The Gen1 Revelation: A Single Diagnostic Command That Exposed the Full Scope of Virtualization Overhead

The Message

In the midst of a deep investigation into cross-GPU communication bottlenecks in a Proxmox virtual machine running 8× NVIDIA RTX PRO 6000 Blackwell GPUs, the assistant issued a single, deceptively simple diagnostic command:

ssh 10.1.230.175 "nvidia-smi --query-gpu=index,pci.bus_id,pcie.link.gen.current,pcie.link.width.current --format=csv,noheader" 2>&1

The response was stark:

0, 00000000:01:00.0, 1, 16
1, 00000000:02:00.0, 1, 16
2, 00000000:03:00.0, 1, 16
3, 00000000:04:00.0, 1, 16
4, 00000000:05:00.0, 1, 16
5, 00000000:06:00.0, 1, 16
6, 00000000:07:00.0, 1, 16
7, 00000000:08:00.0, 1, 16

Every single GPU reports pcie.link.gen.current = 1 — PCIe Gen1 — despite a link width of 16 lanes. This single output, returned in message index 389, represents a pivotal moment in a much larger investigation. It is the quiet diagnostic that speaks volumes, revealing that the virtualization overhead is even more severe than previously understood.

Context: The Long Road to This Discovery

To understand why this simple nvidia-smi query matters, one must trace the investigation that led to it. The session began with the deployment of the GLM-5-NVFP4 model — a 744-billion-parameter mixture-of-experts language model — across 8 RTX PRO 6000 Blackwell GPUs. The initial deployment succeeded, but performance was far below expectations. The model achieved roughly 485 tokens per second at peak concurrency, well short of the 1,000+ tok/s target, and single-stream latency was abysmal at over 21 seconds per request.

The assistant correctly identified the root cause: the machine was running inside a Proxmox KVM virtual machine, and cross-GPU Peer-to-Peer (P2P) DMA was completely unsupported. Every GPU-to-GPU transfer had to bounce through host memory, incurring a latency floor of 13.7 microseconds for small transfers. For a model with 78 transformer layers, each requiring multiple all-reduce operations, this latency penalty accumulated catastrophically.

What followed was a deep, multi-layered investigation into the virtualization topology. The assistant traced the problem from the VM's chipset (i440FX, later migrated to Q35) through the host's IOMMU groups, the PCIe root complex topology, and even into the BIOS-level ACS (Access Control Services) settings. Each layer peeled back revealed another constraint: the GPUs were each attached to their own dedicated PCIe root complex on the ASUS ESC8000A-E13 motherboard, a design that maximizes per-GPU bandwidth but creates separate IOMMU domains that fundamentally prevent VFIO from granting direct P2P DMA access.

By message 388, the assistant had mapped out the full physical-to-virtual GPU correspondence, understood the NUMA topology mismatch, and was weighing approaches to mitigate the problem — custom QEMU arguments with PCIe expander buses, NCCL topology XML overrides, or software-level workarounds. Then came message 389.

Why This Message Was Written

The assistant issued this command for a specific and well-motivated reason. Throughout the P2P investigation, the focus had been on topology — which GPUs could talk to which others, through what paths, with what NUMA affinity. The nvidia-smi topo -m output had been examined repeatedly. But one critical parameter had not been checked: the actual negotiated PCIe link speed inside the VM.

The assistant's thinking, visible in the progression of messages leading up to this one, reveals a systematic diagnostic approach. After establishing that P2P DMA was impossible due to hardware topology, the assistant began considering alternative approaches to improve cross-GPU communication. But before committing to any particular mitigation strategy, it needed a complete picture of the VM's PCIe capabilities. The PCIe link generation and width are fundamental parameters that determine the maximum bandwidth available for any PCIe transaction — including the host-mediated transfers that were currently carrying all cross-GPU traffic.

The command was chosen with care. nvidia-smi's --query-gpu format allows precise selection of fields. The assistant queried index (for ordering), pci.bus_id (to confirm which GPU was which), pcie.link.gen.current (the negotiated PCIe generation), and pcie.link.width.current (the number of lanes). This combination would reveal both the theoretical maximum bandwidth (gen × width) and whether the VM was properly negotiating high-speed links with the physical GPUs.

