Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

February 6, 2014

Map-D: A GPU Database…

Filed under: GPU,MapD,NVIDIA — Patrick Durusau @ 8:34 pm

Map-D: A GPU Database for Real-time Big Data Analytics and Interactive Visualization by Todd Mostak (map-D) and Tom Graham (map-D). (MP4)

From the description:

map-D makes big data interactive for anyone! map-D is a super-fast GPU database that allows anyone to interact and visualize streaming big data in real time. Its unique architecture runs 70-1,000x faster than other in-memory databases or big data analytics platforms. To boot, it works with any size or kind of dataset; works with data that is streaming live on to the system; uses cheap, off-the-shelf hardware; is easily scalable.map-D is focused on learning from big data. At the moment, the map-D team is working on projects with MIT CSAIL, the Harvard Center for Geographic Analysis and the Harvard-Smithsonian Center for Astrophysics. Join Todd Mostak and Tom Graham, key members of the map-D team, as they demonstrate the speed and agility of map-D and describe the live processing, search and mapping of over 1 billion tweets.

I have been haunting the GTC On-Demand page waiting for this to be posted.

I had to download the MP4. (Approximately 124 MB) Suspect they are creating a lot of traffic at the GTC On-Demand page.

As a bonus, see also:

Map-D: GPU-Powered Databases and Interactive Social Science Research in Real Time by Tom Graham (Map_D) and Todd Mostak (Map_D) (streaming) or PDF.

From the description:

Map-D (Massively Parallel Database) uses multiple NVIDIA GPUs to interactively query and visualize big data in real-time. Map-D is an SQL-enabled column store that generates 70-400X speedups over other in-memory databases. This talk discusses the basic architecture of the system, the advantages and challenges of running queries on the GPU, and the implications of interactive and real-time big data analysis in the social sciences and beyond.

Suggestions of more links/papers on Map-D greatly appreciated!

Enjoy!

PS: Just so you aren’t too shocked, the Twitter demo involves scanning a billion row database in 5 mili-seconds.

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