Autonomous recovery for distributed training jobs

Show HN: Autonomous recovery for distributed training jobs

Operating in show hn launch, Autonomous recovery for distributed training jobs operates.

Profile

Hi HN! We’re TensorPool. We help companies access and optimize large scale compute for training foundation models.The ProblemIt’s been almost a year since we’ve finished YC, and we’ve just crossed 100,000 multinode training GPU hours run on our platform.On those training runs, we’ve seen countless 3am job crashes because of issues like an Xid error from a flaky GPU or an S3 timeout that corrupted a checkpoint save. By the time you wake up and notice, you've lost 8+ hours of compute. You scramble to diagnose the issue, manually restart from the last checkpoint, and hope it doesn't happen again. Rinse and repeat.For training runs that take days to weeks, this constant babysitting is exhausting

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The company is listed at the Show HN launch stage of development.

Website: docs.tensorpool.dev/features/agent