英伟达，遥遥领先

Core Insights - The latest MLPerf benchmark results indicate that Nvidia's GPUs continue to dominate the market, particularly in the pre-training of the Llama 3.1 403B large language model, despite AMD's recent advancements [1][2][3] - AMD's Instinct MI325X GPU has shown performance comparable to Nvidia's H200 in popular LLM fine-tuning benchmarks, marking a significant improvement over its predecessor [3][6] - The MLPerf competition includes six benchmarks targeting various machine learning tasks, emphasizing the industry's trend towards larger models and more resource-intensive pre-training processes [1][2] Benchmark Performance - The pre-training task is the most resource-intensive, with the latest iteration using Meta's Llama 3.1 403B, which is over twice the size of GPT-3 and utilizes a four times larger context window [2] - Nvidia's Blackwell GPU achieved the fastest training times across all six benchmarks, with the first large-scale deployment expected to enhance performance further [2][3] - In the LLM fine-tuning benchmark, Nvidia submitted a system with 512 B200 processors, highlighting the importance of efficient GPU interconnectivity for scaling performance [6][9] GPU Utilization and Efficiency - The latest submissions for the pre-training benchmark utilized between 512 and 8,192 GPUs, with performance scaling approaching linearity, achieving 90% of ideal performance [9] - Despite the increased requirements for pre-training benchmarks, the maximum GPU submissions have decreased from over 10,000 in previous rounds, attributed to improvements in GPU technology and interconnect efficiency [12] - Companies are exploring integration of multiple AI accelerators on a single large wafer to minimize network-related losses, as demonstrated by Cerebras [12] Power Consumption - MLPerf also includes power consumption tests, with Lenovo being the only company to submit results this round, indicating a need for more submissions in future tests [13] - The power consumption for fine-tuning LLMs on two Blackwell GPUs was measured at 6.11 gigajoules, equivalent to the energy required for heating a small house in winter [13]