Editor’s note: This is one of four profiles of finalists for NVIDIA’s 2018 Global Impact Award, which provides $200,000 to researchers using NVIDIA technology for groundbreaking work that addresses social, humanitarian and environmental problems.
Massive earthquakes, building-size ocean waves, understated warnings. These are some of the conditions that have led to incredible devastation caused by tsunamis.
Working to change that, a team of researchers from the University of Málaga’s Differential Equations, Numerical Analysis and Applications group (known by its Spanish acronym, EDANYA) is using GPUs to refine tsunami early warning systems (TEWS).
The EDANYA group has developed the first GPU-based numerical model, known as Tsunami-HySEA, to accelerate tsunami simulations in the framework of TEWS. The model’s ultimate goal is to save lives and prevent damage in future tsunamis.
“We can do this by trying to reproduce how the tsunami wave will evolve faster than it happens in real time, in the real world,” said Jorge Macías, associate professor at the University of Málaga and member of the EDANYA group. “We are able to estimate what the impact of the tsunami wave will be earlier than it happens, allowing civil protection authorities to use this information to carry out measures aimed at saving lives.”
Accelerating Early Warning Systems
The aim of TEWS is to detect tsunami threats in advance and deploy warnings to those in affected regions to minimize casualties.
Currently, two methods are used to analyze a tsunami’s impact. One uses decision matrices that estimate a tsunami’s impact on the coast based on the earthquake’s magnitude and distance of the coastal area to the epicenter. However, Macías says, this methodology is too rudimentary, extremely inaccurate and presents many drawbacks.
The second relies on large databases of pre-computed, possible tsunami scenarios, based on varying epicenter locations and magnitudes, among other parameters. Simulated tsunamis in the database can be used to assess the impact of actual tsunami. But if a tsunami fails to match one of the pre-computed scenarios, the system won’t provide relevant information, and it can’t perform real-time computations.
Traditional numerical models would need around 10 hours to perform a single simulation of a tsunami on the scale of the 2011 Tōhoku tsunami in northeast Japan. In contrast, the Tsunami-HySEA model can compute such an event in just four to five minutes using two NVIDIA Tesla P100 GPUs.
The Tsunami-HySEA’s ability to assess a tsunami’s impact in real time provides TEWS with the most accurate information to alert people to seek higher ground. And it can produce data to create a more accurate database of future tsunami scenarios much faster than before. The hardware is also inexpensive and more affordable for a much larger community of users.
This achievement has placed the University of Málaga’s EDANYA group among four finalists for NVIDIA’s 2018 Global Impact Award. The award provides an annual grant of $200,000 for groundbreaking work that addresses the world’s most important social and humanitarian problems. The 2018 awards will go to researchers or institutions using NVIDIA technology to achieve breakthrough results with broad impact.
Expanding Beyond Tsunamis
The EDANYA group was among the very first research teams to suggest incorporating GPUs for tsunami simulations. Their work on the subject traces back to 2005, leading to the group publishing its first peer reviewed paper on the topic in 2009, according to Manuel Castro, director of the unit of numerical methods at the University of Málaga.
The group’s success has encouraged other researchers to adopt GPUs in their respective work.
“After our contribution, other tsunami codes have been implemented in GPUs and in CUDA languages,” said Castro. “But, in any case, we were the first ones to provide a complete software/hardware solution for TEWS.”
The Tsunami-HySEA is in preoperational stages at the National Institute of Geophysics and Volcanology and at the Joint Research Center of the European Commission, and is in testing at the National Geographic Institute.
Looking ahead, the EDANYA group also plans to adapt the code behind Tsunami-HySEA for other natural disasters, such as landslides and storm surges.
“Developing countries in tsunami-prone areas are now able to establish their own in-house tsunami flood mapping resources or even to perform real-time simulations because the hardware infrastructure required to perform such fast simulations is now extremely cheap,” said Macías. “I think the software-hardware combination of the Tsunami-HySEA model and NVIDIA GPUs is a real game changer in tsunami research and TEWS, opening a new horizon for these warning systems.”
Check out the work of last year’s Global Impact Award winners.