Why Fault Tolerance Is Non-Negotiable at Scale
Reliability math is unforgiving at scale. If a single GPU has a tiny chance of failing on any given day, a cluster of thousands of them will see failures routinely, often more than once per run.
If a single failure kills the job, you will never finish a multi-week training run. You will instead spend your time restarting from scratch and watching the same kinds of failures recur.
The only workable answer is to make failure a normal, handled event. Continuous checkpointing means a failed node costs you minutes, not days. Automatic recovery means no engineer has to be paged at three in the morning.
SparkMind is built so that hardware failure is expected and absorbed. The run continues, the engineers sleep, and the schedule holds, because at this scale, designing for perfect hardware is designing to fail.
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