Bytedance Deep Learning: Batch Flow Integrated Training Practice

Explore the evolution and practical implementation of ByteDance's batch flow integrated machine learning training framework in this 27-minute conference talk. Dive into the architecture, scheduling mechanisms, and innovative approaches that enable ByteDance to handle massive-scale AI model training across various business applications. Learn about the integration of Apache Iceberg, HDFS, and Kafka for efficient batch and streaming data processing. Discover how the framework supports flexible scheduling, multi-stage multi-source data orchestration, and heterogeneous elastic training. Gain insights into the challenges faced and solutions developed for global shuffle of streaming samples, full link Native implementation, and training data visualization. Understand the benefits of the new scheduling architecture, including improved resource utilization and unified resource management. Examine the Primus open-source project and its integration with Spark for enhanced pre-processing capabilities in training workflows.