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FailBench: Evaluating Fault Tolerance Across Distributed Training Architectures
Distributed deep learning relies on data, pipeline, tensor, and hybrid parallelism, yet fault-tolerance mechanisms are typically evaluated only on the architecture for which they were designed. This leaves practitioners with little guidance when choosing mechanisms across architectures. FailBench pr
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