AI-driven flood modeling and 3D visualization tools are transforming how communities prepare for and respond to climate risks. In this NVIDIA GTC 2024 session, Guy Schumann and Guillaume Gallion from RSS-Hydro explore how next-generation geospatial applications and high-fidelity visualizations, including NVIDIA Omniverse, can enhance disaster resilience by providing dynamic tools for decision��
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Christopher Bretherton, Senior Director of Climate Modeling at the Allen Institute for AI (AI2), highlights how AI is revolutionizing climate science. In this NVIDIA GTC 2024 session, Bretherton presents advancements in machine learning-based emulators for predicting regional climate changes and precipitation extremes. These tools accelerate climate modeling, making it faster, more efficient��
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Dale Durran, a professor in the Atmospheric Sciences Department at the University of Washington, introduces a breakthrough deep learning model that combines atmospheric and oceanic data to set new climate and weather prediction accuracy standards. In this NVIDIA GTC 2024 session, Durran presents techniques that reduce reliance on traditional parameterizations, enabling the model to bypass��
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Robotics could make everyday life easier by taking on repetitive or time-consuming tasks. At NVIDIA GTC 2024, researchers from Stanford University unveiled BEHAVIOR-1K, a major benchmark designed to train robots to perform 1,000 real-world-inspired activities��such as folding laundry, cooking breakfast, and cleaning up after a party. Using OmniGibson, a cutting-edge simulation environment for��
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Pharmaceutical research demands fast, efficient simulations to predict how molecules interact, speeding up drug discovery. Jiqun Tu, a senior developer technology engineer at NVIDIA, and Ellery Russell, tech lead for the Desmond engine at Schr?dinger, explore advanced GPU optimization techniques designed to accelerate molecular dynamics simulations. In this NVIDIA GTC 2024 session��
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As the demand for high-performance computing (HPC) and AI applications grows, so does the importance of energy efficiency. NVIDIA Principal Developer Technology Engineer, Alan Gray, shares insights on optimizing energy and power efficiency for various applications running on the latest NVIDIA technologies, including NVIDIA H100 Tensor Core GPUs and NVIDIA DGX A100 systems. Traditionally��
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By 2030, John Deere aims for fully autonomous farming, addressing global challenges like labor shortages, sustainability, and food security. Their AI and robotics solutions make farming more efficient and profitable, reduce environmental impact, lower carbon footprints, and promote biodiversity. In this session, Chris Padwick, director of Machine Learning and Computer Vision at John Deere��
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Stephen Jones, a leading expert and distinguished NVIDIA CUDA architect, offers his guidance and insights with a deep dive into the complexities of mapping applications onto massively parallel machines. Going beyond the basics to explore the intricacies of GPU programming, he focuses on practical techniques such as parallel program design and specific details of GPU optimization for improving the��
]]>To fully harness the capabilities of NVIDIA GPUs, optimizing NVIDIA CUDA performance is essential, particularly for developers new to GPU programming. This talk is specifically designed for those stepping into the world of CUDA, providing a solid foundation in GPU architecture principles and optimization techniques. Athena Elafrou, a developer technology engineer at NVIDIA��
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As the use of large language models (LLMs) grows across many applications, such as chatbots and content creation, it��s important to understand the process of scaling and optimizing inference systems to make informed decisions about hardware and resources for LLM inference. In the following talk, Dmitry Mironov and Sergio Perez, senior deep learning solutions architects at NVIDIA��
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