Using GPU-acceleration to Interact with Open Street Map at Planet-Scale
Who is this presentation for?Data engineers, data architects, developers
We’ll explore the explosive growth in quantity of geospatial data, and how this is fueling the need to more frequently join geospatial data with traditional data. We’ll explain how those new scale requirements demand a massive improvement in speed, and how GPUs can be used to accelerate the querying of geospatial data using an open source in-GPU-memory SQL database. Finally, we will demonstrate interactive analysis of the entire, global Open Street Map dataset as an example of what is now possible.
Prerequisite knowledgeThis is a technical talk for suited for Big Data Architects, Geospatial Analysts, Big Data Analysts, and Data Scientists. They should have basic knowledge of: - Python - Basic ML
What you'll learn
Aaron is the VP of Community at OmniSci, responsible for OmniSci’s developer, user and open source communities. He comes to OmniSci with more than two decades of previous success building ecosystems around some of software’s most familiar platforms. Most recently he ran the global community for Mesosphere, including leading the launch and growth of DC/OS as an open source project. Prior to that he led the Java Community Process at Sun Microsystems, and ecosystem programs at SAP. Aaron has also served as the founding CEO of two startups in the entertainment space. Aaron has an MS in Computer Science and BS in Computer Engineering from Case Western Reserve University.
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