Cases2 cases

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1. IL-0476 PCIe downgrade on one machine slowed a 128-machine V100 training job for 40 minutes through a PFC surge

   ByteDance2025

   Symptoms

   A distributed training task on 128 machines in ByteDance's production environment slowed down severely for 40 minutes but kept running, holding thousands of V100 GPUs at reduced speed. The alerting in place notified engineers only when a task stopped completely, so the slowdown itself raised no alert.

   Throughput degradation

   Trigger

   The PCIe link of one machine degraded from 6.4Gbps to 4Gbps during the training task.

   Root cause

   Hardware failure

   Component

   PCIe linkInfiniBand fabric

   Contributing factor

   No alert on limit

   Detection

   No alert fired because alerts came only when a task stopped. Engineers from several teams found the faulty machine by manual diagnosis, which took 40 minutes.

   Action items

   • Detect faulty machines automatically during training by comparing each machine's per-second monitoring metrics with the other machines (Minder)

   Lessons

   Some faults slow a task without stopping it, and alerting that waits for a halted task misses them. Logs alone are incomplete because they do not contain monitoring metrics such as PFC packet rates, and no single metric reveals every fault type, so ByteDance compares machines with each other on several metrics and treats a difference that lasts for minutes as a fault.

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2. IL-0238 Xid 74 NVLink errors led the GPU faults and InfiniBand flash cuts failed tasks on DeepSeek's 10,000-GPU A100 cluster

   DeepSeek2024

   Symptoms

   On DeepSeek's Fire-Flyer 2 training cluster of 10,000 PCIe A100 GPUs, Xid 74 NVLink errors, which occur mainly on the NVLink Bridge between pairs of GPUs, were the most common GPU Xid error and occurred several orders of magnitude more often than other hardware faults. InfiniBand link flash cuts disrupted application communication and sometimes failed training tasks, and computational and GPU memory errors that ECC did not detect caused gradnorm spikes, loss explosions and even non-convergence of models.

   GPU unavailableLink flappingTraining job failureTraining divergence or loss spike

   Root cause

   Hardware failure

   Component

   GPU hardware and memoryInfiniBand fabric

   Contributing factor

   –

   Detection

   Xid errors were read from the NVIDIA driver's messages in the kernel or event log. A validator run weekly by the automatic operations system tested every node, and diagnosis tools such as hostping were integrated into the platform.

   Remediation

   • Reset the GPU to clear most GPU memory ECC errors, relying on A100 row remapping
   • Reset the GPU or rebooted the node after uncorrectable GPU errors
   • Ran a fieldiag test after Xid 119 and sent most such GPUs for RMA
   • Removed nodes that failed the weekly validator from the scheduling platform
   • Resumed interrupted training from checkpoints saved about every 5 minutes

   Lessons

   The best way to keep devices stable is to find problems before they happen, which is why the validator runs weekly. GPU ECC faults far outnumber CPU ones and need to be handled quickly so that performance and accuracy are not affected. Software-looking Xid errors such as illegal memory access may come from corrupted memory, so hardware faults should be considered once software bugs are ruled out. Whether to install NVLink should depend on actual need because of its drawbacks.

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