The Discovery: Gen1 in a Gen5 World

The output was unambiguous: all eight GPUs reported 1, 16 — PCIe Gen1 ×16. This is a staggering finding. The RTX PRO 6000 Blackwell GPUs are PCIe Gen5-capable devices. The host machine's physical slots are Gen5 ×16. Earlier in the investigation, the assistant had confirmed at the host level that the GPUs were running at Gen5 ×16 with ASPM disabled. Yet inside the VM, the guest operating system saw only Gen1.

This means the virtualization layer was not just preventing P2P DMA — it was also capping the raw link speed at one-sixteenth of its potential. PCIe Gen1 ×16 provides approximately 4 GB/s per direction (3.94 GB/s in practice). PCIe Gen5 ×16 provides approximately 63 GB/s. The GPUs inside the VM were communicating with the outside world — including host memory, which was the intermediary for all cross-GPU transfers — at roughly 6% of the available hardware bandwidth.

The implications are profound. Even if P2P DMA could be somehow enabled, the Gen1 link speed would still severely limit direct GPU-to-GPU transfers. And for the host-mediated transfers that were currently the only available path, the Gen1 bottleneck meant that every cross-GPU communication was operating at a tiny fraction of its potential throughput.

Assumptions and Potential Mistakes

This message reveals an implicit assumption that had persisted through much of the earlier investigation: that the PCIe link speed inside the VM would match the host-level link speed. The assistant had checked host-level PCIe status earlier and confirmed Gen5 ×16 links. It had assumed, reasonably but incorrectly, that the VM would inherit this capability through the VFIO passthrough mechanism.

This assumption was understandable. VFIO passthrough typically preserves the PCIe configuration space of the physical device, and the guest OS should be able to negotiate the same link speed that the host negotiated. However, the virtual PCIe root port created by QEMU's Q35 chipset emulation may not support Gen5 negotiation, or the VFIO driver may not properly expose the link capabilities to the guest. The result is that the guest sees only Gen1, regardless of what the hardware is capable of.

Another implicit assumption was that the primary bottleneck was P2P latency rather than raw bandwidth. The assistant had noted earlier that PCIe links were "barely utilized" during inference and that the bottleneck appeared to be "per-layer latency from VM overhead on cross-GPU transfers, NOT raw bandwidth." The Gen1 discovery complicates this picture: if the link is running at Gen1, then even the bandwidth that is being utilized is capped at 4 GB/s. The low utilization might be a consequence of the latency bottleneck masking the bandwidth ceiling, or the bandwidth ceiling might be a contributing factor to the overall performance problem.

Input Knowledge Required

To fully understand this message, one needs knowledge of several domains:

PCIe architecture: The distinction between link generation (Gen1 through Gen5) and link width (×16, ×8, etc.) is fundamental. PCIe is a point-to-point serial bus where each "generation" doubles the per-lane data rate. Gen1 ×16 provides about 4 GB/s, Gen2 ×16 provides 8 GB/s, Gen3 ×16 provides 16 GB/s, Gen4 ×16 provides 32 GB/s, and Gen5 ×16 provides 64 GB/s. The nvidia-smi fields pcie.link.gen.current and pcie.link.width.current report the actual negotiated values, which may differ from the device's or slot's capabilities.

Virtualization and VFIO: Understanding that PCIe devices passed through to a VM via VFIO still need to negotiate link speeds with the virtual PCIe root port. The QEMU Q35 chipset emulation creates virtual PCIe root ports that may not support the same link speeds as the physical hardware.

NVIDIA's nvidia-smi tool: Knowledge of the --query-gpu format and the specific fields available for querying PCIe status. The tool can report both current and maximum link generation and width.

The broader investigation context: Understanding that this message is part of a systematic effort to diagnose and mitigate virtualization overhead for large-scale GPU inference. The assistant had already established that P2P DMA was unsupported, mapped the physical-to-virtual GPU topology, and was evaluating mitigation strategies.

