The Moment Everything Broke: When Eight GPUs Became Two

A Deep Analysis of Message 331 in the Proxmox GPU Passthrough Saga

1. Introduction

In the long and winding journey of deploying a large language model inference server across eight NVIDIA RTX PRO 6000 Blackwell GPUs inside a Proxmox virtual machine, there comes a moment of dramatic reversal. Message 331 in this conversation is that moment. It is the message where the user, having diligently applied a series of carefully reasoned configuration changes recommended by the AI assistant, reboots the system and discovers that the grand plan has backfired catastrophically: only two of the eight GPUs are recognized by the NVIDIA driver.

This message is a masterclass in the gap between theory and practice in systems administration. It demonstrates how even well-researched, logically sound configuration changes can produce unexpected and severe side effects when they interact with the complex realities of hardware topology, firmware behavior, and kernel resource allocation. The message is also a turning point in the conversation—the point at which the team realizes that enabling Peer-to-Peer (P2P) DMA between GPUs in a virtualized environment is going to be far more difficult than initially hoped, and that the immediate priority must shift from performance optimization to basic functionality recovery.

In this article, we will dissect message 331 in exhaustive detail. We will examine the reasoning that led to the changes being made, the assumptions that proved incorrect, the diagnostic value of the data the user provided, and the cascade of consequences that flowed from this single reboot. We will also explore the broader context of GPU virtualization, PCIe BAR allocation, and the delicate art of configuring Proxmox for high-performance GPU workloads. By the end, you will understand not just what happened in this message, but why it happened, what it reveals about the underlying systems, and how it shaped the subsequent direction of the entire project.

2. Context: The Road to Message 331

2.1 The Project: Deploying GLM-5-NVFP4 on Eight Blackwell GPUs

To understand message 331, we must first understand the project that gave rise to it. The conversation is part of a larger effort to deploy the GLM-5-NVFP4 large language model—a massive, state-of-the-art neural network—using the SGLang inference engine across eight NVIDIA RTX PRO 6000 Blackwell GPUs. These GPUs, each with 96 GB of VRAM (reported as 97887 MiB), represent a staggering amount of computational power. The RTX PRO 6000 Blackwell is NVIDIA's professional workstation GPU based on the Blackwell architecture, and eight of them in a single system constitute a formidable inference server.

The machine in question is a server running Proxmox VE (a Debian-based hypervisor) on an AMD EPYC 9335 processor platform. The eight GPUs are passed through to a virtual machine (VM ID 128, named "llm-one") using VFIO (Virtual Function I/O), the Linux framework for direct device assignment to virtual machines. The VM runs Ubuntu 24.04 with a custom kernel and the NVIDIA proprietary driver stack.

2.2 The P2P Bottleneck

The conversation leading up to message 331 is driven by a single, critical performance problem: Peer-to-Peer (P2P) DMA between GPUs is not working inside the VM. When the SGLang inference engine runs with tensor parallelism across multiple GPUs, it needs to frequently exchange data between them—activations, gradients, attention states, and so on. If P2P DMA is not available, every cross-GPU transfer must go through system memory (host RAM), which adds approximately 14 microseconds of latency per transfer. This latency accumulates across hundreds or thousands of transfers per inference step, dramatically reducing throughput.

The NVIDIA driver reports P2P status using a matrix of codes: OK means P2P is fully supported, NS means "Not Supported," PHB means the GPUs are on different PCIe host bridges, and so on. In the initial configuration, all GPU pairs showed NS for P2P, and the topology showed them on a flat PCI bus (the legacy i440FX chipset emulated by QEMU). The assistant correctly identified that the root cause was likely a combination of:

  1. The host kernel not using IOMMU passthrough mode (iommu=pt), which adds translation overhead
  2. The VM using the legacy i440FX chipset instead of Q35, which doesn't model PCIe properly
  3. The GPU passthrough entries missing pcie=1, which presents GPUs as conventional PCI devices rather than PCIe devices

2.3 The Assistant's Three-Phase Plan

In message 330, the assistant laid out a carefully structured three-phase plan to address these issues:

Phase 1 (Low risk, no host reboot): Add pcie=1 to all eight hostpci entries in the VM configuration. This would make QEMU present the GPUs as proper PCIe devices, potentially enabling the NVIDIA driver to use PCIe-native features like ACS (Access Control Services) and ARI (Alternative Routing-ID Interpretation).

Phase 2 (Requires host reboot): Add amd_iommu=on iommu=pt to the Proxmox host kernel command line. The iommu=pt parameter enables IOMMU passthrough mode, which skips address translation for devices assigned to VFIO, reducing DMA latency.

Phase 3 (Higher risk): Switch the VM from the i440FX chipset to Q35, which provides proper PCIe topology modeling. The assistant explicitly recommended deferring this step unless Phase 1 and 2 proved insufficient, noting that it "may require driver reinstallation inside the VM."

The assistant's reasoning was sound: Phase 1 and 2 were incremental changes that could be tested independently, while Phase 3 was a more fundamental architectural change. The plan was to proceed cautiously, testing P2P status after each phase.

2.4 What Actually Happened

The user, however, did not follow the phased approach. Instead, they applied all three changes simultaneously:

  1. Added pcie=1 to all eight hostpci entries
  2. Switched the machine type from i440FX to Q35 (machine: q35)
  3. Added amd_iommu=on iommu=pt to the host kernel command line
  4. Rebooted both the host and the VM This is the state captured in message 331. The user's question—"Do I want vIOMMU enabled in Machine setting?"—suggests they were thinking ahead about further optimizations even as they reported the results of the changes already made. But the data they provided told a very different story from what anyone expected.

3. The Message Itself: A Detailed Reading

3.1 The Question: vIOMMU

The message begins with a question that reveals the user's mindset:

Do I want vIOMMU enabled in Machine setting?

This is a reasonable question from someone who has been reading about GPU virtualization and IOMMU configuration. The user has just enabled IOMMU passthrough on the host (amd_iommu=on iommu=pt), and they are wondering whether a virtual IOMMU (vIOMMU) inside the VM would provide additional benefits. The question shows that the user is thinking proactively about optimization, trying to understand which levers to pull.

However, the question also reveals a potential misunderstanding. Host IOMMU (the physical IOMMU built into the AMD EPYC CPU) and virtual IOMMU (an emulated IOMMU presented to the guest OS by QEMU) are fundamentally different things. The host IOMMU translates DMA addresses from PCIe devices before they reach system memory—it's a security and isolation mechanism that also enables device passthrough. A virtual IOMMU, on the other hand, adds another layer of address translation inside the guest, which typically increases overhead rather than reducing it. In most GPU passthrough scenarios, vIOMMU is not recommended.

3.2 The VM Configuration: Evidence of Changes Applied

The user provides the output of qm config 128, which shows the current VM configuration after the changes:

hostpci0: mapping=pro6000,pcie=1
hostpci1: mapping=pro6000,pcie=1
hostpci2: mapping=pro6000,pcie=1
hostpci3: mapping=pro6000,pcie=1
hostpci4: mapping=pro6000,pcie=1
hostpci5: mapping=pro6000,pcie=1
hostpci6: mapping=pro6000,pcie=1
hostpci7: mapping=pro6000,pcie=1

All eight entries now have pcie=1 appended. The machine type is confirmed as machine: q35. The host kernel command line, shown separately, includes amd_iommu=on iommu=pt. Everything the assistant recommended has been applied.

The VM configuration also reveals other interesting details:

3.3 The Host Kernel Command Line: Evidence of Phase 2

root@kpro6:~# cat /proc/cmdline 
initrd=\EFI\proxmox\6.8.12-9-pve\initrd.img-6.8.12-9-pve root=ZFS=rpool/ROOT/pve-1 amd_iommu=on iommu=pt boot=zfs vmlinuz

The host kernel now has amd_iommu=on iommu=pt in its command line. This confirms that Phase 2 was successfully applied. The host has been rebooted (the user said "Also rebooted now"), and the new kernel parameters are active.

3.4 The Guest dmesg: A Story of Failure

The bulk of message 331 is the guest VM's dmesg output—thousands of lines of kernel boot messages. This is where the story of the failed GPU detection unfolds. Let me walk through the key diagnostic signals embedded in this output.

3.4.1 The Q35 Machine Type is Confirmed

Early in the dmesg, we see:

[    0.000000] DMI: QEMU Standard PC (Q35 + ICH9, 2009), BIOS rel-1.16.3-0-ga6ed6b701f0a-prebuilt.qemu.org 04/01/2014

This confirms that the VM is now using the Q35 chipset, as intended. The BIOS is SeaBIOS (version 1.16.3), which is the default BIOS for QEMU VMs. This is important because SeaBIOS has specific limitations when it comes to allocating large PCI BARs, as we will see.

3.4.2 The PCI Topology is Revealed

The dmesg shows the PCI topology that QEMU has constructed for the eight GPUs:

pci 0000:00:10.0: PCI bridge to [bus 01]
pci 0000:00:10.1: PCI bridge to [bus 02]
pci 0000:00:10.2: PCI bridge to [bus 03]
pci 0000:00:10.3: PCI bridge to [bus 04]
pci 0000:00:1c.0: PCI bridge to [bus 05]
pci 0000:00:1c.1: PCI bridge to [bus 06]
pci 0000:00:1c.2: PCI bridge to [bus 07]
pci 0000:00:1c.3: PCI bridge to [bus 08]

Each GPU is on its own PCIe root port, which is the correct configuration for Q35 with pcie=1. The first four GPUs are on root ports 00:10.0 through 00:10.3 (the "north" PCIe root complex), and the remaining four are on 00:1c.0 through 00:1c.3 (the "south" PCIe root complex). This is a significant improvement over the i440FX configuration, where all GPUs would have been on a flat PCI bus behind a single PCI-to-PCI bridge.

3.4.3 The Bridge Windows Are Allocated

For each PCIe root port, QEMU allocates a memory window for the GPU's BARs. The dmesg shows these allocations:

pci 0000:00:10.0:   bridge window [mem 0x391800000000-0x393fffffffff 64bit pref]
pci 0000:00:10.1:   bridge window [mem 0x38f000000000-0x3917ffffffff 64bit pref]
pci 0000:00:10.2:   bridge window [mem 0x38c800000000-0x38efffffffff 64bit pref]
pci 0000:00:10.3:   bridge window [mem 0x38a000000000-0x38c7ffffffff 64bit pref]
pci 0000:00:1c.0:   bridge window [mem 0x387800000000-0x389fffffffff 64bit pref]
pci 0000:00:1c.1:   bridge window [mem 0x385000000000-0x3877ffffffff 64bit pref]
pci 0000:00:1c.2:   bridge window [mem 0x382800000000-0x384fffffffff 64bit pref]
pci 0000:00:1c.3:   bridge window [mem 0x380000000000-0x3827ffffffff 64bit pref]

Each window is 160 GB in size (e.g., 0x391800000000 to 0x393fffffffff = 0x27FFFFFFFF = ~160 GB). The total address space consumed by all eight windows is approximately 1.28 TB, which fits within the root bus resource window of [mem 0x380000000000-0x395fffffffff] (approximately 1.5 TB).

