Mapping the Invisible Topology: Tracing GPU NUMA Affinity Across the Virtualization Boundary

In the ongoing battle to squeeze performance from eight NVIDIA RTX PRO 6000 Blackwell GPUs running inside a Proxmox virtual machine, message [msg 373] represents a quiet but pivotal diagnostic pivot. After rounds of kernel parameter tweaking, chipset migration, and ACS disable attempts—all aimed at enabling peer-to-peer (P2P) DMA between GPUs—the assistant takes a step back from the "fix it" mindset and instead asks a more fundamental question: what is the actual topology, and can we at least get the NUMA affinity right?

This message is a data-gathering operation, pure and simple. It contains two shell commands executed against the VM, and their outputs. But beneath the surface, it represents a critical reorientation of the debugging strategy—a recognition that if you cannot change the hardware reality, you must at least measure it accurately before deciding what to optimize next.

The Message Itself

The assistant begins with a short preamble:

Now I know the mapping. Let me also figure out which physical GPU maps to which VM GPU index.

Then two bash commands are dispatched in parallel. The first queries the VM's NVIDIA driver for each GPU's index, PCI bus ID, and UUID:

nvidia-smi --query-gpu=index,pci.bus_id,uuid --format=csv,noheader

The second runs detailed lspci queries on each of the eight PCI addresses visible inside the VM:

sudo lspci -v -s 01:00.0 ... 08:00.0

The outputs reveal that inside the VM, the GPUs appear at PCI addresses 0000:01:00.0 through 0000:08:00.0, each with a unique UUID and a 64-bit prefetchable memory region of 64MB. The lspci output for GPU 0 shows it is a "3D controller: NVIDIA Corporation Device 2bb5 (rev a1)" in "Physical Slot: 0", while GPU 1 shows "Physical Slot: 0-2"—a subtle difference that hints at the underlying physical slot numbering on the motherboard.

Why This Message Was Written: The Reasoning and Motivation

To understand why this message exists, one must understand the dead end the conversation had just reached. In the preceding messages ([msg 360] through [msg 372]), the assistant and user had been on a determined quest to enable P2P DMA between GPUs inside the VM. This quest had taken them through:

• Verifying that all 8 GPUs were detected after the Q35 chipset migration and pci=realloc fix
• Discovering that P2P was still showing "NS" (Not Supported) in nvidia-smi topo -p2p
• Researching VFIO P2P documentation and NVIDIA's AI Enterprise VM configuration guides
• Learning that virtual PCIe switch topologies could change the reported topology but not the actual data path
• Comparing the VM's topology output (all PHB) against a bare-metal topology the user provided (showing NODE within sockets and SYS across sockets)
• Realizing that the VM was missing NUMA affinity entirely—all GPUs showed affinity to "NUMA 0-1" rather than being split across two NUMA nodes as they were on bare metal The user's bare-metal topology had shown a clear NUMA split: GPUs 0-3 on NUMA node 0, GPUs 4-7 on NUMA node 1. This distinction is critical for NCCL (NVIDIA Collective Communications Library) performance, because intra-NUMA transfers (NODE) are faster than cross-NUMA transfers (SYS). Without NUMA affinity in the VM, NCCL treats all GPU pairs identically, losing the opportunity to optimize communication patterns. In [msg 371], the assistant had asked the user to run a command on the Proxmox host to determine which physical PCI addresses belonged to which NUMA node. The user responded in [msg 372] with the answer:
• 01:00.0, 11:00.0, 61:00.0, 71:00.0 → NUMA 0
• 81:00.0, 91:00.0, e1:00.0, f1:00.0 → NUMA 1 Now, in [msg 373], the assistant takes this host-side NUMA mapping and attempts to cross-reference it with the VM-side view. The critical question is: do the VM's PCI bus addresses (01:00.0 through 08:00.0) correspond directly to the host's PCI addresses? If the mapping is straightforward, then GPUs 0-3 in the VM (at PCI 01:00.0–04:00.0) would map to NUMA 0, and GPUs 4-7 (at 05:00.0–08:00.0) would map to NUMA 1. But this is not guaranteed—the VM's PCI topology is virtualized, and the QEMU/Proxmox PCI assignment may reorder or remap devices. The motivation is clear: the assistant needs to build a complete, verified mapping from VM GPU index → VM PCI address → host PCI address → NUMA node. Only with this mapping can the team attempt to fix the NUMA affinity problem, either by reordering the hostpci mappings in the Proxmox configuration or by constructing a more sophisticated virtual PCIe topology.

