addressalign-toparrow-leftarrow-rightbackbellblockcalendarcameraccwcheckchevron-downchevron-leftchevron-rightchevron-small-downchevron-small-leftchevron-small-rightchevron-small-upchevron-upcircle-with-checkcircle-with-crosscircle-with-pluscontroller-playcrossdots-three-verticaleditemptyheartexporteye-with-lineeyefacebookfolderfullheartglobegmailgooglegroupshelp-with-circleimageimagesinstagramFill 1light-bulblinklocation-pinm-swarmSearchmailmessagesminusmoremuplabelShape 3 + Rectangle 1ShapeoutlookpersonJoin Group on CardStartprice-ribbonprintShapeShapeShapeShapeImported LayersImported LayersImported Layersshieldstartickettrashtriangle-downtriangle-uptwitteruserwarningyahoo

GPUs for Graph and Predictive Analytics (+beer, swag & fun-foods)

Brad Bebee, Chief Executive Officer, Blazegraph

Free beer + drinks, swag, candy & more!

A Database Month event http://www.DBMonth.com/database/gpu-analytics

Apache Spark and GPUs are two of the biggest stories in Data Science and Analytics in the past year. Apache Spark makes it easy to build analytics over large scale data sets. NVIDIA GPUs provide the computational power for machine and deep learning challenges.

However, It is non-trivial to exploit the power of GPUs and scale applications onto multi-core, parallel architectures. GPU algorithms not only require significant expertise to develop, but also intimate knowledge of the CPU and GPU memory systems, and detailed knowledge of the Compute Unified Device Architecture (CUDA), Writing fast, efficient data analytics for graph and machine learning on GPUs can be hard due to the complexities of CUDA and achieving effective parallelism.

DASL and SPARQL are high-level languages for graph and machine learning algorithms (DASL) and graph pattern matching (SPARQL) that provide speedups of up to 1,000x over Spark native and up to 300x over leading graph databases when executed on the BlazeGraph platform.

We will present Blazegraph GPU benchmarking results against our SPARQL-enabled, non-GPU Blazegraph platform over the Lehigh University Benchmark (LUBM) and Berlin Sparql Benchmark (BSBM) demonstrating[masked]X speed-up. Users of the RDF/SPARQL API are able to achieve this acceleration simply by changing to the GPU-enabled platform without underlying code or application changes.

We will present Blazegraph DASL (pronounced 'dazzle') for graph and predictive analytics that combines the ease of Spark with the speed of GPUs. It has shown 1000X acceleration for large graphs when compared to in-memory processing with GraphX. DASL is a Scala-based language provides graphs and machine learning algorithms over linear algebra primitives. DASL programs are translated into task graphs that expose the available parallelism. The underlying Blazegraph DASL runtime integrates closely with Apache Spark. It provides the ability to write and execute DASL programs in Apache Spark and delivers a distributed, scalable architecture for machine learning and graph algorithms on GPUs and GPU clusters within the Spark environment.

Brad Bebee, Chief Executive Officer, Blazegraph

Brad is the CEO of Blazegraph leading efforts to deliver graphs at scale with Blazegraph products. An expert in graphs and large-scale analytics, he has a diverse background in software developments, telecommunications, and information retrieval.

Swag giveaway + food/drinks at 6:30pm
Power-Networking at 6:35pm 
Presentation starts at 6:40pm

Did you know that Techie Youth is the ONE-AND-ONLY organization providing career-opportunities to severely-at-risk foster-youth in New York?

Techie Youth is a 501c3 not-for-profit charity of NYC that provides technology-education, followed by assistance beginning an IT-career, to at-risk youth in NYC & Long Island who are in foster-care and classified as being severely-at-risk of becoming homeless and/or incarcerated in the next 18-24 months.

These kids need YOU, they have nobody else.
Please help them. Learn about Nadine, a student of Techie Youth: http://www.TechieYouth.org/hope

Join or login to comment.

  • Eric David B.

    Video of this event has been posted to http://www.DatabaseMonth.com

    2 · April 28, 2016

  • Warren P.

    Can we get a copy of the slides? Would be helpful in explaining to co-workers the value proposition. Thanks

    April 28, 2016

  • peter m

    Bitcoin mining with Radeon GPU's and solving graph query problems with NVidia GPU's? I had to go home and play a game to chase the dustbunnies out of my Radeon 5700 series graphics adapter. Just kidding. Fascinating talk by Brad that prompted me to do more in-depth research.

    April 20, 2016

  • A former member
    A former member

    Unfortunately I was not able to make it, will the slides be posted?

    1 · April 20, 2016

  • dino v.

    will the slides or presentation be posted?

    April 20, 2016

  • Drew W.

    Moderator needed to intervene when questioner starts a conversation with speaker.

    1 · April 19, 2016

    • Eric David B.

      I've done that in the past with other speakers, but tonight Brad seemed to have a good control over the situation, so it did not seem necessary - plus the "conversation"­ that you refer to was directly-relevant to the topic. I would have stepped in if it was tangential, disrespectful or disturbing; but I did not feel it was any of those.

      1 · April 20, 2016

  • Jimmy S.

    This is a great meetup. Really engaging people, great topics, and memorable awkward moments.

    2 · April 20, 2016

  • Joseph D.

    It wad really grest to see how far GPUs have come and that they have a bright future.

    1 · April 19, 2016

Our Sponsors

People in this
Meetup are also in:

Sign up

Meetup members, Log in

By clicking "Sign up" or "Sign up using Facebook", you confirm that you accept our Terms of Service & Privacy Policy