3.4.4 The BAR Allocation Failures

Despite the bridge windows being correctly allocated, the individual GPU BARs fail to be assigned within those windows. The dmesg shows:

pci 0000:01:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
pci 0000:01:00.0: BAR 2 [mem 0x390000000000-0x391fffffffff 64bit pref]: failed to assign

This pattern repeats for GPUs at 01:00.0, 02:00.0, 03:00.0, 05:00.0, 06:00.0, and 07:00.0. Only GPUs at 04:00.0 and 08:00.0 succeed.

Each GPU has three BARs:

3.4.5 The NVIDIA Driver Failures

The consequence of the BAR allocation failures is that the NVIDIA driver cannot initialize the affected GPUs:

NVRM: This PCI I/O region assigned to your NVIDIA device is invalid:
NVRM: BAR2 is 0M @ 0x0 (PCI:0000:01:00.0)
nvidia: probe of 0000:01:00.0 failed with error -1

This message repeats for six GPUs. The NVIDIA driver checks that BAR2 has been assigned a valid memory address, and when it finds BAR2 at address 0 (meaning it was never assigned), it refuses to initialize the device. The driver's error handling is correct—a GPU with no VRAM mapping is unusable.

Only two GPUs survive:

[drm] Initialized nvidia-drm 0.0.0 20160202 for 0000:04:00.0 on minor 0
[drm] Initialized nvidia-drm 0.0.0 20160202 for 0000:08:00.0 on minor 1

These correspond to the last GPU on the north complex (bus 04) and the last GPU on the south complex (bus 08). Why these two succeeded while the others failed is a question we will explore in depth later.

3.4.6 The Kernel's Own Diagnostic

Perhaps the most telling line in the entire dmesg output is this one:

pci_bus 0000:00: Some PCI device resources are unassigned, try booting with pci=realloc

This is the Linux kernel's PCI subsystem telling us exactly what to do. The kernel has detected that some PCI devices have unassigned BARs, and it knows that the pci=realloc kernel parameter can trigger a reallocation pass that might fix the problem. This diagnostic message is the single most important piece of information in the entire message 331 output, and it directly shapes the next phase of the conversation.

3.5 The nvidia-smi Output: The Bottom Line

The final piece of data in message 331 is the nvidia-smi output:

+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 590.48.01              Driver Version: 590.48.01      CUDA Version: 13.1     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    Off |   00000000:04:00.0 Off |                    0 |
| N/A   24C    P8             33W /  600W |       0MiB /  97887MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+
|   1  NVIDIA RTX PRO 6000 Blac...    Off |   00000000:08:00.0 Off |                    0 |
| N/A   25C    P8             34W /  600W |       0MiB /  97887MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+

Only two GPUs are visible. Both show their full 97887 MiB of VRAM (the 96 GB capacity), and both are at low power (P8 state, 33-34W). The driver version is 590.48.01, and CUDA version is 13.1. The GPUs are on buses 04:00.0 and 08:00.0, which matches the dmesg output showing only those two GPUs being initialized.

4. The Diagnostic Value of Message 331

4.1 What the Data Tells Us

Message 331 is extraordinarily rich in diagnostic information. Let me enumerate the key insights that can be extracted from the data the user provided:

1. The Q35 switch worked structurally. The PCI topology shows eight separate PCIe root ports, each with its own bridge window. The GPUs are properly presented as PCIe devices (the dmesg shows PCIe Legacy Endpoint for each GPU). The machine type change was successful from a QEMU perspective.

2. The host IOMMU changes worked. The host kernel command line includes amd_iommu=on iommu=pt, and the VM boots successfully with VFIO passthrough. There are no IOMMU-related errors in the dmesg.

3. The BAR allocation problem is the critical bottleneck. The root cause of the GPU detection failure is clear: the guest firmware (SeaBIOS) cannot allocate 128 GB BAR2 regions for all eight GPUs within the available 64-bit MMIO space. Only two GPUs get their BAR2 assigned.

4. The problem is in the guest firmware, not QEMU. The bridge windows are correctly sized and allocated by QEMU. The failure occurs when the guest kernel's PCI subsystem tries to assign BARs within those windows. The kernel's own suggestion (pci=realloc) points to a guest-side solution.

5. The two surviving GPUs are at the "ends" of the topology. GPU 0 (bus 04:00.0) is the last GPU on the north complex, and GPU 1 (bus 08:00.0) is the last GPU on the south complex. This suggests that the BAR allocation algorithm processes devices in order and runs out of space partway through, but the exact reason why 04 and 08 succeed while 01-03 and 05-07 fail requires deeper analysis.

4.2 What the Data Does NOT Tell Us

While message 331 is rich in diagnostic data, it also has some notable gaps:

1. We don't see the pre-change state. The user didn't provide a dmesg from before the changes, so we can't directly compare the old and new PCI topologies. We know from earlier messages that the old configuration used i440FX, but we don't have a detailed dmesg from that state.

2. We don't see the exact BAR allocation order. The dmesg shows the bridge window assignments and the BAR failures, but it doesn't show the exact order in which the kernel tried to assign BARs. This makes it harder to determine why specific GPUs succeeded or failed.

3. We don't see the host-side QEMU configuration for the MMIO window. The size of the 64-bit MMIO window is determined by QEMU based on the host-phys-bits CPU property. We don't have direct evidence of what value QEMU used.

4. We don't have P2P status. The user didn't run nvidia-smi topo -p2p or nvidia-smi topo -m at this point. We know from subsequent messages that P2P would still show NS (Not Supported), but we don't have that data within message 331 itself.

4.3 The Critical Diagnostic Clue

The single most important piece of diagnostic information in message 331 is the kernel's own message:

pci_bus 0000:00: Some PCI device resources are unassigned, try booting with pci=realloc

This message is generated by the Linux kernel's PCI resource allocation code when it detects that some devices have BARs that could not be assigned during the initial enumeration pass. The pci=realloc kernel parameter tells the PCI subsystem to perform a second pass that aggressively reassigns resources, potentially moving bridge windows and reallocating BARs to make everything fit.

The fact that the kernel itself suggests this fix is significant. It means the problem is not a fundamental hardware limitation (the bridge windows are large enough) but rather a firmware/BIOS issue. SeaBIOS, the open-source BIOS used by QEMU, has a relatively simple PCI resource allocation algorithm that may not handle the case of eight GPUs each requiring 128 GB BARs. The kernel's pci=realloc can override the firmware's decisions and find a working allocation.

5. The Technical Deep Dive: Why Did BAR Allocation Fail?

5.1 Understanding PCI BARs

Every PCIe device has Base Address Registers (BARs) that define the memory or I/O address ranges the device will respond to. When the system boots, the firmware (BIOS or UEFI) enumerates all PCIe devices, reads their BAR size requirements, and assigns address ranges from the available address space. The operating system can then use these assigned addresses to communicate with the devices.

For modern GPUs, the BARs are enormous:

5.2 The 64-bit MMIO Window

On x86 systems, PCIe memory address space is divided into two regions:

pci_bus 0000:00: root bus resource [mem 0x380000000000-0x395fffffffff window]

This is approximately 1.5 TB of 64-bit MMIO space. With eight GPUs each needing 128 GB for BAR2, plus smaller BARs, the total requirement is about 1.03 TB (8 × 128 GB + 8 × 64 MB + 8 × 32 MB). This should fit within 1.5 TB, but the allocation fails because of alignment constraints and fragmentation.

5.3 The Alignment Problem

The critical constraint is that each BAR must be naturally aligned: the base address must be a multiple of the BAR size. For a 128 GB BAR, the base address must be a multiple of 128 GB. This means the eight BAR2 regions must be placed at addresses like:

5.4 Why Two GPUs Succeeded

The two GPUs that succeeded are at buses 04 and 08—the last GPU on each PCIe root complex. This is not a coincidence. The PCI enumeration and BAR allocation typically proceeds in order: bus 00 devices first, then bus 01, bus 02, etc. When the allocator reaches bus 04 (the fourth GPU on the north complex), it has already allocated BARs for buses 01, 02, and 03. If the allocation for buses 01-03 consumed more space than expected due to alignment padding, bus 04 might be the first one that fits within the remaining space.

Similarly on the south complex, buses 05, 06, and 07 might fail before bus 08 succeeds. The exact pattern depends on the specific alignment of bridge windows and BARs, which is determined by SeaBIOS's allocation algorithm.

5.5 The SeaBIOS Limitation

SeaBIOS is a minimal, open-source BIOS implementation designed for QEMU. It is not a full-featured firmware like OVMF (UEFI) or a commercial BIOS. Its PCI resource allocation is relatively simple and may not handle extreme configurations like eight GPUs with 128 GB BARs.

The dmesg output shows that SeaBIOS 1.16.3 is being used. This version was released in 2023 and should support large BARs, but the interaction between multiple large BARs and the bridge window allocation may expose edge cases in the allocator.

The kernel's pci=realloc parameter provides a workaround: after the firmware's initial allocation, the kernel can perform its own reallocation pass using a more sophisticated algorithm. This is why the kernel suggests it as a fix.

6. Assumptions and Their Consequences

6.1 The Assistant's Assumptions

In message 330, the assistant made several assumptions that proved to be incorrect or incomplete:

Assumption 1: The Q35 switch would be straightforward. The assistant acknowledged that switching to Q35 "may require driver reinstallation inside the VM" but did not anticipate the BAR allocation failure. The assumption was that QEMU would handle the large BARs correctly, and the main risk was driver compatibility.

Assumption 2: The phased approach would be followed. The assistant recommended a three-phase plan with testing after each phase. The assumption was that the user would apply changes incrementally, allowing problems to be isolated. Instead, the user applied all changes at once, making it harder to determine which change caused the BAR allocation problem.

Assumption 3: pcie=1 would not cause BAR issues. The assistant correctly identified that pcie=1 was needed for proper PCIe topology, but did not anticipate that presenting GPUs as PCIe devices (rather than conventional PCI devices) would change the BAR allocation behavior. In the i440FX configuration, the GPUs were behind a PCI-to-PCI bridge, which may have handled BAR allocation differently.

Assumption 4: The host IOMMU changes were independent. The assistant treated the host kernel cmdline changes (Phase 2) as independent of the VM configuration changes (Phase 1 and 3). While this is technically correct—the host IOMMU changes don't affect BAR allocation inside the VM—the assumption that all three changes could be applied simultaneously without interaction proved optimistic.

6.2 The User's Assumptions

The user also made assumptions that shaped their actions:

Assumption 1: More changes are better. The user applied all three phases at once, likely assuming that if the changes were all beneficial, applying them together would save time. This is a common heuristic in system administration, but it violates the principle of "one change at a time" that is crucial for debugging complex systems.

Assumption 2: The reboot would fix everything. The user rebooted the host (to apply kernel cmdline changes) and the VM (to apply Q35 and pcie=1 changes) and expected the system to come back with all eight GPUs working. When it didn't, they were understandably confused and asked about vIOMMU as a potential next step.

Assumption 3: vIOMMU might help. The user's question about vIOMMU suggests they were thinking of IOMMU as a solution to all GPU passthrough problems. While vIOMMU can be useful in some scenarios (e.g., for device hotplug or for guest-initiated DMA remapping), it would not help with BAR allocation—in fact, it would add overhead.

6.3 The Cost of Assumptions

The gap between assumptions and reality in message 331 is substantial. The assistant expected a smooth transition to Q35 with improved P2P topology. The user expected all eight GPUs to work after the reboot. Instead, the system went from eight working GPUs (in the i440FX configuration) to only two working GPUs (in the Q35 configuration). This is a regression, not an improvement.

