The energy industry��s digital transformation requires a substantial increase in computational demands for key HPC workloads and applications. This trend is exemplified by advanced seismic imaging methodologies such as reverse time migration (RTM) and full waveform inversion (FWI), where doubling maximum frequency can produce a 16x increase in computational workload. Similarly��
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Hear from ExxonMobil, Honeywell, Siemens Energy, and more as they explore AI and HPC innovation in oil, gas, power, and utilities.
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In a major earthquake, even a few seconds of advance warning can help people prepare �� so Stanford University researchers have turned to deep learning to predict strong shaking and issue early alerts. DeepShake, a spatiotemporal neural network trained on seismic recordings from around 30,000 earthquakes, analyzes seismic signals in real time. By observing the earliest detected waves from an��
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To support its efforts to become climate neutral by 2050, the European Union has launched a Destination Earth initiative to build a detailed digital simulation of the planet that will help scientists map climate development and extreme weather events with high accuracy. The decade-long project will create a digital twin of the Earth, rendered at one-kilometer scale and based on continuously��
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At GTC 21, discover what��s next in AI across the energy industry, including upstream, midstream, downstream, and utilities. Register for free to attend 30+ groundbreaking energy sessions in areas like dynamic energy systems, field planning, geophysics optimization, renewable energy, and seismic image analysis. Reverse time migration (RTM) is a powerful seismic migration technique��
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Researchers at MIT and Harvard University recently published a study outlining how deep learning is helping seismologists detect earthquakes that might have otherwise been missed. Published in the Science Advances Journal last month, the study focused on Oklahoma, a state that before 2009 only experienced around two earthquakes of magnitude 3.0 or higher per year. In 2015, this tally climbed up��
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The Italian multinational oil giant Eni deployed a 18.6 petaflops GPU-accelerated supercomputer, making it the most powerful industrial system in the world. Located outside Milan, the new HPC4 machine will scan for oil and gas reservoirs deep below the Earth. ��This is where the company��s heart is, where we hold our most delicate data and proprietary technology,�� Eni Chief Executive Officer��
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University of San Diego researchers developed a deep learning-based method to identify the molecular structures of natural products such as soil microorganisms, terrestrial plants and, marine life forms. According to the researchers, SMART (Small Molecule Accurate Recognition) ��has the potential to accelerate the molecular structure identification process ten-fold.
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Phil Maechling, a computer scientist at USC��s Southern California Earthquake Center shares how they are using the Tesla GPU-accelerated Titan and Blue Waters supercomputers with CUDA to analyze the impact of earthquakes and why and when they occur. ��Instead of waiting for earthquakes to happen, we do physics-based simulations of ��scenario�� earthquakes,�� said Maechling. ��We use the results to��
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Texas A&M installed a new $2.1 million supercomputer with 10 times the processing power of their previous system Eos, which was launched in 2009. Nicknamed ��Terra,�� the new supercomputer will support projects that include developing new materials, discovering new drugs, forecasting storm surges and managing energy resources. ��Terra represents a new supercomputer iteration deployed at Texas A&M,����
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To accelerate biomedical research, Australia��s Monash University boosted its research infrastructure with a third GPU-accelerated supercomputer called MASSIVE-3. MASSIVE-3 is equipped with both Tesla GPUs and Quadro GPUs for data processing and visualization, driving the new system nearly four times faster than MASSIVE-2. Over the past five years, MASSIVE has played a key role in driving��
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Jeroen Tromp, Professor at Princeton University shares how his team is using the Tesla GPU-accelerated Titan Supercomputer at Oak Ridge National Laboratory to image the earth��s interior on a global scale. Tromp and his team are simulating seismic wave propagation by analyzing hundreds of earthquakes recorded by thousands of stations across the world to create 3D global tomographic maps.
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Thor Johnsen, an HPC Expert at Chevron, talks about how they are using NVIDIA GPUs for seismic imaging and modeling of the subsurface of the earth to create detailed 3D maps used to identify locations for oil drilling. Share your GPU-accelerated science with us: http://nvda.ly/Vpjxr Watch more scientists and researchers share how accelerated computing is #thepathforward: Watch��
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Tom Jordan, Director, Southern California Earthquake at University of Southern California and a team of researchers are using the 27 petaflop Titan Supercomputer at Oak Ridge National Lab with 18,688 Tesla GPUs to develop physics-based earthquake simulations. Their work is helping advance our understanding of earthquake systems, including potential seismic hazards from known faults and the impact��
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Thomas Schulthess, of ETH Zurich and Director of the Swiss National Supercomputing Centre (CSCS) discusses how they are using GPU-accelerated supercomputers for more detailed weather forecasts. Watch Thomas�� talk ��From ��Piz Daint�� to ��Piz Kesch��: The Making of a GPU-based weather forecasting system�� in the NVIDIA GPU Technology Theater at SC15: Watch Now Share your GPU��
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