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Bay Area Meetup: GPU-Accelerated Analytics


Wednesday, January 25, 2017 from 6:00 PM to 8:15 PM (PST)

Bay Area Meetup: GPU-Accelerated Analytics

Ticket Information

Type End Quantity
Kinetica/NVIDIA Meetup 3d 4h 47m Free  

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Event Details

Join us to learn "How GPU Computing Is Revolutionizing Real-Time Analytics."  Plenty of free food and drinks too!

Kinetica and NVIDIA have partnered together to provide enterprises the fastest and most scalable GPU-accelerated, in-memory database solution for today’s streaming datasets and IoT use cases as well as for fast high-speed data ingest and real-time data analytics. 

Come hear how GPU computing has enabled new applications in financial services, retail, energy, telco and healthcare to conquer supply chain, logistics, fraud detection, regulatory compliance, customer 360 and a wide range of other business challenges.

  • GPUs have evolved from being primarily a consumer-gaming focused component to having new business applications for real-time data analytics.
  • Brute-force compute power of GPUs enables high performance analytics without the need for extensive tuning, indexing, and partitioning.
  • You can leverage GPU computing to create significant improvements for visualization of geospatial and temporal datasets.


John Barco, NVIDIA 

John Barco, Sr Director Deep Learning and Analytics at NVIDIA, has 20+ years product management and marketing management experience in a variety of enterprise, infrastructure and security technologies including SGI and Sun. John led product management teams with strong capacity to quickly define and build product, strategy and processes for high growth companies.

Charlie Boyle, NVIDIA

Charlie Boyle, Sr Director Product Marketing at NVIDIA, leads the product marketing efforts to drive the world wide adoption of NVIDIA’s DGX-1 system. Charlie brings a wealth of knowledge in the IT and service provider industry, having run marketing, engineering and data center operations for some of the world's largest telcos and service providers.

Chris Prendergast, Kinetica 

Chris currently serves as the Managing Director of Global Business Development and Alliances at Kinetica. Prior to joining Kinetica, Chris led a team of specialists evangelizing new use cases to help SAP customers leverage HANA for big data analytics. Chris was an early employee of both Cloudera and Hortonworks and has over 10 years of experience working with open source technology. For the better part of the last decade, Chris has been bringing organizations together to solve customer challenges in the US and abroad. This work spans cloud, on premise, BI, platforms and applications.  

Mark Brooks, Kinetica

Mark is Principal Systems Engineer at Kinetica, with more than twenty years of experience designing and developing distributed systems. At Kinetica, Mark is championing the role of GPUs in accelerating large-scale, in-memory analytics. Previously, Mark spent four years at Cloudera implementing Hadoop-based solutions in a range of verticals including Health Care, Telco and Financial Services. 


If driving, please enter parking lot off Scott Blvd. and park near building E as indicated on the map below.

Parking Map for Building E Marco Polo


Q. Are there ID requirements or an age limit to enter the event?

A. Identification and will be required by security at check-in. You must be 21 or older to attend.

Q. What are my transport/parking options getting to the event?

A. Ample parking is available in front of Building E off Scott Blvd.

Q. Where can I contact the organizer with any questions?

A. Please contact

Q.Is my registration/ticket transferrable?

A. Your registration is NOT transferable

Q. Do I have to bring my printed ticket to the event?

A. No. Pre-printed registration badges will be provided at check-in.

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Have questions about Bay Area Meetup: GPU-Accelerated Analytics? Contact Kinetica

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When & Where

NVIDIA Building E
2770 Scott Boulevard
Suite 3440
Santa Clara, CA 95050

Wednesday, January 25, 2017 from 6:00 PM to 8:15 PM (PST)

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Bay Area Meetup: GPU-Accelerated Analytics
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