However, it's important to note that this regression is not necessarily permanent. The kernel's pci=realloc suggestion provides a clear path forward. The system can be fixed. But the immediate cost is downtime and debugging effort.

7. The Thinking Process: What the Assistant Should Have Done Differently

7.1 Anticipating the BAR Problem

In retrospect, the assistant should have anticipated the BAR allocation problem. The RTX PRO 6000 Blackwell is a new GPU (released in 2025), and its 128 GB BAR2 is unusually large. The combination of eight such GPUs in a single VM is an extreme configuration that pushes against the limits of SeaBIOS's PCI resource allocation.

The assistant could have:

  1. Warned about BAR allocation risks when recommending the Q35 switch
  2. Suggested testing with one GPU first to verify that Q35 + pcie=1 works before adding all eight
  3. Recommended OVMF instead of SeaBIOS from the start, since OVMF has better large BAR support
  4. Prepared the pci=realloc fix as part of the plan rather than as a reactive measure

7.2 The Phased Approach Failure

The assistant's three-phase plan was sound in theory but failed in practice because the user didn't follow it. This is a common challenge in remote system administration: the person executing the commands may not have the same understanding of the risks and dependencies as the person designing the plan.

A better approach might have been to:

  1. Explicitly warn against applying all changes at once
  2. Provide a clear testing procedure for each phase
  3. Make the phases more granular (e.g., Phase 1a: add pcie=1 to one GPU, test; Phase 1b: add pcie=1 to all GPUs, test; etc.)

7.3 The vIOMMU Distraction

The user's question about vIOMMU, while reasonable, is a distraction from the immediate problem. The assistant correctly recognized this in the subsequent message (332), advising against enabling vIOMMU. But the fact that the user asked about vIOMMU at all suggests they were looking for a "magic bullet" solution to the GPU detection problem, rather than focusing on the clear diagnostic signal in the dmesg.

8. The Broader Context: GPU Virtualization Challenges

8.1 The VFIO/IOMMU Stack

GPU passthrough in Proxmox relies on a complex stack of technologies:

  1. VFIO (Virtual Function I/O): A Linux kernel framework for direct device assignment to virtual machines. VFIO allows a physical device to be "passed through" to a VM, giving the guest OS direct access to the device's PCIe configuration space, BARs, and interrupts.
  2. IOMMU (I/O Memory Management Unit): A hardware component in modern CPUs (both Intel VT-d and AMD-Vi) that translates DMA addresses from PCIe devices. The IOMMU provides isolation: a device assigned to a VM can only DMA to memory pages that the hypervisor has explicitly mapped for it.
  3. PCIe ACS (Access Control Services): A PCIe feature that controls peer-to-peer transactions between devices. ACS can be used to enforce isolation between devices in different IOMMU groups.
  4. QEMU/KVM: The hypervisor that emulates the virtual machine hardware and manages device passthrough. Each layer in this stack adds complexity and potential failure modes. Message 331 demonstrates how a change at the QEMU level (machine type and PCIe topology) can interact unexpectedly with the guest firmware and kernel.

8.2 The SeaBIOS vs. OVMF Tradeoff

SeaBIOS and OVMF are the two firmware options for QEMU VMs:

SeaBIOS:

8.3 The P2P Challenge

The ultimate goal of all these changes is to enable P2P DMA between GPUs. In a bare-metal system, P2P works when GPUs are on the same PCIe switch or when the CPU's internal fabric supports direct peer-to-peer transactions. In a virtualized system, P2P requires additional support from the hypervisor and IOMMU.

Even after fixing the BAR allocation problem (which subsequent messages show was accomplished with pci=realloc), P2P remained NS (Not Supported). This is because each GPU is in a separate IOMMU group on the host, and VFIO cannot enable P2P between devices in different groups. The only way to enable P2P would be to merge the IOMMU groups, which requires either ACS override (to disable PCIe access control) or changes to the hardware topology.

This is a fundamental limitation of the AMD EPYC platform: each GPU is on its own PCIe root complex, with no shared PCIe switch. The platform is designed for maximum per-GPU bandwidth (each GPU gets a dedicated x16 Gen5 link), but this topology inherently prevents P2P between GPUs in different root complexes.

9. The Aftermath: What Happened Next

9.1 The Immediate Fix: pci=realloc

In the messages immediately following message 331, the assistant correctly identified the pci=realloc solution. The user applied it (after some initial confusion about the cloud-init grub configuration file), rebooted, and all eight GPUs came back.

This was a significant victory. The Q35 + pcie=1 configuration was preserved, and with pci=realloc, the kernel could reassign the BARs that SeaBIOS had failed to allocate. The system now had:

9.2 The Persistent P2P Problem

However, P2P remained NS even after the BAR fix. The topology showed PHB (PCIe Host Bridge) for all GPU pairs, which is better than the old flat bus but still not sufficient for P2P. The GPUs are on different PCIe root ports, and without a shared PCIe switch or NVLink bridge, P2P DMA is not possible.

This led to the next phase of the investigation: trying to enable P2P by modifying the host's IOMMU configuration, including attempts to disable ACS (Access Control Services) to merge IOMMU groups. These attempts ultimately failed because the hardware topology (each GPU on its own root complex) fundamentally prevents P2P, regardless of ACS settings.

9.3 The Broader Impact

Message 331 was a turning point in the conversation. Before it, the focus was on incremental improvements to P2P performance. After it, the focus shifted to:

  1. First, recovering basic functionality (fixing the BAR allocation)
  2. Then, exploring more radical approaches to P2P (ACS disable, kernel parameters)
  3. Eventually, accepting the P2P limitation and optimizing around it The message also changed the dynamic between the user and the assistant. The user became more cautious about applying changes, and the assistant became more explicit about risks and testing procedures.

10. Lessons Learned

10.1 For System Administrators

Lesson 1: Change one thing at a time. The most important lesson from message 331 is the value of incremental change. Applying all three phases at once made it impossible to determine which change caused the BAR allocation problem. (In fact, it was likely the Q35 switch combined with SeaBIOS, but we can't be certain because we don't have test results from intermediate states.)

Lesson 2: Read the kernel's diagnostic messages. The kernel's suggestion to use pci=realloc was the single most valuable piece of information in the entire dmesg output. System administrators should always scan kernel logs for explicit diagnostic messages like this—they often point directly to the solution.

Lesson 3: Understand your firmware's limitations. SeaBIOS is a minimal firmware that works well for most configurations but can struggle with extreme setups like eight GPUs with 128 GB BARs. When working with large-BAR devices, consider using OVMF (UEFI) firmware instead.

Lesson 4: Have a rollback plan. Before making significant configuration changes, know how to revert them. The user was able to recover by adding pci=realloc, but if that hadn't worked, they would have needed to revert to i440FX.

10.2 For AI Assistants

Lesson 1: Anticipate failure modes. When recommending configuration changes, think through what could go wrong and warn the user explicitly. The assistant should have anticipated the BAR allocation problem and suggested testing with one GPU first.

Lesson 2: Be explicit about the phased approach. Don't just recommend a phased approach—explain why it's important and what could go wrong if phases are combined. The user may not understand the risks of combining changes.

Lesson 3: Provide diagnostic commands. When asking the user to provide data, include specific commands to run and explain what to look for. The assistant did this well in message 328, providing exact commands for checking IOMMU groups and PCI topology.

Lesson 4: Recognize when the user is ahead of you. The user's question about vIOMMU showed they were thinking about the next step before the current step was complete. The assistant should have gently redirected focus to the immediate problem (BAR allocation) before discussing vIOMMU.

10.3 For Hardware Planners

Lesson 1: Understand your platform's P2P capabilities. The AMD EPYC platform with one GPU per root complex is excellent for bandwidth but terrible for P2P. If your workload requires frequent cross-GPU communication, consider platforms with PCIe switches or NVLink.

Lesson 2: Virtualization adds complexity. Running GPUs in a VM adds layers of indirection (IOMMU, VFIO, QEMU) that can interfere with P2P. If P2P is critical, consider bare-metal deployment.

Lesson 3: Plan for firmware limitations. Even with the best hardware, firmware limitations can cause problems. Test your configuration with the actual firmware (SeaBIOS vs. OVMF) before deploying.

11. The Technical Details: A Reference

11.1 PCI BAR Sizes for RTX PRO 6000 Blackwell

| BAR | Size (hex) | Size (decimal) | Purpose | |-----|-----------|----------------|---------| | BAR0 | 0x4000000 | 64 MB | Control registers, doorbells | | BAR2 | 0x200000000 | 128 GB | VRAM mapping | | BAR4 | 0x2000000 | 32 MB | Additional control registers |

11.2 Bridge Window Allocation

| GPU Bus | Root Port | Bridge Window (64-bit pref) | Size | |---------|-----------|----------------------------|------| | 01:00.0 | 00:10.0 | 0x391800000000-0x393fffffffff | 160 GB | | 02:00.0 | 00:10.1 | 0x38f000000000-0x3917ffffffff | 160 GB | | 03:00.0 | 00:10.2 | 0x38c800000000-0x38efffffffff | 160 GB | | 04:00.0 | 00:10.3 | 0x38a000000000-0x38c7ffffffff | 160 GB | | 05:00.0 | 00:1c.0 | 0x387800000000-0x389fffffffff | 160 GB | | 06:00.0 | 00:1c.1 | 0x385000000000-0x3877ffffffff | 160 GB | | 07:00.0 | 00:1c.2 | 0x382800000000-0x384fffffffff | 160 GB | | 08:00.0 | 00:1c.3 | 0x380000000000-0x3827ffffffff | 160 GB |

11.3 Key dmesg Messages and Their Meanings

| Message | Meaning | |---------|---------| | BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space | The kernel's PCI allocator could not find a free address range for the 128 GB BAR2 within the bridge window. | | NVRM: This PCI I/O region assigned to your NVIDIA device is invalid: BAR2 is 0M @ 0x0 | The NVIDIA driver detected that BAR2 was not assigned (address 0), indicating the GPU cannot be used. | | nvidia: probe of 0000:01:00.0 failed with error -1 | The NVIDIA driver's probe routine failed, typically because BAR2 was not assigned. | | pci_bus 0000:00: Some PCI device resources are unassigned, try booting with pci=realloc | The kernel detected unassigned BARs and suggests using the pci=realloc parameter to trigger a reallocation pass. | | Initialized nvidia-drm ... for 0000:04:00.0 on minor 0 | The NVIDIA DRM (Direct Rendering Manager) subsystem initialized successfully for this GPU. |

11.4 Proxmox VM Configuration Parameters

| Parameter | Value in msg 331 | Meaning | |-----------|------------------|---------| | machine: q35 | Set | Use Q35 chipset (proper PCIe topology) | | hostpci0: mapping=pro6000,pcie=1 | Set | Pass through GPU with PCIe capability | | cpu: host | Set | Expose host CPU features to guest | | numa: 1 | Set | Enable NUMA topology in guest | | bios: seabios | Default | Use SeaBIOS firmware (not OVMF) | | args | Not set | No custom QEMU arguments |

12. Conclusion

Message 331 is a watershed moment in the conversation. It is the point at which the carefully laid plans for P2P optimization collide with the messy reality of firmware limitations and hardware topology. The message is a testament to the complexity of modern GPU virtualization and the importance of diagnostic data in troubleshooting.

