GPU-Accelerated Data Analytics in Python
Explore GPU-accelerated data analytics in Python through this comprehensive workshop from PyCon US. Learn about RAPIDS, an open-source library suite that enables data scientists to leverage GPU acceleration for ETL, machine learning, and graph analytics workloads using familiar Python APIs. Discover how to speed up compute times and increase model iteration without requiring specialized GPGPU programming knowledge. Dive into component libraries like cuDF, cuML, cuGraph, cuSignal, cuSpatial, and the Cyber Log Accelerator. Gain insights into data processing evolution, real-world benefits of GPU acceleration, and integration with the broader open-source GPU data science ecosystem. Suitable for those with basic data science knowledge, no prior GPU programming experience required.