GTC Silicon Valley-2019: BlazingSQL on RAPIDS: SQL for Apache Arrow in GPU Memory. Connect Data Lakes to RAPIDS
GTC Silicon Valley-2019 ID:S9798:BlazingSQL on RAPIDS: SQL for Apache Arrow in GPU Memory. Connect Data Lakes to RAPIDS
Felipe Aramburu(BlazingDB),Rodrigo Aramburu(BlazingDB),William Malpica(BlazingDB)
Learn about BlazingSQL, our new, free GPU SQL engine built on RAPIDS open-source software. We will show multiple demo workflows using BlazingSQL to connect data lakes to RAPIDS tools. We'll explain how we dramatically accelerated our engine and made it substantially more lightweight by integrating Apache Arrow into GPU memory and cuDF into RAPIDS. That made it easy to install and deploy BlazingSQL + RAPIDS in a matter of minutes. More importantly, we built a robust framework to help users bring data from data lakes into GPU-Accelerated workloads without having to ETL on CPU memory or separate GPU clusters. We'll discuss how that makes it possible to keep everything in the GPU while BlazingSQL manages the SQL ETL. RAPIDS can then take these results to continue machine learning, deep learning, and visualization workloads.