The user's question about vIOMMU shows a mind engaged with the problem, thinking ahead to the next optimization. The dmesg output they provided is a goldmine of diagnostic information, containing the kernel's own suggestion for the fix (pci=realloc). The nvidia-smi output is a stark reminder of the bottom line: only two GPUs out of eight are working.

But the story of message 331 is not one of failure—it's one of learning. Every line of the dmesg output tells us something about how the system works. The bridge window allocations show us QEMU's PCIe topology. The BAR assignment failures reveal the limitations of SeaBIOS. The NVIDIA driver errors confirm the consequences of those failures. And the kernel's diagnostic message points the way forward.

In the messages that follow, the assistant correctly diagnoses the problem and prescribes pci=realloc. The fix works, and all eight GPUs come back. The system is restored, and the investigation into P2P continues. But the scars of message 331 remain: a newfound caution about configuration changes, a deeper understanding of firmware limitations, and a recognition that even the best-laid plans can go awry when they meet the real world.

For the reader, message 331 offers a masterclass in PCIe troubleshooting, GPU virtualization, and the art of reading kernel logs. It demonstrates the value of diagnostic data, the importance of incremental change, and the humility that comes from watching a carefully crafted plan unravel in real time. It is, in short, a perfect case study in the challenges and rewards of high-performance GPU computing in virtualized environments.

Appendix A: Complete Transcript of Message 331

[The following is the complete text of message 331, redacted for sensitive information.]

[user] Do I want vIOMMU enabled in Machine setting? Also rebooted now -> root@kpro6:~# qm config 128
boot: c
bootdisk: scsi0
ciuser: theuser
cores: 60
cpu: host
description: qm clone 9000 201 --name "new-ubuntu-vm"%0A%0Aqm resize 201 scsi0 +10G
hostpci0: mapping=pro6000,pcie=1
hostpci1: mapping=pro6000,pcie=1
hostpci2: mapping=pro6000,pcie=1
hostpci3: mapping=pro6000,pcie=1
hostpci4: mapping=pro6000,pcie=1
hostpci5: mapping=pro6000,pcie=1
hostpci6: mapping=pro6000,pcie=1
hostpci7: mapping=pro6000,pcie=1
ide2: vmstore:vm-128-cloudinit,media=cdrom,size=4M
ipconfig0: ip=dhcp
machine: q35
memory: 450000
meta: creation-qemu=9.2.0,ctime=1752337365
name: llm-one
net0: virtio=BC:24:11:52:32:42,bridge=nv
numa: 1
scsi0: local-zfs:vm-128-disk-0,size=1232384M
scsihw: virtio-scsi-pci
smbios1: uuid=681b9919-cc5c-4de5-b497-e2d60a5ac951
sockets: 2
sshkeys: ssh-ed25519%20AAAAC3NzaC1lZDI1NTE5AAAAIBPzBIU%2BLvpQQC1xc5Al914In6XiBQNERP38q2Lmnk9R%0Assh-ed25519%20AAAAC3NzaC1lZDI1NTE5AAAAIOCibmDvgUoUT73%2Ba43J72U%2BrA8Q4oTeVKiCA7OFsX9c
vmgenid: 7f4e5fe5-4ac4-42e0-823f-a7def1707176
root@kpro6:~# cat /proc/cmdline 
initrd=\EFI\proxmox\6.8.12-9-pve\initrd.img-6.8.12-9-pve root=ZFS=rpool/ROOT/pve-1 amd_iommu=on iommu=pt boot=zfs vmlinuz

[The dmesg output follows, showing the full kernel boot log from the guest VM. Key sections are analyzed in the main article.]

theuser@llm-one:~$ nvidia-smi 
Thu Feb 19 01:55:06 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 590.48.01              Driver Version: 590.48.01      CUDA Version: 13.1     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA RTX PRO 6000 Blac...    Off |   00000000:04:00.0 Off |                    0 |
| N/A   24C    P8             33W /  600W |       0MiB /  97887MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+
|   1  NVIDIA RTX PRO 6000 Blac...    Off |   00000000:08:00.0 Off |                    0 |
| N/A   25C    P8             34W /  600W |       0MiB /  97887MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+

Appendix B: Key Concepts Glossary

13. Deep Dive: The dmesg NUMA Topology and CPU Configuration

13.1 The EPYC 9335 Processor

The dmesg output in message 331 reveals detailed information about the host CPU that is passed through to the VM:

[    0.870248] smpboot: CPU0: AMD EPYC 9335 32-Core Processor (family: 0x1a, model: 0x2, stepping: 0x1)

The AMD EPYC 9335 is a server processor from AMD's Turin family (Zen 5 architecture), released in 2024. It has 32 cores and 64 threads, with a base clock of 2.95 GHz (the dmesg shows "2995.498 MHz"). The VM is configured with 60 cores and 2 sockets, which means it's using most of the host's 64 threads (leaving 4 for the host OS and Proxmox).

The processor family code 0x1a corresponds to the AMD Zen 5 microarchitecture, and model 0x2 with stepping 0x1 indicates an early production revision. This is cutting-edge hardware, and the combination of Zen 5 CPUs with Blackwell GPUs represents one of the most powerful AI inference platforms available in early 2026.

13.2 NUMA Topology

The dmesg shows a two-node NUMA topology:

[    0.003006] NODE_DATA(0) allocated [mem 0x376e7d5000-0x376e7fffff]
[    0.003017] NODE_DATA(1) allocated [mem 0x6e5cfd5000-0x6e5cffffff]

The VM has two NUMA nodes, each with 60 CPUs (matching the sockets: 2 configuration). The memory is split between the nodes:

[    0.003423] Initmem setup node 0 [mem 0x0000000000001000-0x000000376e7fffff]
[    0.003426] Initmem setup node 1 [mem 0x000000376e800000-0x0000006e5cffffff]

Node 0 has approximately 222 GB of RAM (from 0x1000 to 0x376e7fffff), and Node 1 has approximately 222 GB (from 0x376e800000 to 0x6e5cffffff). The total of 444 GB is close to the configured 450 GB (the difference is reserved for the kernel and firmware).

The NUMA configuration is critical for GPU performance. Each GPU is physically connected to one of the two CPU sockets via PCIe lanes. If a GPU is on socket 0 and its memory is allocated from socket 1's RAM, every DMA transfer must cross the Infinity Fabric interconnect between sockets, adding latency. The numa: 1 setting in the VM config tells QEMU to expose this NUMA topology to the guest, allowing the NVIDIA driver and CUDA runtime to optimize memory allocations.

However, the dmesg also shows a concerning message:

[    1.018644] pci_bus 0000:00: Unknown NUMA node; performance will be reduced

This message appears for the root PCI bus, indicating that QEMU did not associate the PCI bus with a specific NUMA node. This can happen when the PCI topology is not properly mapped to the NUMA topology in the VM configuration. The consequence is that the kernel may not optimally map PCIe interrupts and DMA to the correct NUMA node, potentially adding latency to GPU-CPU communication.

13.3 The 120-CPU Configuration

The VM is configured with 60 cores and 2 sockets, for a total of 120 CPUs (threads). The dmesg shows:

[    0.298459] smpboot: Allowing 120 CPUs, 0 hotplug CPUs

And the CPU enumeration shows all 120 CPUs being brought online across two NUMA nodes:

[    0.874543] .... node  #0, CPUs:          #1   #2   #3   #4   #5   #6   #7   #8   #9  #10  #11  #12  #13  #14  #15  #16  #17  #18  #19  #20  #21  #22  #23  #24  #25  #26  #27  #28  #29  #30  #31  #32  #33  #34  #35  #36  #37  #38  #39  #40  #41  #42  #43  #44  #45  #46  #47  #48  #49  #50  #51  #52  #53  #54  #55  #56  #57  #58  #59
[    0.884784] .... node  #1, CPUs:    #60  #61  #62  #63  #64  #65  #66  #67  #68  #69  #70  #71  #72  #73  #74  #75  #76  #77  #78  #79  #80  #81  #82  #83  #84  #85  #86  #87  #88  #89  #90  #91  #92  #93  #94  #95  #96  #97  #98  #99 #100 #101 #102 #103 #104 #105 #106 #107 #108 #109 #110 #111 #112 #113 #114 #115 #116 #117 #118 #119

Node 0 has CPUs 0-59 (60 threads), and Node 1 has CPUs 60-119 (60 threads). This 60/60 split is important for GPU affinity: half the GPUs should be associated with each NUMA node for optimal performance. In the subsequent messages, we see that the GPUs are indeed split across the two PCIe root complexes, which correspond to the two CPU sockets.

13.4 KVM Paravirtualization Features

The dmesg shows several KVM paravirtualization features being enabled:

[    0.298502] kvm-guest: KVM setup pv remote TLB flush
[    0.298504] kvm-guest: setup PV sched yield
[    0.302219] kvm-guest: PV spinlocks enabled
[    0.820552] kvm-guest: APIC: send_IPI_mask() replaced with kvm_send_ipi_mask()

These features optimize the guest's interaction with the KVM hypervisor:

14. The PCIe Topology in Detail

14.1 The Q35 Chipset Architecture

The Q35 chipset emulated by QEMU provides a more realistic PCIe topology than the legacy i440FX. The dmesg reveals the specific PCIe hierarchy:

[    1.016252] ACPI: PCI Root Bridge [PCI0] (domain 0000 [bus 00-ff])

This is the root PCI bus, which is the top of the PCIe hierarchy. Under it, QEMU creates multiple PCIe root ports:

pci 0000:00:10.0: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:10.1: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:10.2: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:10.3: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:1c.0: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:1c.1: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:1c.2: [1b36:000c] type 01 class 0x060400 PCIe Root Port
pci 0000:00:1c.3: [1b36:000c] type 01 class 0x060400 PCIe Root Port

The vendor ID 1b36 is QEMU's PCI vendor ID, and device ID 000c is the PCIe Root Port device. The class code 0x060400 indicates a PCI-to-PCI bridge (which is how PCIe root ports are enumerated). Each root port creates a new PCI bus segment:

pci 0000:01:00.0: [10de:2bb5] type 00 class 0x030200 PCIe Legacy Endpoint
pci 0000:02:00.0: [10de:2bb5] type 00 class 0x030200 PCIe Legacy Endpoint
...

The NVIDIA vendor ID is 10de, and device ID 2bb5 corresponds to the RTX PRO 6000 Blackwell. The class code 0x030200 indicates a "3D controller" (as opposed to a "VGA compatible controller" with class code 0x030000). This is because the GPUs are passed through without VGA emulation, making them pure compute devices.

14.2 The Two PCIe Complexes

The Q35 chipset has two separate PCIe root complexes:

14.3 The Legacy PCI Bridge

In addition to the eight PCIe root ports, the Q35 chipset also includes a legacy PCI bridge:

pci 0000:00:1e.0: [8086:244e] type 01 class 0x060401 conventional PCI bridge

This bridge (Intel vendor ID 8086, device ID 244e) provides connectivity for legacy PCI devices that are not PCIe-native. In this configuration, it handles the VirtIO devices (network, SCSI, etc.):

pci 0000:0a:03.0: [1af4:1002] type 00 class 0x00ff00 conventional PCI endpoint
pci 0000:0a:05.0: [1af4:1004] type 00 class 0x010000 conventional PCI endpoint
pci 0000:0a:12.0: [1af4:1000] type 00 class 0x020000 conventional PCI endpoint

These are the VirtIO console, SCSI, and network devices, respectively. They are on bus 0a (behind the legacy PCI bridge), separate from the GPU buses. This separation is important because it means the GPUs have dedicated PCIe root ports without sharing bandwidth with other devices.

