ByteDance cooperated with Peking University and published a paper on the MegaScale large language model training and production system on arXiv. The MegaScale system leverages more than 10,000 GPUs to build a single cluster and achieves a model FLOP utilization of up to 55.2%, which is a significant achievement in the field of large language model training. The system also integrates advanced diagnostic tools, which can effectively monitor system components and events, quickly locate and solve problems, thereby ensuring system stability and efficiency.
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Bytedance and a research team from Peking University published a paper on arXiv, introducing their production system MegaScale for training large language models. MegaScale built a single cluster with more than 10,000 GPUs and achieved a model FLOP utilization of 55.2%. The system also includes a suite of diagnostic tools to monitor system components and events, identify root causes, and enable fault tolerance and mitigation of lag issues.
The success of the MegaScale system shows that ByteDance and Peking University have made significant progress in building an efficient and reliable large-scale language model training system, which provides important technical support for the development and application of large language models in the future. Its high FLOP utilization and powerful diagnostic tools provide a strong guarantee for improving training efficiency and model performance. In the future, we look forward to seeing the application and development of the MegaScale system in more fields.