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Realtime Geospatial Analytics with GPUs, RAPIDS, and Apache Arrow Josh Patterson

September 12, 2019

Prior to RAPIDS, geospatial analytics, especially networking analytics for routing, required large CPU clusters to process. Even with 100s of machines, it would take hours if not days to get answers. With RAPIDS, and Apache 2.0 open source project built on Apache Arrow, graph analytics, clustering, and many other geospatial workflows can be completed end to end in seconds. Learn how to load data (CSV, Parquet, or ORC) directly into GPU memory with cuIO, process it with Dask-cuDF, and analyze it with cuML and cuGraph in seconds, all on a single node. Finally, learn how RAPIDS is scaling to multiple GPU nodes to solve the largest of geospatial challenges.

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