15. The BAR Allocation Algorithm: A Deeper Analysis

15.1 How PCI Resource Allocation Works

When the system boots, the PCI resource allocation proceeds in several stages:

  1. Firmware enumeration: The BIOS (SeaBIOS) enumerates all PCIe devices, reads their BAR size requirements, and attempts to assign addresses. This is a depth-first traversal of the PCIe tree.
  2. Bridge window allocation: For each PCIe root port (or PCI-to-PCI bridge), the firmware allocates a memory window that encompasses all devices behind that bridge. The window must be large enough for the sum of all device BARs, plus alignment padding.
  3. Device BAR assignment: Within each bridge window, the firmware assigns individual BARs to devices. Each BAR must be naturally aligned (base address must be a multiple of BAR size).
  4. Kernel reallocation: After the firmware's initial assignment, the Linux kernel can perform a reallocation pass if pci=realloc is specified. This pass can move bridge windows and reassign BARs to resolve conflicts. The failure in message 331 occurs at step 3: the firmware successfully allocates bridge windows (step 2), but cannot assign individual BARs within those windows (step 3).

15.2 The Alignment Constraint

The natural alignment requirement is the key constraint that causes the failure. For a 128 GB BAR, the base address must be a multiple of 128 GB (0x2000000000 in hex). This means the BAR can only be placed at addresses like:

15.3 Why the Specific Pattern of Failures

Let me reconstruct the likely allocation sequence:

North complex (buses 01-04):

  1. Bridge window for bus 01: 0x391800000000-0x393fffffffff (160 GB)
  2. BAR2 for GPU at 01:00.0: needs 128 GB at a 128 GB-aligned address within this window - Possible base: 0x391800000000 (128 GB aligned? 0x391800000000 / 0x2000000000 = 0x1C8C, not an integer → not aligned) - Next aligned: 0x392000000000 (within window? 0x392000000000 < 0x393fffffffff → yes) - But wait—the BAR at 0x392000000000 would extend to 0x393fffffffff, which is the end of the window - This should work, but the dmesg says it failed - The issue might be that BAR0 (64 MB) and BAR4 (32 MB) also need to be allocated, and their placement creates fragmentation
  3. The same pattern repeats for buses 02, 03, and 04 Why bus 04 succeeds: Bus 04's bridge window is 0x38a000000000-0x38c7ffffffff. The BAR2 for GPU at 04:00.0 needs a 128 GB-aligned base within this window. The base 0x38a000000000 is 128 GB-aligned (0x38a000000000 / 0x2000000000 = 0x1C50, an integer). The BAR extends from 0x38a000000000 to 0x38bfffffffff, which is within the window. But why would this work for bus 04 but not for buses 01-03? The difference might be that buses 01-03 have their BARs allocated in a way that fragments the space, leaving no 128 GB-aligned slot for bus 04's BAR2. However, since the allocation is typically done depth-first (bus 01 first, then bus 02, etc.), bus 04 should have the most constrained space, not the least. An alternative explanation is that the firmware allocates BARs in a different order—perhaps it allocates all BAR0s first, then all BAR2s, then all BAR4s. In that case, the BAR0s (64 MB each) consume negligible space, and the BAR2s are allocated in order. The first few BAR2s might be placed at non-optimal positions due to alignment constraints, consuming more space than expected and leaving insufficient room for later BAR2s. The exact reason why buses 04 and 08 succeed while others fail is difficult to determine without tracing the firmware's allocation algorithm. But the key insight is that the problem is in the firmware, not the hardware, and the kernel's pci=realloc can fix it.

15.4 The Role of PCIe Max Payload Size

An interesting detail in the dmesg is the Max Payload Size (MPS) negotiation:

[    1.130694] pci 0000:01:00.0: Max Payload Size set to 128 (was 256, max 256)

This message appears for all eight GPUs. The GPU supports a Max Payload Size of 256 bytes (the standard for PCIe Gen5), but the root port has set it to 128 bytes. This is because QEMU's PCIe root port implementation defaults to 128 bytes MPS. While this doesn't affect BAR allocation, it does impact PCIe bandwidth efficiency: larger payload sizes reduce the overhead of packet headers and improve throughput.

The dmesg also shows the available bandwidth:

[    1.131754] pci 0000:01:00.0: 252.048 Gb/s available PCIe bandwidth, limited by 16.0 GT/s PCIe x16 link at 0000:00:10.0 (capable of 504.112 Gb/s with 32.0 GT/s PCIe x16 link)

This confirms that the GPUs are connected via PCIe Gen5 x16 links (16 GT/s per lane, 16 lanes = 256 GT/s raw, ~252 Gb/s effective after encoding overhead). The GPU is capable of Gen5 x16 at 32 GT/s (the full Blackwell specification), but the link is limited to 16 GT/s by the root port. This is expected for QEMU's virtual PCIe implementation, which doesn't support the higher Gen5 signaling rates.

16. The NVIDIA Driver Initialization Sequence

16.1 Driver Loading

The dmesg shows the NVIDIA driver loading sequence:

[   16.466573] nvidia: loading out-of-tree module taints kernel.
[   16.466584] nvidia: module verification failed: signature and/or required key missing - tainting kernel

The NVIDIA driver is an out-of-tree module (not part of the mainline Linux kernel), so loading it "taints" the kernel. This is a cosmetic warning that doesn't affect functionality. The "module verification failed" message indicates that the driver is not signed with a kernel-compatible signature, which is expected for the NVIDIA open kernel module.

16.2 The nvlink Module

[   16.520975] nvidia-nvlink: Nvlink Core is being initialized, major device number 238

The nvlink module is loaded, which provides support for NVIDIA's NVLink interconnect. However, the RTX PRO 6000 Blackwell does not have NVLink bridges (unlike the A100/H100 which use NVLink for GPU-to-GPU communication). The nvlink module is loaded but unused.

16.3 The BAR2 Validation Failure

The critical failure sequence for each GPU is:

[   16.520988] NVRM: This PCI I/O region assigned to your NVIDIA device is invalid:
               NVRM: BAR2 is 0M @ 0x0 (PCI:0000:01:00.0)
[   16.524863] nvidia: probe of 0000:01:00.0 failed with error -1

The NVIDIA driver reads BAR2 from the GPU's PCI configuration space and checks whether it has been assigned a valid address. When BAR2 is 0 (meaning no address was assigned), the driver refuses to initialize the GPU. This is a safety check: if the driver tried to use a GPU with no VRAM mapping, it would cause system crashes or memory corruption.

The error message "BAR2 is 0M @ 0x0" is slightly misleading: it says "0M" (zero megabytes) because the BAR size register reads as 0 when no address is assigned. The actual BAR size (128 GB) is encoded in the BAR's read-only bits, but the driver reports the size as 0 because the address portion is 0.

16.4 The Successful Initializations

For the two GPUs that succeed:

[   23.315020] [drm] Initialized nvidia-drm 0.0.0 20160202 for 0000:04:00.0 on minor 0
[   23.315069] nvidia 0000:04:00.0: [drm] No compatible format found
[   23.315072] nvidia 0000:04:00.0: [drm] Cannot find any crtc or sizes

The DRM (Direct Rendering Manager) subsystem initializes, but it reports "No compatible format found" and "Cannot find any crtc or sizes." These messages are expected for compute-only GPUs that don't have a display output. The DRM subsystem is looking for display modes, but since the GPU is passed through without VGA emulation, there are no displays attached.

16.5 The LTR Warning

[   22.998566] NVRM: GPU0 kbifInitLtr_GB202: LTR is disabled in the hierarchy

LTR (Latency Tolerance Reporting) is a PCIe feature that allows devices to report their latency tolerance to the system, enabling power management optimizations. The message indicates that LTR is disabled in the PCIe hierarchy, which is expected for QEMU's virtual PCIe implementation. This doesn't affect functionality but may impact power efficiency.

17. The Broader Narrative: From P2P Dreams to Harsh Reality

17.1 The Arc of the Conversation

Message 331 sits at a critical point in the conversation's narrative arc. To understand its significance, we need to trace the arc from the beginning of the P2P investigation through to the eventual resolution.

Act 1: Discovery (Messages 321-330) The assistant identifies that P2P is disabled in the VM and proposes a three-phase plan to enable it. The investigation of the Proxmox host reveals that IOMMU is active but not in passthrough mode, the VM uses the legacy i440FX chipset, and the GPUs are not presented as PCIe devices. The plan seems straightforward and promising.

Act 2: Crisis (Message 331) The user applies all changes at once and reboots. The system comes back with only two GPUs. The P2P optimization plan has backfired, and basic functionality is compromised. This is the crisis point of the narrative.

Act 3: Recovery (Messages 332-362) The assistant diagnoses the BAR allocation problem and prescribes pci=realloc. After some initial confusion about the cloud-init grub configuration, the fix is applied and all eight GPUs return. The system is restored, but P2P remains NS.

Act 4: Acceptance (Messages 363+) The team explores more aggressive approaches to enable P2P, including ACS disable on the host and kernel parameter modifications. These attempts ultimately fail because the hardware topology (each GPU on its own PCIe root complex) fundamentally prevents P2P. The team accepts the limitation and optimizes around it.

17.2 The Emotional Trajectory

Message 331 is the low point of the emotional trajectory. Before it, there is optimism and confidence: the problem is understood, the solution is planned, and the path forward is clear. After it, there is confusion and concern: the changes have made things worse, and the root cause is not immediately obvious.

The user's question about vIOMMU reveals this confusion. They are casting about for explanations, wondering if there's a setting they missed. The assistant's response in message 332 must balance reassurance ("we can fix this") with honesty ("the BAR allocation failed") and direction ("add pci=realloc").

17.3 The Turning Point

The turning point in the narrative is not message 331 itself, but the assistant's recognition of the pci=realloc suggestion in the dmesg output. This transforms the crisis into a learning opportunity: the system itself told us what was wrong, and now we know how to fix it.

This is a powerful narrative moment because it validates the diagnostic approach. The dmesg output, which initially seemed like a sea of confusing messages, contained the key to the solution. The assistant's ability to extract that signal from the noise is what saves the day.

18. The Hardware Platform: ASUS ESC8000A-E13

18.1 Server Architecture

From the context of the conversation, we know that the Proxmox host is running on an ASUS ESC8000A-E13 server motherboard. This is a dual-socket EPYC 9005 series platform designed for GPU-intensive workloads. Key features include:

18.2 The EPYC 9335 I/O Die

The AMD EPYC 9335 uses a chiplet architecture with multiple I/O dies (IODs) connected via Infinity Fabric. Each IOD provides a set of PCIe root complexes. The eight GPUs are distributed across the available root complexes, with each GPU on its own complex.

The key characteristic of this architecture is that P2P DMA between GPUs on different root complexes must traverse the Infinity Fabric interconnect between IODs. While Infinity Fabric has high bandwidth (up to 256 GB/s per link), it adds latency compared to a direct P2P connection through a PCIe switch.

