the use of FPGAs in tsunami researches. The approach to designing special FPGA-based processors for the fast solution of various engineering problems using a PC could be extended to other areas, such as bioinformatics (motif search in DNA sequences and other algorithms of genome analysis and molecular dynamics) and seismic data processing (three-dimensional (3D) wave package decomposition, data compression, noise suppression, etc.). View Full-Text
Keywords: tsunami wave numerical modeling; performance hardware acceleration; reducing energy consumption tsunami wave numerical modeling; performance hardware acceleration; reducing energy consumption
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MDPI and ACS Style

Lavrentiev, M.; Lysakov, K.; Marchuk, A.; Oblaukhov, K.; Shadrin, M. Hardware/Software Solution for Low Power Evaluation of Tsunami Danger. J. Low Power Electron. Appl. 2022, 12, 6. https://doi.org/10.3390/jlpea12010006

AMA Style

Lavrentiev M, Lysakov K, Marchuk A, Oblaukhov K, Shadrin M. Hardware/Software Solution for Low Power Evaluation of Tsunami Danger. Journal of Low Power Electronics and Applications. 2022; 12(1):6. https://doi.org/10.3390/jlpea12010006

Chicago/Turabian Style

Lavrentiev, Mikhail, Konstantin Lysakov, Andrey Marchuk, Konstantin Oblaukhov, and Mikhail Shadrin. 2022. "Hardware/Software Solution for Low Power Evaluation of Tsunami Danger" Journal of Low Power Electronics and Applications 12, no. 1: 6. https://doi.org/10.3390/jlpea12010006

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