5 finalists for the esteemed high-performance computing award have achieved breakthroughs in local weather modeling, fluid simulation and extra with the Alps, JUPITER and Perlmutter supercomputers.
5 finalists for the Gordon Bell Prize for excellent achievements in high-performance computing (HPC) are utilizing NVIDIA-powered supercomputers for his or her vital work in local weather modeling, supplies science, fluid simulation, geophysics and digital design.
Introduced right this moment at SC25, the finalists’ tasks are driving AI and HPC for science utilizing physics simulation, high-precision math and different superior supercomputing strategies, accelerating breakthroughs throughout climate forecasting, semiconductor design, house exploration and different fields. Their outcomes are open and accessible on ArXiv.
The supercomputers powering their work embrace:
- Alps — hosted on the Swiss Nationwide Supercomputing Centre (CSCS) and powered by greater than 10,000 NVIDIA GH200 Grace Hopper Superchips.
- Perlmutter — hosted on the Nationwide Power Analysis Scientific Computing Heart (NERSC) and powered by NVIDIA accelerated computing.
- JUPITER — Europe’s first exascale supercomputer, hosted on the Jülich Supercomputing Centre (JSC) and powered by the NVIDIA Grace Hopper platform and Quantum-X800 InfiniBand networking.
A rendering of JUPITER supercomputer racks that includes the NVIDIA Grace Hopper platform. Video courtesy of Forschungszentrum Jülich / Sascha Kreklau.
“At CSCS, we don’t simply assist open science — we speed up it,” stated Thomas Schulthess, director of CSCS. “The extraordinary breakthroughs by this 12 months’s 5 Gordon Bell finalists in local weather modeling, supplies science, fluid dynamics and digital twins stand as irrefutable proof: with out the Alps supercomputer, these scientific discoveries merely wouldn’t exist. Pushing computational boundaries turns daring targets into actuality, delivering scientific revolutions that may redefine our world.”
Study extra in regards to the 5 finalists’ tasks under.
ICON: Modeling Earth at Kilometer-Scale
A novel configuration for the ICON Earth system mannequin — developed by researchers on the Max Planck Institute for Meteorology, German Local weather Computing Centre (DKRZ), CSCS, JSC, ETH Zurich and NVIDIA — is poised to allow extra correct climate forecasts and a deeper understanding of how the planet works.
By modeling the whole Earth’s techniques at kilometer-scale decision, ICON can seize the circulate of vitality, water and carbon by the ambiance, oceans and land with distinctive element and unprecedented temporal compression — permitting about 146 days to be simulated each 24 hours — which permits extra environment friendly local weather simulations projecting as much as a long time ahead.
A simulation of carbon dioxide flux utilizing the ICON mannequin.
“Integrating all important elements of the Earth system within the ICON mannequin at an unprecedented decision of 1 kilometer permits researchers to see full world Earth system info on native scales and study extra in regards to the implications of future warming for each individuals and ecosystems,” stated Daniel Klocke, computational infrastructure and mannequin improvement group chief at Max Planck Institute for Meteorology.
ORBIT-2: Exascale Imaginative and prescient Basis Fashions for Climate and Local weather Modeling
Developed as a part of a collaboration between Oak Ridge Nationwide Laboratory, NVIDIA and others — and operating on the Alps supercomputer — ORBIT-2 is an AI basis mannequin for climate and local weather downscaling that demonstrates unparalleled scalability and precision.
Tapping into exascale computing and algorithmic innovation, ORBIT-2 overcomes challenges confronted by conventional local weather fashions with spatial hyper-resolution downscaling, a way that creates high-resolution knowledge from lower-resolution sources. This allows groups to seize and predict way more localized phenomena like city warmth islands, excessive precipitation occasions and refined shifts in monsoon patterns.
“NVIDIA’s superior supercomputing applied sciences enabled ORBIT-2 to realize distinctive scalability, reliability and impression on the intersection of AI and high-performance computing on NVIDIA platforms,” stated Prasanna Balaprakash, director of AI packages and part head for knowledge and AI techniques at Oak Ridge Nationwide Laboratory.
QuaTrEx: Advancing Transistor Design By way of Nanoscale Machine Modeling
A staff from ETH Zurich has superior nanoscale digital machine modeling with QuaTrEx, a bundle of algorithms that may enhance the design of next-generation transistors.
Operating on the Alps supercomputer with NVIDIA GH200 Superchips, QuaTrEx can simulate units with greater than 45,000 atoms with FP64 efficiency and excessive parallel-computing effectivity. This allows quicker, extra correct design of transistors, known as NREFTs, that will probably be essential for the semiconductor trade.
A simulation of the circulate of electrons in a nanoribbon transistor. Video courtesy of ETH Zurich.
“Entry to Alps was instrumental within the improvement of QuaTrEx,” stated Mathieu Luisier, full professor of computational nanoelectronics at ETH Zurich. “It allowed us to simulate units that we couldn’t think about dealing with only a few months in the past.”
Simulating Spacecraft at File-Breaking Scales With the MFC Movement Solver
Designing spacecrafts, particularly these with many small engines, requires detailed simulation, as engines packed intently collectively could cause their exhaust to work together and warmth up a rocket’s base.
Operating on the Alps supercomputer, MFC, an open-source solver developed by the Georgia Institute of Know-how in collaboration with NVIDIA and others, permits fluid circulate simulation 4x quicker and with over 5x larger vitality effectivity whereas sustaining the identical accuracy because the earlier world document. Based mostly on full-scale runs on Alps, MFC is anticipated to run at 10x the size of the earlier world document on JUPITER. This paves the way in which for quicker, extra correct design of vital elements for house exploration.
A rocket engine simulation utilizing computational fluid dynamics. Video courtesy of the Georgia Institute of Know-how.
“Our new info geometric regularization methodology, mixed with the NVIDIA GH200 Superchip’s unified digital reminiscence and mixed-precision capabilities, has drastically improved the effectivity of simulating advanced computational fluid flows, enabling us to simulate rocket engine plumes at unprecedented scales,” stated Spencer Bryngelson, assistant professor in computational science and engineering on the Georgia Institute of Know-how.
A Digital Twin for Tsunami Early Warning
The College of Texas at Austin, Lawrence Livermore Nationwide Laboratory and the College of California San Diego have created the world’s first digital twin that may difficulty real-time probabilistic tsunami forecasts based mostly on a full-physics mannequin.
Utilized to the Cascadia subduction zone within the Pacific Northwest, the digital twin achieved advanced computations that will usually take 50 years on 512 GPUs in simply 0.2 seconds on the Alps and Perlmutter supercomputers, representing a ten billion-fold speedup.
“For the primary time, real-time sensor knowledge will be quickly mixed with full-physics modeling and uncertainty quantification to present individuals an opportunity to behave earlier than catastrophe strikes,” stated Omar Ghattas, professor of mechanical engineering at UT Austin. “This framework offers a foundation for predictive, physics-based emergency-response techniques throughout numerous hazards.”
For the tsunami digital twin, ICON and MFC tasks, NVIDIA CUDA-X libraries performed a key position in maximizing the efficiency and effectivity of the advanced simulations. ICON additionally faucets into NVIDIA CUDA Graphs, which permit work to be outlined as graphs moderately than single operations.
Study extra in regards to the newest supercomputing developments by becoming a member of NVIDIA at SC25, operating by Thursday, Nov. 20.
