OmniSci and RAPIDS: End-to-End Open Source Data Science Workflow

Learn how the OmniSci GPU-Accelerated SQL engine fits into the overall RAPIDS partner ecosystem for open source GPU analytics. Using open data, we'll show how to ingest data that's from both streaming and standing sources, perform descriptive statistics and feature engineering using SQL and cuDF, and return the results as a GPU DataFrame. We'll also describe how data science workflow can be accomplished using tools from the RAPIDS ecosystem, all without the data ever leaving the GPU.

Transcript

1. OmniSci and RAPIDS: End-to-End Open Source Data Science Workflow NVIDIA GTC | San Jose | March 20, 2019 slides: https://speakerdeck.com/omnisci
2. © OmniSci 2018 Aaron Williams VP, Global Community @_arw_ aaron@omnisci.com /in/aaronwilliams/ /williamsaaron Venkat Krishnamurthy VP, Product @niviksha venkat.krishnamurthy@omnisci.com /in/vkcmu/
3. © OmniSci 2018 3 Fast Hardware + Fast Software 3-Tier Memory Caching Query Compilation In-Situ Rendering
4. © OmniSci 2018 4 * open source for single node github.com/omnisci/mapd-core
5. © OmniSci 2018 Camp Fire Demo
6. © OmniSci 2018 WiFi Access Points Demo
7. Unifying GPU-accelerated Analytics and Data Science ✔ With OmniSci’s Arrow-capable python API (and via Ibis), OmniSci can output results direct to cudf, and integrate with RAPIDS via Python (requires pymapd 0.7.0). ✔ OmniSci’s JupyterLab integration (and support for Altair and Ibis) allows for connecting, querying, in-notebook visualization and extraction of data OmniSci User Defined Functions (coming 2019) will allow deeper, lower-level integration with RAPIDs libraries Altair: https://altair-viz.github.io/ Ibis: http://ibis-project.org/ OmniSci query result set in-GPU to RAPIDS GPU-resident outputs from RAPIDS ML algorithms
8. © OmniSci 2018 Aaron Williams VP, Global Community @_arw_ aaron@omnisci.com /in/aaronwilliams/ /williamsaaron Venkat Krishnamurthy VP, Product @niviksha venkat.krishnamurthy@omnisci.com /in/vkcmu/ slides: https://speakerdeck.com/omnisci Thank you!