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This observation would help verify a different incident: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. It does not directly establish the required result for the current case: A hop and port identity audit matches the approved diagram and each rail carries its expected workload during a test.

This observation would help verify a different incident: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. It does not directly establish the required result for the current case: A hop and port identity audit matches the approved diagram and each rail carries its expected workload during a test.

This observation would help verify a different incident: A host is declared healthy based on one GPU benchmark even though the node contains eight accelerators with a mix of memory capacities. It does not directly establish the required result for the current case: A hop and port identity audit matches the approved diagram and each rail carries its expected workload during a test.

This underlying cause is associated with another GPU platform incident: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. The observed case instead concerns: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This underlying cause is associated with another GPU platform incident: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. The observed case instead concerns: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This underlying cause is associated with another GPU platform incident: NCCL all-reduce performs well within a rack but slows dramatically when ranks span two racks connected by a single overburdened uplink. The observed case instead concerns: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This prevention control targets another operational risk: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. The currently reported mechanism remains: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This prevention control targets another operational risk: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. The currently reported mechanism remains: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This prevention control targets another operational risk: A cluster uses both Ethernet and InfiniBand interfaces, but NCCL chooses the slow management-facing interface for data transfer on one node group. The currently reported mechanism remains: A link-up state cannot prove that high-speed cables connect to the intended topology or isolated rail.

This option could be appropriate for a different NVIDIA infrastructure problem (4.5: Confirm cabling is correct): A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The present issue is more specifically caused by: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This option could be appropriate for a different NVIDIA infrastructure problem (4.5: Confirm cabling is correct): A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. The present issue is more specifically caused by: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This option could be appropriate for a different NVIDIA infrastructure problem (4.3: Perform single-node NCCL and verify NVLink Switch): An engineer benchmarks NCCL with only two GPUs on an eight-GPU HGX node, then assumes its result validates every NVSwitch interconnection. The present issue is more specifically caused by: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This observation would help verify a different incident: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. It does not directly establish the required result for the current case: Selected cables can be located at both ends without guesswork and a controlled disconnect affects only the recorded link.

This observation would help verify a different incident: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. It does not directly establish the required result for the current case: Selected cables can be located at both ends without guesswork and a controlled disconnect affects only the recorded link.

This observation would help verify a different incident: A GPU worker throttles under stress while facility cooling remains within specification, and operators blame the network because distributed iteration time increases. It does not directly establish the required result for the current case: Selected cables can be located at both ends without guesswork and a controlled disconnect affects only the recorded link.

This underlying cause is associated with another GPU platform incident: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. The observed case instead concerns: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This underlying cause is associated with another GPU platform incident: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The observed case instead concerns: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This underlying cause is associated with another GPU platform incident: A NeMo burn-in shows stable GPU utilization but training throughput varies widely because dataset sharding and storage clients are inconsistent across nodes. The observed case instead concerns: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This prevention control targets another operational risk: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The currently reported mechanism remains: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This prevention control targets another operational risk: A 400-Gbps breakout assembly is connected with reversed lane mapping so one logical child port terminates at the wrong peer while other child ports work. The currently reported mechanism remains: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This prevention control targets another operational risk: Operators increase NCCL stress parallelism until every node becomes thermally unstable, then misclassify the resulting throttling as an InfiniBand cabling fault. The currently reported mechanism remains: Duplicate or stale labels make high-density fabric troubleshooting unreliable despite correctly negotiated interfaces.

This option could be appropriate for a different NVIDIA infrastructure problem (4.5: Confirm cabling is correct): A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The present issue is more specifically caused by: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This option could be appropriate for a different NVIDIA infrastructure problem (4.5: Confirm cabling is correct): A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. The present issue is more specifically caused by: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This option could be appropriate for a different NVIDIA infrastructure problem (4.13: Perform NVIDIA NeMo burn-in): A NeMo language-model smoke test passes, but a longer training run repeatedly fails after checkpoint intervals because model artifacts cannot be written to shared storage. The present issue is more specifically caused by: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This observation would help verify a different incident: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. It does not directly establish the required result for the current case: Every expected child link resolves to its intended peer and a port-by-port test detects no unintended cross-connection.

This observation would help verify a different incident: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. It does not directly establish the required result for the current case: Every expected child link resolves to its intended peer and a port-by-port test detects no unintended cross-connection.

This observation would help verify a different incident: GPU nodes lose fabric connectivity after a switch firmware update, but the switch shows no errors because engineers did not check its running network OS version against approved settings. It does not directly establish the required result for the current case: Every expected child link resolves to its intended peer and a port-by-port test detects no unintended cross-connection.

This underlying cause is associated with another GPU platform incident: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. The observed case instead concerns: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This underlying cause is associated with another GPU platform incident: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The observed case instead concerns: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This underlying cause is associated with another GPU platform incident: One leaf switch reboots repeatedly under load after maintenance, while its peer leaf remains stable and has a different firmware revision. The observed case instead concerns: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This prevention control targets another operational risk: A technician lands two adjacent GPU host fibers on the wrong switch ports, and both links show up yet a multi-rail collective runs over one rail. The currently reported mechanism remains: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This prevention control targets another operational risk: A rack expansion replicates old patch labels, and engineers cannot tell which high-speed trunk belongs to each new GPU server during a fault. The currently reported mechanism remains: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.

This prevention control targets another operational risk: An LLM platform signs off infrastructure after HPL and NCCL pass, but the real NeMo run fails because the configured container cannot access the required tokenizer and approved model artifacts. The currently reported mechanism remains: Physical breakout assemblies can expose partial link success while individual logical lanes are miswired.