In a virtualized environment, the situation is worse: the VFIO/IOMMU layer adds additional translation overhead for cross-GPU transfers. The combination of Infinity Fabric latency and IOMMU translation overhead results in the ~14 µs per transfer that the assistant measured earlier in the conversation.

18.3 Why No PCIe Switch?

Server motherboards for GPU workloads typically come in two configurations:

  1. Direct-attach: Each GPU is connected directly to a CPU root complex. This is the ESC8000A-E13 design. It maximizes per-GPU bandwidth and is simpler/cheaper to implement.
  2. Switch-attach: GPUs are connected through PCIe switches, which can aggregate multiple GPUs under a single root complex. This enables P2P DMA between GPUs on the same switch. NVIDIA's DGX platforms use this approach with NVSwitch. The direct-attach design is more common for general-purpose GPU servers because it's more flexible and cost-effective. The switch-attach design is used for specialized AI platforms where P2P performance is critical. For this deployment, the direct-attach design is a fundamental constraint. No amount of software configuration can create a P2P path between GPUs on different root complexes in a VM, because the VFIO/IOMMU layer enforces isolation between IOMMU groups.

19. The Virtualization Overhead Theme

19.1 Layers of Abstraction

The P2P problem in this deployment is a classic example of virtualization overhead. Each layer of abstraction adds latency and constraints:

  1. Physical layer: GPUs on separate PCIe root complexes, connected via Infinity Fabric
  2. IOMMU layer: AMD-Vi IOMMU translates DMA addresses, adding latency to every transfer
  3. VFIO layer: The VFIO framework manages device assignment and enforces isolation between IOMMU groups
  4. QEMU layer: The hypervisor emulates the PCIe topology and manages device passthrough
  5. Guest kernel layer: The guest OS manages PCI resources and device drivers
  6. NVIDIA driver layer: The driver initializes GPUs and manages memory At each layer, there are potential bottlenecks and constraints. The BAR allocation problem in message 331 is a failure at layer 5 (guest kernel) caused by limitations at layer 4 (QEMU firmware). The P2P limitation is a failure at layer 2 (IOMMU) caused by the physical topology at layer 1.

19.2 The Cost of Isolation

Virtualization provides isolation between VMs, which is essential for multi-tenant environments. But this isolation comes at a cost: devices in different IOMMU groups cannot communicate directly. Every cross-GPU transfer must go through system memory, where it can be monitored and controlled by the hypervisor.

For workloads that require frequent cross-GPU communication (like tensor-parallel LLM inference), this isolation overhead can be crippling. The ~14 µs per transfer measured earlier in the conversation is the cumulative cost of:

19.3 The Tradeoff

The fundamental tradeoff in this deployment is between isolation and performance. Proxmox provides robust isolation between VMs, which is valuable for multi-tenant environments. But for a single-tenant, high-performance AI workload, this isolation is pure overhead.

The team's decision to run the workload in a VM rather than on bare metal is likely driven by operational considerations: Proxmox provides backup, snapshot, migration, and management capabilities that are valuable for production deployments. But these benefits come at the cost of P2P performance.

20. The Tooling: Proxmox, QEMU, and the Linux PCI Subsystem

20.1 Proxmox VE Configuration

Proxmox VE provides a web interface and command-line tools for managing VMs. The qm command is used for QEMU/KVM VM management. In this conversation, we see several Proxmox-specific features:

20.2 QEMU's PCIe Implementation

QEMU's PCIe implementation is a software emulation of the PCIe specification. Key aspects relevant to this conversation:

20.3 The Linux PCI Subsystem

The Linux kernel's PCI subsystem is responsible for managing PCIe devices, including:

21. Expanded Lessons Learned

21.1 For Proxmox Administrators

Lesson: Understand the implications of machine type changes. Switching from i440FX to Q35 changes the PCI topology fundamentally. While Q35 is generally better for GPU passthrough, it can expose BAR allocation issues that were hidden by the i440FX's simpler topology.

Recommendation: When switching to Q35 for GPU passthrough, be prepared to also switch to OVMF firmware and add pci=realloc to the guest kernel. Test with a single GPU first, then scale up.

21.2 For GPU Workload Engineers

Lesson: Know your GPU's BAR sizes. The RTX PRO 6000 Blackwell has a 128 GB BAR2. This is unusually large and can cause allocation problems in virtualized environments. Check the BAR sizes of your GPUs before designing the virtualization configuration.

Recommendation: Use lspci -vvv to examine BAR sizes. For GPUs with large BARs, prefer OVMF firmware and ensure the 64-bit MMIO window is large enough.

21.3 For AI Infrastructure Planners

Lesson: P2P in VMs is hard. Enabling P2P DMA between GPUs in a virtualized environment requires specific hardware support (shared PCIe switch or NVLink), specific hypervisor configuration (merged IOMMU groups), and specific guest configuration (proper PCIe topology). It is not always possible.

Recommendation: If your workload requires P2P, test it early in the deployment process. Don't assume it will work just because the GPUs are passed through. If P2P is critical, consider bare-metal deployment or platforms with NVLink.

21.4 For Debugging Complex Systems

Lesson: The kernel tells you what's wrong. The Linux kernel's diagnostic messages are often the fastest path to a solution. In message 331, the kernel explicitly suggested pci=realloc. Always scan kernel logs for such messages.

Recommendation: When troubleshooting PCIe issues, use dmesg | grep -iE &#39;pci|bar|nvidia|error|fail|can.t&#39; to find relevant messages. Look for explicit suggestions from the kernel.

22. Conclusion: The Enduring Value of Message 331

Message 331 is more than just a diagnostic data dump—it is a case study in the complexity of modern GPU virtualization. It demonstrates how a well-intentioned optimization can go wrong, how the kernel's diagnostic messages point the way to a solution, and how the hardware topology ultimately constrains what software can achieve.

The message is also a testament to the value of thorough data collection. The user provided a complete dmesg output, a VM configuration, a host kernel command line, and an nvidia-smi output. This comprehensive data enabled the assistant to diagnose the problem accurately and prescribe the correct fix. Without this data, the team might have spent hours or days chasing wrong hypotheses.

For the reader, message 331 offers several enduring lessons:

  1. Change one thing at a time. The most important lesson in system administration is also the most frequently violated. Incremental changes with testing at each step would have revealed the BAR allocation problem immediately and made it trivially fixable.
  2. Read the kernel's output. The Linux kernel is remarkably good at diagnosing its own problems. When it says "try booting with pci=realloc," listen to it.
  3. Understand your firmware. SeaBIOS is adequate for most configurations, but extreme setups require OVMF. Know the limitations of your tools.
  4. Accept hardware constraints. Not all problems can be solved with software. The P2P limitation in this deployment is a hardware constraint that no amount of configuration can overcome.
  5. Document everything. The comprehensive data in message 331 is a model for how to report system problems. Every line of the dmesg output tells a story, and having the complete story is essential for accurate diagnosis. In the end, message 331 is a story of recovery from self-inflicted wounds. The team made changes that broke the system, but they had the diagnostic tools and knowledge to fix it. The system came back stronger than before, with proper PCIe topology and IOMMU passthrough enabled. And the team learned valuable lessons about the limits of virtualization for GPU workloads. This is the essence of systems engineering: not avoiding failures, but recovering from them quickly and learning from them deeply.---

23. Extended Analysis: The dmesg Line by Line

23.1 The Boot Process in Detail

The dmesg output in message 331 contains approximately 1,500 lines of kernel boot messages. While we've analyzed the key sections, there are many more details worth examining. Let me walk through the boot process in chronological order, highlighting the most significant messages.

Early boot (seconds 0-1):

[    0.000000] Linux version 6.8.0-100-generic (buildd@lcy02-amd64-061) (x86_64-linux-gnu-gcc-13 (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0, GNU ld (GNU Binutils for Ubuntu) 2.42) #100-Ubuntu SMP PREEMPT_DYNAMIC Tue Jan 13 16:40:06 UTC 2026 (Ubuntu 6.8.0-100.100-generic 6.8.12)

The kernel is Ubuntu's 6.8.0-100-generic, built with GCC 13.3.0 on January 13, 2026. This is a relatively recent kernel build, compiled just over a month before the conversation (February 19, 2026). The kernel version 6.8.12 is the upstream base, with Ubuntu's -100-generic patch set applied.

[    0.000000] Command line: BOOT_IMAGE=/vmlinuz-6.8.0-100-generic root=UUID=e4cd6da8-09cb-4378-9577-e2053726667f ro console=tty1 console=ttyS0

The kernel command line is short and clean. Notably, pci=realloc is NOT present at this point—it will be added in the next reboot after the assistant diagnoses the problem. The console=tty1 console=ttyS0 parameters enable both the physical console and the serial console, which is standard for server VMs.

[    0.000000] DMI: QEMU Standard PC (Q35 + ICH9, 2009), BIOS rel-1.16.3-0-ga6ed6b701f0a-prebuilt.qemu.org 04/01/2014

This confirms the Q35 chipset and SeaBIOS 1.16.3. The BIOS date is April 1, 2014, which is the build date of the SeaBIOS binary, not the actual release date of the code. SeaBIOS 1.16.3 was actually released in 2023, but the binary retains its original build timestamp.

[    0.000000] Hypervisor detected: KVM

The kernel detects it's running under KVM virtualization. This triggers the paravirtualization optimizations we discussed earlier.

Memory initialization (seconds 0-1):

[    0.719816] Memory: 453399380K/460799428K available (22528K kernel code, 4439K rwdata, 14400K rodata, 4920K init, 4788K bss, 7399844K reserved, 0K cma-reserved)

The VM has approximately 453 GB of available RAM out of 460 GB total. The difference (about 7 GB) is reserved for the kernel, firmware, and other system uses. The 450 GB configured in the VM is confirmed to be available.

CPU initialization (seconds 0-1):

[    0.822545] tsc: Marking TSC unstable due to TSCs unsynchronized

The Time Stamp Counter (TSC) is marked as unstable because the virtual CPUs may not have synchronized TSCs. This is expected in a VM environment and doesn't cause problems for most workloads. The kernel will use a different clocksource (kvm-clock) for timekeeping.

PCI enumeration (seconds 1-13):

The PCI enumeration takes approximately 12 seconds, which is unusually long. This is because the kernel is probing all eight GPUs and their BARs, and the BAR allocation failures cause retries and fallback paths that consume time.

[    1.371544] PCI: pci_cache_line_size set to 64 bytes
[    1.371565] pci 0000:01:00.0: BAR 2 [mem 0x390000000000-0x391fffffffff 64bit pref]: can't claim; no compatible bridge window

The first BAR failure occurs at 1.37 seconds into boot. The GPU at 01:00.0 (the first GPU) cannot claim its BAR2 because there's "no compatible bridge window." This is the beginning of the cascade of failures.

The phrase "can't claim" is different from "can't assign." The kernel's PCI subsystem first tries to "claim" BARs that the firmware has already assigned. If the firmware didn't assign a BAR (because SeaBIOS couldn't allocate it), the kernel's claim attempt fails, and the kernel then tries to "assign" the BAR itself. If that also fails, we get the "can't assign; no space" message.

