Accelerated Data Science: Analytic Pipelines with GPUs

The RAPIDS suite of open source software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. Join us in March to learn how you can utilize RAPIDS to accelerate your data science!

Agenda

6:30 PM -- Networking & Food

7:00 PM -- Greetings

7:05 PM -- RAPIDS – Open GPU-accelerated Data Science - Corey J. Nolet & Adam Thompson

8:45 PM -- Post event drinks at Green Turtle

Location

Loyola University
Room 210/230
8890 McGaw Rd
Columbia, MD 21045

Please proceed to the second floor once you enter the building.

Parking

There is ample free parking surrounding the building.

Food and Drinks

Complimentary food, such as pizza and chips, and non-alcoholic beverages will be provided.

Talks

RAPIDS – Open GPU-accelerated Data Science
RAPIDS is an initiative driven by NVIDIA to accelerate the complete end-to-end data science ecosystem with GPUs. It consists of several open source projects that expose familiar interfaces making it easy to accelerate the entire data science pipeline- from the ETL and data wrangling to feature engineering, statistical modeling, machine learning, and graph analysis.

Speakers

Corey J. Nolet
Corey has a passion for understanding the world through the analysis of data. He is a developer on the RAPIDS open source project focused on accelerating machine learning algorithms with GPUs.

Adam Thompson
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.

Projects

More information about RAPIDS can be found at https://rapids.ai/ and https://developer.nvidia.com/rapids