PaSca: A Scalable Graph Neural Architecture Search System
This article introduces PaSca, a scalable graph neural architecture search framework based on the SGAP paradigm, detailing its problem motivation, methodological innovations, extensive experiments on scalability and prediction performance, and summarizing its open‑source release and impact on large‑scale graph learning.