[    1.372054] pci 0000:02:00.0: BAR 2 [mem 0x38e000000000-0x38ffffffffff 64bit pref]: can't claim; no compatible bridge window
[    1.372604] pci 0000:03:00.0: BAR 2 [mem 0x38c000000000-0x38dfffffffff 64bit pref]: can't claim; no compatible bridge window
[    1.373067] pci 0000:05:00.0: BAR 2 [mem 0x386000000000-0x387fffffffff 64bit pref]: can't claim; no compatible bridge window
[    1.373622] pci 0000:06:00.0: BAR 2 [mem 0x384000000000-0x385fffffffff 64bit pref]: can't claim; no compatible bridge window
[    1.374039] pci 0000:07:00.0: BAR 2 [mem 0x382000000000-0x383fffffffff 64bit pref]: can't claim; no compatible bridge window

Six GPUs fail to claim their BAR2. Note that GPUs at 04:00.0 and 08:00.0 are NOT in this list—they successfully claimed their BARs.

The bridge windows referenced in these messages (e.g., 0x390000000000-0x391fffffffff) are the firmware's attempted assignments, not the actual bridge windows we saw earlier. The firmware tried to assign these addresses, but they don't match the bridge windows that QEMU allocated.

Resource reallocation (seconds 1-13):

After the initial claim failures, the kernel attempts to reassign resources:

[    1.406847] pci 0000:00:10.0: bridge window [io  0x1000-0x0fff] to [bus 01] add_size 1000
[    1.407270] pci 0000:00:10.1: bridge window [io  0x1000-0x0fff] to [bus 02] add_size 1000
...

The kernel is trying to add I/O space to the bridge windows. Each bridge requests an additional 4 KB of I/O space (add_size 1000 in hex = 4096 bytes). This is the kernel's attempt to make the firmware's allocation work by expanding the windows.

[    1.410230] pci 0000:00:10.0: bridge window [io  0x6000-0x6fff]: assigned
[    1.410566] pci 0000:00:10.1: bridge window [io  0x7000-0x7fff]: assigned
...

The I/O space is successfully assigned to each bridge. But this doesn't fix the BAR2 problem because BAR2 uses memory space, not I/O space.

The critical BAR assignment failures (seconds 1-13):

[    1.412928] pci 0000:01:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
[    1.413368] pci 0000:01:00.0: BAR 2 [mem 0x390000000000-0x391fffffffff 64bit pref]: failed to assign

After the I/O space reassignment, the kernel tries to assign BAR2 for each GPU. For GPU at 01:00.0, it first tries to find a free space of 128 GB within the bridge window. When that fails ("can't assign; no space"), it tries the firmware's original assignment (0x390000000000-0x391fffffffff), which also fails because it doesn't fit in the bridge window.

This pattern repeats for each failing GPU:

[    1.938077] pci 0000:02:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
[    2.956799] pci 0000:03:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
[    4.529794] pci 0000:04:00.0: ... (no BAR2 error)
[    6.587398] pci 0000:05:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
[    7.310458] pci 0000:06:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space
[    9.084342] pci 0000:07:00.0: BAR 2 [mem size 0x2000000000 64bit pref]: can't assign; no space

Note the timestamps: each failure takes about 1-2 seconds, which is the time the kernel spends trying different allocation strategies before giving up. The total time from first failure to last is about 8 seconds.

The kernel's suggestion (second 12.79):

[   12.789458] pci_bus 0000:00: Some PCI device resources are unassigned, try booting with pci=realloc

This message appears at 12.79 seconds, after all BAR allocation attempts have completed. The kernel has detected that some devices have unassigned resources and explicitly suggests the fix. This is a remarkable diagnostic feature of the Linux kernel—it not only detects the problem but tells you how to fix it.

NVIDIA driver loading (seconds 16-23):

[   16.466573] nvidia: loading out-of-tree module taints kernel.
[   16.520988] NVRM: This PCI I/O region assigned to your NVIDIA device is invalid:
               NVRM: BAR2 is 0M @ 0x0 (PCI:0000:01:00.0)
[   16.524863] nvidia: probe of 0000:01:00.0 failed with error -1

The NVIDIA driver loads at 16.47 seconds and immediately detects the BAR2 problem for the first GPU. The driver's probe routine fails with error -1 (a generic error code), and the GPU is marked as unavailable.

[   21.787332] NVRM: The NVIDIA probe routine failed for 6 device(s).
[   21.787338] NVRM: loading NVIDIA UNIX Open Kernel Module for x86_64  590.48.01

At 21.79 seconds, the NVIDIA driver reports that 6 devices failed probe. It then continues to load the kernel module (the base driver infrastructure) even though most GPUs are unavailable. The two successful GPUs are initialized shortly after:

[   23.315020] [drm] Initialized nvidia-drm 0.0.0 20160202 for 0000:04:00.0 on minor 0
[   24.601630] [drm] Initialized nvidia-drm 0.0.0 20160202 for 0000:08:00.0 on minor 1

The DRM subsystem initializes for GPU 0 (bus 04:00.0) at 23.32 seconds and GPU 1 (bus 08:00.0) at 24.60 seconds. The 1.3-second gap between the two initializations is likely due to driver initialization overhead (firmware loading, memory allocation, etc.).

23.2 What the dmesg Doesn't Show

While the dmesg is comprehensive, there are some things it doesn't tell us:

  1. The exact SeaBIOS allocation algorithm: We can see the results of SeaBIOS's allocation (the bridge windows and the failed BAR assignments), but we can't see the algorithm itself. We don't know why SeaBIOS chose specific addresses for the bridge windows or why it couldn't allocate BAR2 for six GPUs.
  2. The QEMU MMIO window size negotiation: QEMU and SeaBIOS negotiate the size of the 64-bit MMIO window through the FWCfg interface. The dmesg shows the resulting window (0x380000000000-0x395fffffffff), but not the negotiation process.
  3. The exact GPU BAR requirements: While we know BAR2 is 128 GB, we don't have the exact BAR0 and BAR4 sizes from the dmesg. We can infer them from the bridge window sizes, but direct confirmation would require lspci -vvv output.
  4. The P2P topology: The dmesg doesn't show P2P information. We need nvidia-smi topo -p2p and nvidia-smi topo -m for that, which were provided in subsequent messages.

24. The Comparative Analysis: i440FX vs. Q35

24.1 Why i440FX Worked

Before the changes in message 331, the VM was using the i440FX chipset. In that configuration, all eight GPUs were detected and working (though P2P was NS). Why did i440FX work when Q35 failed?

The i440FX chipset is a legacy PCI chipset that doesn't support PCIe natively. In QEMU's implementation, i440FX presents all devices on a flat PCI bus, with PCI-to-PCI bridges used to connect multiple devices. The key difference is in how BAR allocation works:

i440FX approach:

24.2 The Address Space Accounting

Let me do the math for both configurations:

i440FX (all GPUs on flat bus):

24.3 The Tradeoff

The i440FX configuration works but provides a flat PCI topology that may prevent the NVIDIA driver from using PCIe-native features. The Q35 configuration provides proper PCIe topology but exposes BAR allocation issues.

The tradeoff is clear:

25. The Firmware Factor: SeaBIOS vs. OVMF

25.1 SeaBIOS Limitations

SeaBIOS is the default firmware for QEMU VMs. It is a minimal, open-source BIOS implementation that provides basic x86 firmware services. Its PCI resource allocation is functional but not sophisticated.

Key limitations of SeaBIOS for large-BAR GPU configurations:

  1. Simple allocation algorithm: SeaBIOS uses a first-fit or best-fit algorithm for BAR allocation, which may not handle complex alignment constraints optimally.
  2. Limited bridge window management: SeaBIOS allocates bridge windows based on the sum of BAR sizes behind each bridge, but it may not account for alignment padding correctly.
  3. No UEFI support: SeaBIOS is a legacy BIOS, so it can't use UEFI features like the PCI Express Capability Structure for advanced BAR management.
  4. No ACPI _DSM methods: SeaBIOS doesn't implement ACPI _DSM (Device Specific Method) for PCI resource allocation, which some firmware implementations use to optimize BAR placement.
  5. Fixed MMIO window: SeaBIOS uses a fixed heuristic for sizing the 64-bit MMIO window, based on the host-phys-bits CPU property. This may not produce the optimal window size for extreme configurations.

25.2 OVMF Advantages

OVMF (Open Virtual Machine Firmware) is a UEFI firmware implementation for QEMU VMs. It is based on TianoCore EDK II, the open-source UEFI reference implementation.

Key advantages of OVMF for large-BAR GPU configurations:

  1. Better PCI resource allocation: OVMF uses a more sophisticated algorithm for BAR allocation, based on the UEFI PCI Bus Driver. It can handle complex alignment constraints more effectively.
  2. Dynamic MMIO window sizing: OVMF can dynamically adjust the 64-bit MMIO window size based on the actual BAR requirements of the devices, rather than using a fixed heuristic.
  3. ACPI _DSM support: OVMF implements ACPI _DSM methods for PCI resource allocation, enabling more efficient BAR placement.
  4. UEFI driver model: OVMF supports UEFI drivers for PCIe devices, which can provide additional configuration options.
  5. Large BAR support: OVMF has been tested with large-BAR GPUs (including NVIDIA's A100 and H100) and has proven to handle them reliably.

25.3 The Migration Path

Switching from SeaBIOS to OVMF requires several steps:

  1. Create an EFI disk: qm set 128 -efidisk0 local-zfs:1,efitype=4m,pre-enrolled-keys=0,size=128K
  2. Change the BIOS type: qm set 128 -bios ovmf
  3. Convert the boot disk: If the VM was installed with SeaBIOS/MBR, the boot disk must be converted from MBR to GPT. This can be done with sgdisk or gdisk tools.
  4. Set the MMIO aperture: qm set 128 -args &#39;-fw_cfg name=opt/ovmf/X-PciMmio64Mb,string=1572864&#39; (1.5 TB) The user mentioned that OVMF "previously didn't boot." This was likely because OVMF was tried with the i440FX chipset, which doesn't support UEFI boot. With Q35, OVMF should work.

26. The GPU Topology: PHB and What It Means

26.1 Understanding PHB

In the subsequent messages (after message 331), the assistant runs nvidia-smi topo -m and gets:

GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0  X   PHB  PHB  PHB  PHB  PHB  PHB  PHB  0-119      0-1         N/A
GPU1  PHB  X   PHB  PHB  PHB  PHB  PHB  PHB  0-119      0-1         N/A
...

The topology shows PHB (PCIe Host Bridge) for all GPU pairs. This is a significant improvement over the i440FX configuration, where the topology would have shown a flat bus (no PCIe hierarchy).

PHB means the GPUs are on different PCIe host bridges but within the same PCIe domain. In the Q35 configuration, each GPU is on its own PCIe root port, which is connected to the host bridge. The NVIDIA driver reports PHB because the GPUs are on different root ports, even though they share the same host bridge.

26.2 Why PHB Prevents P2P

P2P DMA requires that the GPUs be on the same PCIe switch or the same root complex. When GPUs are on different root ports (even on the same host bridge), the PCIe specification does not guarantee direct P2P capability. The NVIDIA driver checks the PCIe topology and reports NS (Not Supported) for P2P when the GPUs are on different root ports.

In a bare-metal system, some platforms support P2P between GPUs on different root ports if the CPU's internal fabric (e.g., AMD Infinity Fabric) supports direct peer-to-peer transactions. However, this requires specific hardware support and is typically only available on platforms with a unified PCIe topology (like AMD's Threadripper Pro or Intel's Xeon with multiple root ports in the same IOMMU group).

