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GTC ON-DEMAND

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Abstract:
NVIDIA IndeX is a scalable scientific data visualization solution for single/multi-GPU systems or GPU clusters and is well suited for implementing complex cloud services easily. The presentation covers many NVIDIA IndeX features such as IndeX's Accelerated Computing API (XAC) for interactive data shading and data processing and introduces novel interfaces for high-bandwidth inferencing on distributed data. The presentation illustrates NVIDIA IndeX applications in astrophysics and demos an interactive 5 TB Galactic Wind data visualization. The talk also highlights the ability to implement new cloud services using NVIDIA IndeX.
NVIDIA IndeX is a scalable scientific data visualization solution for single/multi-GPU systems or GPU clusters and is well suited for implementing complex cloud services easily. The presentation covers many NVIDIA IndeX features such as IndeX's Accelerated Computing API (XAC) for interactive data shading and data processing and introduces novel interfaces for high-bandwidth inferencing on distributed data. The presentation illustrates NVIDIA IndeX applications in astrophysics and demos an interactive 5 TB Galactic Wind data visualization. The talk also highlights the ability to implement new cloud services using NVIDIA IndeX.  Back
 
Topics:
In-Situ & Scientific Visualization, Accelerated Data Science, Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9692
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Abstract:
AI and related technologies are beginning to revolutionize astronomy and astrophysics. As facilities like the Large Synoptic Survey Telescope and the Wide Field InfraRed Telescope come online, data volumes in astronomy will increase. We will describe a deep learning framework that allows astronomers to identify and categorize astronomical objects in enormous datasets with more fidelity than ever. We'll also review new applications of AI in astrophysics, including data analysis and numerical simulation.
AI and related technologies are beginning to revolutionize astronomy and astrophysics. As facilities like the Large Synoptic Survey Telescope and the Wide Field InfraRed Telescope come online, data volumes in astronomy will increase. We will describe a deep learning framework that allows astronomers to identify and categorize astronomical objects in enormous datasets with more fidelity than ever. We'll also review new applications of AI in astrophysics, including data analysis and numerical simulation.  Back
 
Topics:
Astronomy & Astrophysics, Deep Learning & AI Frameworks, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9508
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Abstract:
The vast scales and complex physics of the universe pose a significant challenge for understanding how galaxies form and evolve. Theoretical astrophysicists attempt to model the physical processes that drive the formation of galaxies and other structures via supercomputer simulations, but the fidelity of these simulations are limited by computational power. With the advent of supercomputers powered by NVIDIA GPUs, astrophysical simulations have taken giant strides forward in their ability to model and understand the detailed properties of galaxies. I review some of our progress enabled by NVIDIA GPUs, including large-scale GPU-powered hydrodynamical simulations and Deep Learning applied to enormous astronomical surveys of galaxies.
The vast scales and complex physics of the universe pose a significant challenge for understanding how galaxies form and evolve. Theoretical astrophysicists attempt to model the physical processes that drive the formation of galaxies and other structures via supercomputer simulations, but the fidelity of these simulations are limited by computational power. With the advent of supercomputers powered by NVIDIA GPUs, astrophysical simulations have taken giant strides forward in their ability to model and understand the detailed properties of galaxies. I review some of our progress enabled by NVIDIA GPUs, including large-scale GPU-powered hydrodynamical simulations and Deep Learning applied to enormous astronomical surveys of galaxies.  Back
 
Topics:
Computational Physics, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8677
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Abstract:

Get an overview of how GPUs are used by computational astrophysicists to perform numerical simulations and process massive survey data. Astrophysics represents one of the most computationally heavy sciences, where supercomputers are used to analyze enormous amounts of data or to simulate physical processes that cannot be reproduced in the lab. Astrophysicists strive to stay on the cutting edge of computational methods to simulate the universe or process data faster and with more fidelity. We'll discuss two important applications of GPU supercomputing in astrophysics. We'll describe the astrophysical fluid dynamics code CHOLLA that runs on the GPU-enabled supercomputer Titan at Oak Ridge National Lab and can perform some of the largest astrophysical simulations ever attempted. Then we'll describe the MORPHEUS deep learning framework that classifies galaxy morphologies using the NVIDIA DGX-1 deep learning system.

Get an overview of how GPUs are used by computational astrophysicists to perform numerical simulations and process massive survey data. Astrophysics represents one of the most computationally heavy sciences, where supercomputers are used to analyze enormous amounts of data or to simulate physical processes that cannot be reproduced in the lab. Astrophysicists strive to stay on the cutting edge of computational methods to simulate the universe or process data faster and with more fidelity. We'll discuss two important applications of GPU supercomputing in astrophysics. We'll describe the astrophysical fluid dynamics code CHOLLA that runs on the GPU-enabled supercomputer Titan at Oak Ridge National Lab and can perform some of the largest astrophysical simulations ever attempted. Then we'll describe the MORPHEUS deep learning framework that classifies galaxy morphologies using the NVIDIA DGX-1 deep learning system.

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Topics:
Astronomy & Astrophysics, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7332
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