Output Knowledge Created

This message created several critical pieces of knowledge:

  1. Quantified virtualization overhead: The VM's PCIe link speed is Gen1 ×16, not Gen5 ×16 as the hardware supports. This means the virtualization layer imposes a 16× bandwidth penalty on all PCIe transactions, not just a latency penalty on cross-GPU transfers.
  2. Refined bottleneck diagnosis: The performance problem has at least two dimensions — the P2P latency issue (each small transfer incurs ~13.7 µs overhead) and the raw bandwidth ceiling (all PCIe traffic capped at ~4 GB/s). These interact: the latency penalty dominates for small transfers, but the bandwidth ceiling would become the primary constraint for large transfers.
  3. Mitigation strategy implications: Any approach that relies on host-mediated transfers (the only available path without P2P) must contend with the Gen1 bandwidth ceiling. This makes software-based workarounds (like NCCL topology XML overrides) less promising, since they can't fix the fundamental link speed limitation. It also suggests that reducing cross-GPU communication volume (e.g., through expert parallelism or pipeline parallelism) may be more effective than trying to optimize the communication path.
  4. New diagnostic direction: The Gen1 finding opens a new line of investigation. Can the VM be configured to negotiate a higher link speed? Does the Q35 chipset emulation support Gen3 or higher? Would switching to a different virtual PCIe topology (e.g., using pxb-pcie expander buses) allow higher link speeds? These questions were not on the table before this message.

The Thinking Process

The assistant's reasoning, visible in the sequence of messages leading to this one, follows a methodical diagnostic pattern. The investigation had been progressing through layers of abstraction:

  1. Application layer: Model deployment works, but performance is poor.
  2. Runtime layer: NCCL all-reduce is slow, cross-GPU transfers are the bottleneck.
  3. Virtualization layer: P2P DMA is unsupported (NS in nvidia-smi topo), all transfers go through host memory.
  4. Host topology layer: IOMMU groups are separate, ACS is not the cause, each GPU is on its own root complex.
  5. PCIe negotiation layer: What link speed are the GPUs actually running at inside the VM? The assistant reached step 5 naturally after exhausting the earlier layers. Having determined that P2P DMA was fundamentally impossible due to hardware topology, and having mapped out the NUMA and PCIe topology in detail, the next logical question was: "Even for host-mediated transfers, what bandwidth is actually available?" The nvidia-smi PCIe link query was the most direct way to answer this. The choice of nvidia-smi over other tools (like lspci or setpci) reflects a practical decision. nvidia-smi provides a clean, machine-parseable output format (--format=csv,noheader) that integrates easily into a shell pipeline. It also reports the GPU driver's view of the link status, which is the most relevant perspective for understanding how the GPU software stack will behave.

Broader Implications

This message, for all its brevity, fundamentally changes the understanding of the virtualization bottleneck. The earlier diagnosis — "P2P is unsupported, causing high latency on small transfers" — was incomplete. The full diagnosis is: "P2P is unsupported, AND the PCIe link speed is capped at Gen1, limiting all PCIe bandwidth to 4 GB/s."

This dual constraint has different effects at different scales. For the small messages typical of NCCL all-reduce operations on a model with hidden_size=6144 (a few hundred KB per tensor), the latency penalty dominates. But for larger operations — loading model weights, transferring KV cache blocks, or any bulk data movement — the bandwidth ceiling becomes equally important.

The finding also raises questions about the QEMU/KVM virtualization stack. Why does a Gen5-capable GPU negotiate only Gen1 inside a Q35 VM? Is this a limitation of the virtual PCIe root port emulation, a VFIO driver issue, or a configuration problem? The answer would determine whether this can be fixed at all within the VM context.

Conclusion

Message 389 is a masterclass in diagnostic efficiency. A single nvidia-smi command, taking milliseconds to execute, revealed a critical parameter that had been overlooked through hours of complex topology analysis. The output — eight lines showing 1, 16 — tells a story of virtualization overhead that is even more severe than previously understood. The GPUs, capable of Gen5 ×16 communication, are limited to Gen1 ×16 inside the VM, representing a 16× bandwidth reduction on top of the already-crippling lack of P2P DMA support.

This message exemplifies the importance of checking fundamental assumptions, even (or especially) when deep into a complex investigation. The assistant had assumed that PCIe link speed would be preserved through virtualization, but the data proved otherwise. The discovery opens new diagnostic avenues and reshapes the mitigation strategy. It is a reminder that in systems debugging, the most valuable insights often come from the simplest queries — if you know which questions to ask.