No
Yes
View More
View Less
Working...
Close
OK
Cancel
Confirm
System Message
Delete
Schedule
An unknown error has occurred and your request could not be completed. Please contact support.
Scheduled
Wait Listed
Personal Calendar
Speaking
Conference Event
Meeting
Interest
Schedule TBD
Conflict Found
This session is already scheduled at another time. Would you like to...
Loading...
Please enter a maximum of {0} characters.
Please enter a maximum of {0} words.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Reply
Replies ()
Search
New Post
Microblog
Microblog Thread
Post Reply
Post
Your session timed out.
This web page is not optimized for viewing on a mobile device. Visit this site in a desktop browser to access the full set of features.
2017 GTC San Jose

S7433 - How to Achieve Real-Time Analytics on a Data Lake Using GPUs

Session Speakers
Session Description

The complexities associated with development and ongoing management of a data lake that aims to deliver real-time analytic response can be costly and overwhelming. To get real-time analytic response on live, streaming data, consider plugging a GPU-accelerated database into your data lake. GPUs are often embedded in compute-intensive technologies like video games, cars, and mobile devices. They're now gaining traction in the data center. This talk will describe how a GPU-accelerated, scale-out, in-memory database brings orders of magnitude more compute power, with a significantly smaller hardware footprint, to provide unrivaled analytic capabilities. Get the latest information on GPUs, and how their multi-core architecture can process many computations efficiently and quickly, making them ideal for today's streaming datasets and IoT use cases.


Additional Session Information
Beginner
Talk
AI Startup Accelerated Analytics Deep Learning and AI Intelligent Machines and IoT Real-Time Graphics
Software
25 minutes
Session Schedule