How Decisions Were Made

This message is notable for what it does not contain: there are no configuration changes, no kernel parameter tweaks, no server launches. The decision made here is a methodological one—to stop guessing and start measuring.

The assistant chooses to run two complementary commands in parallel. The nvidia-smi query provides the high-level mapping from GPU index (0-7) to PCI bus ID and UUID. The lspci queries provide the low-level hardware details: device class, vendor, subsystem, physical slot number, and memory mapping. Together, these create a fingerprint for each GPU that can be cross-referenced against the host-side data.

The choice of lspci -v (verbose) rather than a simpler lspci is deliberate. The verbose output includes the "Physical Slot" field, which reveals the motherboard's slot numbering—a crucial clue for mapping VM GPUs to physical slots and, by extension, to NUMA nodes. The assistant is thinking several steps ahead: once the physical slot is known, it can be correlated with the host's PCI topology to determine which NUMA node each GPU belongs to.

Assumptions Made

The assistant makes several implicit assumptions in this message:

1. The VM's PCI bus numbering preserves some ordering from the host. The assistant assumes that 01:00.0 in the VM corresponds to one of the host's NUMA-0 GPUs, but this is not verified within the message itself—it's a hypothesis to be tested.
2. UUIDs are stable identifiers. By collecting UUIDs, the assistant assumes these will match between the VM and host views, providing a reliable cross-reference. This is generally true for NVIDIA GPUs, but it's worth noting that UUIDs can change under certain conditions (e.g., GPU reset, driver reinstallation).
3. The lspci output will complete successfully for all eight GPUs. The truncated output (the message cuts off at GPU 2) suggests the command may have been interrupted or the output was too large. The assistant assumes the data was gathered successfully even though only partial output is visible.
4. Physical slot numbers are meaningful. The assistant treats "Physical Slot: 0" and "Physical Slot: 0-2" as useful topology information. This assumes the motherboard firmware reports accurate slot numbers that correlate with the physical PCIe slot layout.

Mistakes or Incorrect Assumptions

The most notable issue is the truncated output. The second bash command's output is cut off mid-stream:

03:00.0 3D controller: N...

This is a critical data loss. The assistant cannot see the lspci details for GPUs 2-7 in the visible portion of the message. However, since the tool calls were dispatched in parallel and the assistant waits for all results before proceeding, the full data was likely available to the assistant in the subsequent reasoning—it's only the displayed output that is truncated. This is a limitation of the conversation rendering, not necessarily a failure in the assistant's actual execution.

A more subtle concern is the assumption of direct mapping. The VM's PCI addresses (01:00.0 through 08:00.0) are sequential and clean, which is suspicious. On the host, the GPUs are scattered across very different PCI domains (01:00.0, 11:00.0, 61:00.0, 71:00.0, 81:00.0, 91:00.0, e1:00.0, f1:00.0). The VM's QEMU PCI bridge is remapping these into a compact, contiguous address space. The assistant does not yet know whether the order of GPUs in the VM matches the order on the host. It's possible that GPU 0 in the VM (at 01:00.0) corresponds to a GPU from NUMA 1 on the host, depending on how Proxmox enumerated the hostpci devices. The UUIDs will resolve this, but the mapping is not yet established within this message.

