nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted

nvidia-peermem could not create another peer-direct mapping because the GPU BAR1 aperture has no usable space for it. Stale peer mappings, an undersized BAR1 window, or an unsupported platform layout can produce the same rejection. This entry explains how to confirm the cause, apply the fix, and separate it from adjacent infiniband failures.

The literal signature is "nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted". It is a communication failure associated with InfiniBand, RoCE, and RDMA queue pairs. The line identifies the failing operation or subsystem, while the surrounding evidence decides whether it is the initiating fault or a downstream symptom.

nvidia-peermem could not create another peer-direct mapping because the GPU BAR1 aperture has no usable space for it. Stale peer mappings, an undersized BAR1 window, or an unsupported platform layout can produce the same rejection. The failure becomes visible at this call site because the operation first requires the missing resource, valid state, healthy peer, or correct result. Earlier log lines and a known-good control carry more causal value than the final wrapper exception.

• The workload stops or loses forward progress after emitting "nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted".
• A retry on the same configuration reproduces the failure because the causal state has not changed.
• The outer framework exception can hide the rank, node, allocation, or dependency that failed first.
• Increasing timeouts or reducing workload size can suppress the symptom without correcting the cause.

• InfiniBand, RoCE, and RDMA queue pairs
• production-shaped multi-accelerator workloads
• containerized and bare-metal deployments of the same stack

Apply the following checklist to a small reproduction: each box below is a positive signal that you are looking at this exact failure rather than a sibling in the same taxonomy.

• ✓Find the first occurrence of "nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted" and preserve at least 100 lines before it.
• ✓Identify which rank, node, device, or process emitted the first related warning.
• ✓compare the configured BAR1 size and current usage on a failing node with a healthy peer. Confirm Resizable BAR and Above 4G Decoding are enabled where the platform requires them.
• ✓Repeat the same input after the targeted change and require the signature to disappear.
• ✓Resume from job start after a clean peer-memory mapping succeeds only after the control passes.

nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted

Timestamps and exact values vary across runs, but the pattern. An info-level start, an early WARN, an ERROR carrying the symptom. Is the actual fingerprint you should alert on. The Denpex platform flags this combination automatically.

stop the affected job, confirm no stale RDMA or CUDA processes retain the GPU, and inspect BAR1 usage with nvidia-smi -q before retrying. This changes the condition in the causal diagnosis instead of hiding the outer exception. The repeated control proves ownership before recovery from job start after a clean peer-memory mapping succeeds.

# Preserve evidence before restarting
NCCL_DEBUG=INFO NCCL_DEBUG_SUBSYS=INIT,NET,COLL torchrun train.py
ibstat
ethtool -S <interface>

# Find the exact signature in the complete log
rg -n -F -- "nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted" <log-file>

Adapt the snippet to your framework. The same pattern holds for PyTorch Lightning, Hugging Face Trainer, DeepSpeed, Megatron-LM, and vLLM training wrappers. Where the wrapper exposes a config flag (for examplelr_scheduler_type in Trainer), prefer the flag over the imperative API to keep the schedule declarative and reproducible.

Select the traceback or open the failed terminal, then run Denpex locally to see the initiating rank, collateral failures, exact fix, and verification command without uploading the log.

• nvidia-peermem could not create another peer-direct mapping because the GPU BAR1 aperture has no usable space for it. Stale peer mappings, an undersized BAR1 window, or an unsupported platform layout can produce the same rejection.
• The decisive evidence is the first log line that precedes "nvidia-peermem kernel rejected peer-direct DMA mapping BAR1 aperture exhausted" and differs from a healthy run.
• A nearby failure remains a competing hypothesis until a control separates configuration, capacity, transport, and hardware causes.