SpaceX has almost finished writing V1.0 of an in-house AI training stack in C (2 minute read)

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Summary

SpaceX is finalizing a custom AI training stack written in C, utilizing pipeline parallelism and 220k GB300 GPUs to achieve over an order of magnitude speed improvement, with plans to develop an inference stack for reinforcement learning.

SpaceX's in-house AI training stack makes heavy use of pipeline parallelism by exact-mapping to 220k GB300s with 800G NICs, getting as close to bare metal as possible. The potential speed improvement is over an order of magnitude. SpaceX's next goal is to write the inference stack in C for simultaneous high-speed RL across a large block of GB300s.
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