[TriLUG-announce] Reminder: Meeting: March 8, Accelerating AI with GPUs

[Aaron Schrab]

Topic:     Accelerating AI with GPUs
Presenter: Nvidia
When:      Thursday, 8 March 2018 - 6:45pm to 9:00pm
Where:     NCSU College of Textiles, 1020 Main Campus Dr., Room 2207
Parking:   Underground parking deck immediately adjacent to the building
            (see map).

Please note that since we're back on the NCSU campus, we need to start
the pizza early so we don't have any food or drink in the meeting room.
Munchies start at 6:45!

Links:
     Map:    https://goo.gl/SNVQgZ
     Page:   https://trilug.org/2018-03-08/accelerating-ai-with-gpus
     Meetup: https://www.meetup.com/trilug/events/248177110/

Summary:
Data scientists in both industry and academia have been using GPUs for AI and
machine learning to make groundbreaking improvements across a variety of
applications including image classification, video analytics, speech recognition
and natural language processing. In particular, Deep Learning – the use of
sophisticated, multi-level "deep" neural networks to create systems that can
perform feature detection from massive amounts of unlabeled training data – is
an area that has been seeing significant investment and research. Although AI
has been around for decades, two relatively recent trends have sparked
widespread use of Deep Learning within AI: the availability of massive amounts
of training data, and powerful and efficient parallel computing provided by GPU
computing. Early adopters of GPU accelerators for machine learning include many
of the largest web and social media companies, along with top tier research
institutions in data science and machine learning. With thousands of
computational cores and 10-100x application throughput compared to CPUs alone,
GPUs have become the processor of choice for processing big data for data
scientists.

Bio:
David Williams is a Solutions Architect for NVIDIA, working with
Enterprise and Startup companies over the Southeastern section of the
United States. Born and raised in Houston, Texas, David left the South
for the freezing shores of Lake Michigan to attend Northwestern
University for his Bachelor's and Master's degrees in Computer
Engineering. Making a much needed return to warmer climates, David moved
to Chapel Hill after graduation and joined NVIDIA. Solution Architects
serve as customer engineering resources, investigating questions and
evaluating proof of concepts for companies interested in NVIDIA
technology. As NVIDIA has become the leading artificial intelligence
company, the technical challenges faced in this new market cover topics
of GPU hardware, system software, data engineering, datacenter
architecture, deep learning frameworks, and neural network data science.
David is excited to discuss the key drivers and introductory concepts of
the world of artificial intelligence and deep learning.

Sponsor: NVIDIA