The Mixture of Experts (MoE) architecture is one of the mainstream technologies in current large model training. By dividing the model into multiple "expert" modules and dynamically selecting the most appropriate module for computation, it achieves higher flexibility and efficiency. However, the MoE architecture faces significant communication overhead in distributed training, especially in cross-device communication, where communication time can account for up to 40% of the total time. This severely limits training efficiency and cost control.

Core Breakthroughs of COMET Technology

To address this bottleneck, ByteDance's DouBao Large Model team announced the open-source release of a key optimization technology called COMET on March 10, 2025. COMET has achieved significant performance improvements and cost reductions through the following innovations:

1. Compute-Communication Overlapping Technology: COMET introduces a fine-grained compute-communication overlapping mechanism. By sharing tensor dependency parsing and adaptive load allocation, it solves the granularity mismatch problem between computation and communication in traditional methods. This technology can achieve a 1.96x speedup on a single MoE layer, with an average end-to-end efficiency improvement of 1.71x.

2. Plugin Integration and Compatibility: COMET is designed to be simple and universal. It can be integrated into existing MoE training frameworks as a plugin without invasive modifications to the training framework. Additionally, it supports the vast majority of mainstream large models in the industry and can be used in conjunction with DeepSeek's DualPipe solution to further reduce training costs.

Application Effects and Significance

The COMET technology has been applied in ByteDance's 10,000-card cluster training, saving millions of GPU hours of training compute power. This achievement not only validates the efficiency and stability of COMET but also provides a more economical and efficient solution for large-scale model training. By open-sourcing this technology, ByteDance hopes to promote collective progress in model training efficiency across the AI community.

Moreover, COMET has been selected for the MLSys 2025, the top global machine learning systems conference, with a high score of 5/5/5/4. It is considered to have "great application potential in large-scale production environments." The introduction of this technology not only solidifies ByteDance's leading position in the AI field but also injects new vitality into the development of the entire industry.

Future Outlook

The open-source release of COMET technology provides valuable resources and references for global AI developers and researchers. It lowers the technical barriers, promotes the popularization of technological innovation and application, and offers a new direction for the development of future large model training technologies. As more developers conduct in-depth research and application of COMET technology, it is expected to demonstrate greater potential and value in more fields.

Through the successful open-source release of COMET technology, ByteDance has once again proven its technical strength and open collaboration attitude in the AI field. This breakthrough not only brings new opportunities for large model training but also provides a more solid foundation for the popularization and application of artificial intelligence technology.

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