GTC 2020: RAPIDS: GPU-Accelerated Data Analytics & Machine Learning

GTC 2020 D2S29
Presenters: Tech Demo Team,NVIDIA
The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA CUDA primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.

This demonstration uses RAPIDS, and OmniSci’s GPU-accelerated analytics platform to quickly visualize and run queries on the 1.1 billion New York City taxi ride dataset.

Watch this session
Join in the conversation below.

Could we download the Jupyter Notebook?