Input Knowledge Required

To fully understand this message, a reader needs:

1. The preceding conversation context: The long struggle with P2P, the Q35 migration, the BAR allocation fix, the ACS disable attempt, and the discovery that the hardware topology (each GPU on its own PCIe root complex) fundamentally prevents P2P.
2. The bare-metal topology comparison: The user's paste of nvidia-smi topo -m showing NODE and SYS connections with proper NUMA affinity, which served as the "gold standard" the VM was being measured against.
3. The host-side NUMA mapping: The user's output from [msg 372] showing which host PCI addresses belong to which NUMA node.
4. Understanding of PCIe topology concepts: What PCI bus addresses mean, how nvidia-smi topo -m works, what NUMA nodes are, and how VFIO/IOMMU mediate device access in virtualized environments.
5. Knowledge of NCCL communication patterns: Why NODE vs SYS distinctions matter for collective communication performance, and why NUMA affinity is important for optimizing all-reduce operations.

Output Knowledge Created

This message produces several valuable pieces of information:

1. VM GPU index to PCI address mapping: GPU 0 → 01:00.0, GPU 1 → 02:00.0, etc. This is the VM's internal view of the PCI topology.
2. GPU UUIDs: Unique identifiers for each GPU that can be cross-referenced with the host's view to establish a definitive mapping.
3. Physical slot information: GPU 0 is in "Physical Slot: 0", GPU 1 is in "Physical Slot: 0-2". This hints at the motherboard's physical layout and may help correlate with the host's PCI topology.
4. Device class and vendor confirmation: All eight GPUs are confirmed as "NVIDIA Corporation Device 2bb5 (rev a1)"—the Blackwell RTX PRO 6000—with proper subsystem IDs.
5. Memory mapping validation: Each GPU has a 64-bit prefetchable memory region of 64MB, confirming the BAR allocation fix (pci=realloc) is working correctly. This output knowledge feeds directly into the next step: cross-referencing UUIDs between the VM and host to definitively map each VM GPU index to a NUMA node. Once that mapping is established, the team can attempt to reconfigure the VM's PCI topology to restore NUMA affinity—potentially recovering the NODE/SYS distinction that NCCL needs for optimal performance.

The Thinking Process Visible in Reasoning Parts

The assistant's reasoning is visible in the structure of the message itself. The phrase "Now I know the mapping" refers to the host-side NUMA data from [msg 372]. The assistant immediately recognizes that this host-side data is only half the picture—it needs to be correlated with the VM's internal view.

The choice to query UUIDs is particularly insightful. PCI bus addresses can change between reboots or configuration changes (as the team has experienced multiple times during this session). UUIDs are hardware-level identifiers burned into the GPU's firmware, providing a stable cross-reference that survives VM reconfiguration. This is the thinking of someone who has been burned by shifting PCI addresses and wants an invariant.

The parallel dispatch of both commands also reveals the assistant's efficiency mindset. Rather than running one command, analyzing it, then running the next, both queries are launched simultaneously because they are independent. This is a hallmark of the opencode session model: tool calls within a single round are dispatched in parallel, and the assistant waits for all results before proceeding. The assistant is exploiting this parallelism to gather complementary data in a single round.

The truncation of the lspci output is unfortunate but revealing. It suggests the assistant may have underestimated the verbosity of the output, or that the conversation rendering system has a display limit. In either case, the assistant likely received the full data internally (the tool result) even though only part is shown in the conversation transcript. This is a reminder that the visible conversation is not always the complete picture—the assistant operates on the full tool results, not the displayed excerpts.

Conclusion

Message [msg 373] is a diagnostic interlude in a larger debugging narrative. It does not fix P2P, it does not launch a server, and it does not produce a performance benchmark. But it is essential groundwork. By establishing the VM-side GPU inventory with PCI addresses, UUIDs, and physical slot information, the assistant creates the data foundation needed for the next logical step: cross-referencing against the host's NUMA topology to determine whether NUMA affinity can be restored.

In the broader arc of the session, this message marks a transition from "can we hack P2P?" to "can we at least get the topology right?" It is the moment when the assistant accepts the hardware limitation (no P2P possible across separate root complexes) and pivots to optimizing what can be controlled: NUMA affinity, PCIe topology reporting, and NCCL communication patterns. Sometimes the most valuable work is not the breakthrough fix but the careful measurement that reveals what is actually possible.