MangoBoost Establishes New Standard for Multi-Node LLM Training on AMD GPUs

South Korean startup MangoBoost has achieved a significant milestone in large-scale AI training by validating the efficiency of AMD Instinct MI300X GPUs through its MLPerf Training v5.0 submission. Using a 32-GPU setup across four nodes, MangoBoost fine-tuned the Llama2-70B-LoRA model in just 10.91 minutes, setting a benchmark for multi-node performance on AMD GPUs. The results showed near-linear scaling efficiency (95–100%), highlighting how enterprises can effectively scale LLM training without network bottlenecks or reliance on specific infrastructure. MangoBoost’s platform demonstrated compatibility with various model sizes, confirming its versatility for production use. Industry experts praised the results, emphasizing the critical role of a well-optimized software stack in leveraging modern AI technologies. CEO Jangwoo Kim emphasized that their achievement proves software-hardware co-optimization facilitates efficient and flexible LLM training, ready for enterprise applications.

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