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GTC ON-DEMAND

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Abstract:
Well discuss how agencies are being challenged by the massive amount of data theyre collecting from increased numbers of systems and improved sensors. The evolution of mission responsibilities is also leading to an influx of data thats overwhelming to todays analysts. Well show how to redefine the limits of scale and speed in big data analytics and lower the cost of curiosity. Leveraging the power of GPUs enables analysts to interpret large-scale sensor data, social media data, and geospatial data. This occurs in a common operating picture to improve the mission and actionable intelligence at scale.
Well discuss how agencies are being challenged by the massive amount of data theyre collecting from increased numbers of systems and improved sensors. The evolution of mission responsibilities is also leading to an influx of data thats overwhelming to todays analysts. Well show how to redefine the limits of scale and speed in big data analytics and lower the cost of curiosity. Leveraging the power of GPUs enables analysts to interpret large-scale sensor data, social media data, and geospatial data. This occurs in a common operating picture to improve the mission and actionable intelligence at scale.  Back
 
Topics:
Accelerated Data Science
Type:
Sponsored Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91492
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Abstract:

Learn how the OmniSci GPU-Accelerated SQL engine fits into the overall RAPIDS partner ecosystem for open source GPU analytics. Using open data, we'll show how to ingest data that's from both streaming and standing sources, perform descriptive statistics and feature engineering using SQL and cuDF, and return the results as a GPU DataFrame. We'll also describe how data science workflow can be accomplished using tools from the RAPIDS ecosystem, all without the data ever leaving the GPU.

Learn how the OmniSci GPU-Accelerated SQL engine fits into the overall RAPIDS partner ecosystem for open source GPU analytics. Using open data, we'll show how to ingest data that's from both streaming and standing sources, perform descriptive statistics and feature engineering using SQL and cuDF, and return the results as a GPU DataFrame. We'll also describe how data science workflow can be accomplished using tools from the RAPIDS ecosystem, all without the data ever leaving the GPU.

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Topics:
Accelerated Data Science, Deep Learning & AI Frameworks
Type:
Sponsored Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9992
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Abstract:

Protecting crew health is a critical concern for NASA in preparation of long duration, deep-space missions like Mars. Spaceflight is known to affect immune cells. Splenic B-cells decrease during spaceflight and in ground-based physiological models. The key technical innovation presented by our work is end-to-end computation on the GPU with the GPU Data Frame (GDF), running on the DGXStation, to accelerate the integration of immunoglobulin gene-segments, junctional regions, and modifications that contribute to cellular specificity and diversity. Study results are applicable to understanding processes that induce immunosuppressionlike cancer therapy, AIDS, and stressful environments here on earth.

Protecting crew health is a critical concern for NASA in preparation of long duration, deep-space missions like Mars. Spaceflight is known to affect immune cells. Splenic B-cells decrease during spaceflight and in ground-based physiological models. The key technical innovation presented by our work is end-to-end computation on the GPU with the GPU Data Frame (GDF), running on the DGXStation, to accelerate the integration of immunoglobulin gene-segments, junctional regions, and modifications that contribute to cellular specificity and diversity. Study results are applicable to understanding processes that induce immunosuppressionlike cancer therapy, AIDS, and stressful environments here on earth.

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Topics:
AI in Healthcare, Performance Optimization, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8528
Streaming:
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