The Ninth IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Analytics and Big Models (BPOD 2026)

The Ninth IEEE BPOD 2026 workshop provides a premier forum for researchers and practitioners to address the evolving challenges of benchmarking, performance tuning, and optimization in the era of Big Data and large-scale AI models. This edition focuses on the intersection of high-performance computing, distributed systems, and modern machine learning architectures to bridge the gap between theoretical efficiency and practical deployment. Participants will engage in critical discussions aimed at establishing robust standards and innovative methodologies for evaluating the next generation of data-intensive analytical platforms.

We invite original research contributions, case studies, and position papers that explore novel benchmarking frameworks, performance characterization, and optimization strategies for big data analytics and large models. Submissions should emphasize empirical results, architectural insights, or scalable solutions that address latency, throughput, and resource efficiency in complex distributed environments.