Optimization at scale
Training a 7B parameter model on 1T tokens requires ~10²¹ FLOPs. At GPU efficiency of 30 50%, this means weeks of training on hundreds of accelerators. Optimization efficiency is not a nice to have — it is a cost multiplier.
Training a 7B parameter model on 1T tokens requires ~10²¹ FLOPs. At GPU efficiency of 30 50%, this means weeks of training on hundreds of accelerators. Optimization efficiency is not a nice to have — it is a cost multiplier.