[Hardware Accelerated Databases] Richard Heyns (Brytlyt)

Event Date: Thursday November 1, 2018
Event Time: 12:00pm EDT
Location: CIC - 4th floor (ISTC Panther Hollow Room)
Speaker: Richard Heyns [INFO]

Title: Using GPU Databases To Build The Next Generation Of Artificial Intelligence

In this talk, we will cover how the implementation of GPU database management systems are different than CPU database systems and provide evidence that shows how much of the performance gains with these systems are achieved via just GPUs. We will also discuss how we are solving the problems of tomorrow – making AI smarter, faster and more intuitive with Brytlyt’s BrytMind by combining SQL with its GPU Manager and AI. We will also explore the different ways GPU Databases will impact the future of technology – whether its Artificial Intelligence on GPU or Task Orchestration and Analytics workbench tools. We will showcase some of our current capabilities from analytics workbench tool, SpotLyt to BrytMind – our GPU accelerated AI tool while also talking about how we became the fastest GPU database in the market as proven by independent benchmarking. We will also talk about things that the user needs to keep in mind before selecting a GPU accelerated database – low integration costs, ability to do fast JOINs, and more.

Part of Hardware Accelerated Database Lectures 2018 Seminar Series

Richard Heyns is CEO of Brytlyt. He is responsible for the initial and ongoing research in bringing processing database operations to General Processing on Graphics Processor Units. He has 15 years of experience working on large business intelligence, big data projects and software development. Brytlyt GPU Database and Analytics Platform is a fork of PostgreSQL that has a patent pending IP through which multibillion datasets can now be queried in seconds, at massively reduced cost. Brytlyt provides its users the ability to get astonishing performance, integration with existing systems, smooth scalability and yet a functionally rich and easy to use interface.