>The number traces to Meta’s Llama 3 technical report, which documented 419 unforeseen disruptions across 16,384 H100s over 54 days of training, of which 148 were GPU failures and 72 were HBM3 memory failures.
From an annualized number on the llama 3 training report. would be interesting to see if we have a better idea given that we're already on rubin.
It depends entirely on the time-to-failure distribution though whether used cards are a good deal or not. Often this kind of hardware has a bathtub shaped hazard rate, actually getting burned in cards may mean you get the weeded out solid specimens, and forgo the lemons.
>The number traces to Meta’s Llama 3 technical report, which documented 419 unforeseen disruptions across 16,384 H100s over 54 days of training, of which 148 were GPU failures and 72 were HBM3 memory failures.
From an annualized number on the llama 3 training report. would be interesting to see if we have a better idea given that we're already on rubin.
A 9% (static) failure rate, implies an average lifespan of 11 years...
With a median lifespan of 7.35 years, although I doubt that 9% per year remains constant as the number of years increases.
Most hardware has an exponential (memoryless) failure distribution in practice. The bathtub curve is a myth.
It depends entirely on the time-to-failure distribution though whether used cards are a good deal or not. Often this kind of hardware has a bathtub shaped hazard rate, actually getting burned in cards may mean you get the weeded out solid specimens, and forgo the lemons.