In a virtualized environment, the VFIO/IOMMU layer adds additional constraints. Even if the hardware supports P2P between root ports, the IOMMU may not allow it because each root port is in a separate IOMMU group. The VFIO framework enforces isolation between IOMMU groups, preventing P2P DMA.

26.3 The CPU Affinity Anomaly

An interesting detail in the topology output is the CPU affinity:

GPU0 ... CPU Affinity: 0-119  NUMA Affinity: 0-1

All GPUs show CPU affinity of 0-119 (all CPUs) and NUMA affinity of 0-1 (both NUMA nodes). This means the NVIDIA driver sees all GPUs as equally distant from all CPUs, which is incorrect. In reality, four GPUs should be closer to NUMA node 0 and four to NUMA node 1.

This "flat" affinity is a consequence of the virtualization layer. QEMU presents the GPUs as being on a single PCIe domain with no NUMA distance information. The NVIDIA driver cannot determine which GPUs are closer to which CPU sockets, so it reports all CPUs as equally distant.

This has performance implications: when the CUDA runtime allocates memory or launches kernels, it cannot optimize for NUMA locality. Memory allocations for a GPU on socket 0 might be served from socket 1's RAM, adding latency. This is a known limitation of GPU passthrough in QEMU and is difficult to fix without exposing the physical NUMA topology to the guest.

27. The Human Element: Collaboration Under Pressure

27.1 The User's Perspective

From the user's perspective, message 331 represents a moment of confusion and concern. They have:

  1. Applied changes recommended by the AI assistant
  2. Rebooted the host (a significant operation that takes the entire system offline)
  3. Waited for the system to come back
  4. Discovered that only 2 of 8 GPUs are working The user's first question—"Do I want vIOMMU enabled in Machine setting?"—reveals their state of mind. They are looking for a quick fix, a checkbox they missed, a setting that will magically restore the GPUs. This is a natural response to an unexpected failure: search for the simple explanation first. The user also provides an enormous amount of data: the full VM config, the host kernel cmdline, the complete dmesg output, and the nvidia-smi output. This is a heroic effort in data collection. The dmesg alone is over 1,500 lines. The user could have just said "it's broken, only 2 GPUs show up," but instead they provided comprehensive diagnostic data.

27.2 The Assistant's Perspective

From the assistant's perspective, message 331 is a diagnostic challenge. The assistant must:

  1. Parse the massive dmesg output
  2. Identify the critical failure signals
  3. Distinguish between symptoms (NVIDIA driver errors) and root causes (BAR allocation failures)
  4. Formulate a fix that doesn't require reverting the beneficial changes
  5. Communicate the diagnosis clearly to the user The assistant's response in message 332 demonstrates effective troubleshooting: - It immediately identifies the key error pattern (BAR2 failures) - It connects the failures to the kernel's suggestion (pci=realloc) - It explains the root cause (bridge window allocation vs. BAR assignment) - It provides a clear, actionable fix - It advises against the vIOMMU distraction

27.3 The Collaboration Dynamic

The collaboration between user and assistant in message 331 and its aftermath is a model of effective remote troubleshooting:

  1. User applies changes and reports results: The user takes action and provides comprehensive data
  2. Assistant analyzes and diagnoses: The assistant processes the data and identifies the root cause
  3. Assistant prescribes fix: The assistant provides clear, step-by-step instructions
  4. User implements fix: The user executes the prescribed commands
  5. Both verify: The assistant checks the results and confirms success This cycle works because both parties contribute their strengths: the user has access to the system and can execute commands, while the assistant has the knowledge to interpret the data and formulate solutions.

28. The Performance Implications

28.1 What Was Lost

The BAR allocation failure in message 331 caused the loss of 6 out of 8 GPUs. For the GLM-5-NVFP4 model deployment, this is catastrophic:

28.2 What Was Gained

Despite the immediate loss of GPUs, the Q35 + pcie=1 configuration provides several benefits once the BAR allocation is fixed:

  1. Proper PCIe topology: The GPUs are now on dedicated PCIe root ports, which is necessary for any future P2P enablement.
  2. PHB topology: The NVIDIA driver reports PHB instead of flat bus, which is a step toward P2P.
  3. IOMMU passthrough: The host kernel now uses iommu=pt, which reduces DMA latency for all GPU transfers.
  4. PCIe-native features: The GPUs can use PCIe features like ACS, ARI, and extended configuration space, which were not available with i440FX.

28.3 The Net Effect

After the pci=realloc fix is applied (in subsequent messages), the system has:

29. The Philosophical Dimension: On the Nature of Systems

29.1 Emergent Complexity

Message 331 is a perfect example of emergent complexity in computer systems. Each individual change was simple and well-understood:

29.2 The Black Swan

The BAR allocation failure in message 331 is a "black swan" event: a rare, unexpected occurrence with severe consequences. Eight-GPU configurations with 128 GB BARs are uncommon. The combination of SeaBIOS firmware, Q35 chipset, and eight large-BAR GPUs is rare enough that it hasn't been thoroughly tested by the QEMU or Proxmox communities.

The team is operating at the edge of what the virtualization stack can handle. They are pushing the limits of SeaBIOS's PCI allocator, QEMU's MMIO window sizing, and the Linux kernel's resource management. At these limits, unexpected failures are more likely.

29.3 The Value of Failure

Message 331 is valuable precisely because it represents a failure. Successes confirm what we already know; failures teach us something new. The BAR allocation failure taught the team:

  1. SeaBIOS has limitations with large-BAR GPUs
  2. The pci=realloc kernel parameter is a powerful tool for fixing BAR issues
  3. The Q35 chipset requires more careful BAR management than i440FX
  4. The kernel's diagnostic messages are reliable guides to solutions Without this failure, the team might have deployed with i440FX and never discovered the BAR allocation issue. They would have been stuck with a suboptimal PCI topology and no path to P2P. The failure forced them to confront the limitations of their configuration and find a better solution.

30. Final Reflections

30.1 The Message as Artifact

Message 331 is an artifact of a specific moment in time: February 19, 2026, at 01:55 UTC. It captures the state of a complex system at a moment of crisis. The dmesg output, the VM config, the host kernel cmdline, and the nvidia-smi output together form a snapshot of a system in transition—moving from one configuration to another, with all the attendant risks and complications.

For future readers, this message is a time capsule. It shows what cutting-edge AI infrastructure looked like in early 2026: AMD EPYC 9335 processors, NVIDIA RTX PRO 6000 Blackwell GPUs, Proxmox VE 8.x, and the Linux 6.8 kernel. It shows the challenges of virtualizing this hardware for AI workloads. And it shows the diagnostic process that engineers use to overcome these challenges.

30.2 The Enduring Questions

Message 331 raises questions that are still relevant today:

  1. How should we virtualize GPUs for AI workloads? The tradeoff between isolation and performance is fundamental. Are there better approaches than full device passthrough?
  2. Can firmware keep up with hardware? SeaBIOS was designed for simpler configurations. As GPUs grow larger BARs and more complex topologies, firmware must evolve.
  3. What is the role of AI assistance in system administration? The assistant in this conversation provided valuable diagnostic guidance, but the user had to execute the commands and provide the data. How can AI assistance become more proactive and autonomous?
  4. How do we balance optimization and reliability? The pursuit of P2P performance led to a configuration that broke basic functionality. How do we know when to push for optimization and when to accept current limitations? These questions have no easy answers. They are the enduring challenges of systems engineering, and each new generation of hardware and software must grapple with them anew.

30.3 The Human Story

At its heart, message 331 is a human story. It's about an engineer (the user) who applied changes in good faith, only to see the system break. It's about an AI assistant that analyzed the wreckage and found a path forward. It's about collaboration, diagnosis, and recovery.

The user's question—"Do I want vIOMMU enabled in Machine setting?"—is a human moment. It's the sound of someone searching for answers, trying to understand why things went wrong, looking for the lever they missed. The assistant's response—first addressing the immediate crisis, then gently explaining why vIOMMU won't help—is also a human moment. It's the sound of expertise meeting confusion with clarity.

This is why message 331 matters. Not just for the technical lessons it contains, but for the human story it tells. It's a story about learning from failure, about the value of diagnostic data, and about the partnership between human and machine in the pursuit of understanding.

Appendix C: Commands Referenced in This Article

| Command | Purpose | When to Use | |---------|---------|-------------| | qm config &lt;VMID&gt; | Show VM configuration | After any VM config change | | cat /proc/cmdline | Show kernel command line | To verify boot parameters | | dmesg | Show kernel log messages | After boot, to diagnose issues | | dmesg | grep -iE &#39;pci\|bar\|nvidia\|error\|fail&#39; | Filter dmesg for relevant messages | When debugging PCIe or GPU issues | | nvidia-smi | Show GPU status | To verify GPU detection and health | | nvidia-smi topo -p2p | Show P2P matrix | To check P2P support between GPUs | | nvidia-smi topo -m | Show GPU topology | To understand GPU connectivity | | lspci -nn | List PCI devices with IDs | To identify GPU bus addresses | | lspci -vvv | Detailed PCI device info | To examine BAR sizes and capabilities | | update-grub | Update GRUB boot config | After changing kernel cmdline | | qm set &lt;VMID&gt; -args &#39;&lt;qemu_args&gt;&#39; | Add custom QEMU arguments | For advanced VM configuration | | qm set &lt;VMID&gt; -delete args | Remove custom QEMU arguments | To revert QEMU args changes | | proxmox-boot-tool refresh | Refresh Proxmox boot config | After changing host kernel cmdline |

Appendix D: Key Files and Their Locations

| File | Location | Purpose | |------|----------|---------| | VM configuration | /etc/pve/nodes/&lt;node&gt;/qemu-server/&lt;VMID&gt;.conf | Proxmox VM settings | | Host kernel cmdline | /etc/kernel/cmdline (Proxmox) | Boot parameters for host | | Guest GRUB config | /etc/default/grub | Boot parameters for guest VM | | Cloud-init GRUB override | /etc/default/grub.d/50-cloudimg-settings.cfg | Cloud image GRUB settings | | PCI device mapping | /etc/pve/mapping/pci/&lt;name&gt;.cfg | Proxmox PCI resource mapping | | Kernel log | /var/log/kern.log | Persistent kernel log | | GRUB configuration | /boot/grub/grub.cfg | Generated GRUB config |

Appendix E: Timeline of Events

| Time (relative) | Event | |-----------------|-------| | Before msg 331 | VM running with i440FX, 8 GPUs working, P2P NS | | Msg 330 | Assistant recommends 3-phase plan | | User action | Apply all 3 phases: Q35, pcie=1, amd_iommu=on iommu=pt | | User action | Reboot host and VM | | Msg 331 | User reports: only 2 GPUs detected | | Msg 332 | Assistant diagnoses BAR allocation failure, recommends pci=realloc | | User action | Add pci=realloc to guest kernel cmdline | | User action | Reboot VM | | Msg 359-361 | All 8 GPUs detected, P2P still NS | | Ongoing | Team explores ACS disable and other P2P workarounds |

This article was written as a deep analysis of message 331 in an opencode coding session about deploying the GLM-5-NVFP4 model on 8 NVIDIA RTX PRO 6000 Blackwell GPUs in a Proxmox virtual machine. The analysis focuses on the technical, diagnostic, and human dimensions of a critical moment in the conversation.