Description
本期播客深入探讨了Comet,这是一种为混合专家模型(MoE)设计的优化系统,通过精细的计算与通信重叠,显著提高了MoE模型的执行效率。我们将讨论Comet的两个关键设计:基于共享张量的依赖解析和自适应工作负载分配,以及它们如何克服现有MoE系统中的挑战。我们还将分享Comet在实际生产环境中的部署情况,以及它如何为大规模GPU集群节省数百万GPU小时。
Audio
Featured in this Episode
No persons identified in this episode.
Transcription
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
0
upvotes
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
SpaceX Said to Pursue 2026 IPO
10 Dec 2025
Bloomberg Tech
Don’t Call It a Comeback
10 Dec 2025
Motley Fool Money
Japan Claims AGI, Pentagon Adopts Gemini, and MIT Designs New Medicines
10 Dec 2025
The Daily AI Show
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
What it will take for AI to scale (energy, compute, talent)
10 Dec 2025
Azeem Azhar's Exponential View
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast