Workshop on Graphs, Architectures, Programming, and Learning

About this Conference

A workshop focusing on the intersection of graph analytics, machine learning, and computational architectures. The event explores how graph methods and machine learning techniques can be integrated and optimized for large-scale data analysis across various computational platforms.

Call for Papers

The workshop seeks papers on graph analytics, machine learning methods, and their computational implementations. Topics include performance analysis of mixed data analytics workflows, graph learning acceleration, programming models, graph frameworks, hardware platforms for graph processing, and application domains. Both regular papers and short (up to four pages) work-in-progress papers are encouraged.

Important Dates

• Full Paper Submission February 1, 2026
• Notification February 28, 2026
• Conference dates 25 May 2026