The Moment of Breakthrough: All 8 GPUs Come Online

A Pivotal Message in the Proxmox GPU Passthrough Saga

In any complex debugging session, there is a moment when the fog clears and the system finally cooperates. Message [msg 362] in this opencode session represents exactly that turning point — a brief, almost understated confirmation that a multi-hour struggle with PCIe BAR allocation, firmware limitations, and virtualization configuration has finally yielded success. The assistant writes:

All 8 GPUs initialized successfully — no BAR errors, no probe failed, all 97887 MiB VRAM each. The pci=realloc + Q35 + pcie=1 combination worked perfectly.

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P2P is still NS — that's expected since P2P between GPUs on separate PCIe root ports in a VM requires additional VFIO/IOMMU configuration. But the topology is now PHB (much better than the old flat i440FX bus), and the GPUs are on proper PCIe root ports.

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Let me now launch the sglang server and benchmark to see if the Q35+PCIe changes alone improve throughput:

This message is deceptively simple. On its surface, it is a status update — a quick confirmation that a technical fix worked. But beneath that brevity lies the culmination of an intense, multi-layered debugging effort spanning host kernel modifications, VM chipset migration, firmware configuration, and guest kernel parameter tuning. Understanding why this message was written, what it reveals about the assistant's reasoning, and what it means for the broader project requires unpacking the entire chain of events that led to this point.

The Context: A System That Refused to Cooperate

The session leading up to this message had been grappling with a fundamental hardware configuration problem. The machine in question is a Proxmox VE host running on an ASUS ESC8000A-E13 motherboard with dual AMD EPYC processors and eight NVIDIA RTX PRO 6000 Blackwell GPUs, each equipped with 96 GB of VRAM. The goal was to deploy the GLM-5-NVFP4 large language model across all eight GPUs using SGLang with tensor parallelism — a demanding workload that requires all GPUs to be visible and functional within the guest VM.

The initial VM configuration used the legacy i440FX chipset, which presented all PCIe devices on a flat bus rather than a proper PCIe hierarchy. This caused severe BAR (Base Address Register) allocation failures: each GPU's BAR2 region — a massive 128 GB mapping for its VRAM — could not be assigned by the firmware. The result was that only 2 of the 8 GPUs were detected by the NVIDIA driver, with the remaining 6 failing with errors like can't claim; no compatible bridge window and BAR2 is 0M @ 0x0.

The assistant had systematically worked through the layers of this problem. On the Proxmox host, IOMMU was enabled via kernel command-line parameters (amd_iommu=on iommu=pt). The VM was migrated from i440FX to the Q35 chipset with PCIe passthrough enabled (pcie=1). An attempt to set mch.above_4g_mem_size=2T was made and then rolled back. The guest kernel was instructed to reallocate PCI resources via the pci=realloc boot parameter. Each step peeled back another layer of the onion, revealing deeper constraints.

Why This Message Was Written: The Reasoning and Motivation

The assistant wrote this message for several interconnected reasons, each reflecting a distinct cognitive need in the debugging workflow.

First, to confirm success. After applying the pci=realloc fix — which itself required two attempts because a cloud-init configuration file was overriding the GRUB settings — the assistant needed to verify that the fix had actually worked. The previous reboot had shown only 2 GPUs. The reboot with pci=realloc properly applied showed all 8. This confirmation was the primary motivation for the message: the assistant was checking off a critical milestone.

Second, to document the state of P2P (Peer-to-Peer) DMA. The assistant immediately notes that P2P is still "NS" (Not Supported). This is not an oversight or a failure — it is an expected outcome given the hardware topology. The assistant's reasoning here is crucial: it distinguishes between the BAR allocation problem (which was solved) and the P2P problem (which remains a separate concern). By explicitly calling out that P2P requires "additional VFIO/IOMMU configuration," the assistant signals that this is a known limitation that will need to be addressed separately, not a regression or an unexpected side effect.

Third, to establish a new baseline. The assistant notes that the topology is now "PHB" (PCIe Host Bridge) rather than the flat bus of i440FX. This is a significant improvement — it means each GPU is on its own PCIe root port, which is the correct configuration for proper PCIe hierarchy. The assistant's motivation here is to set expectations for the upcoming benchmark: even without P2P, the improved topology alone might yield throughput improvements. The message transitions from debugging to benchmarking.

Fourth, to plan the next action. The todo list embedded in the message marks several items as completed — the IOMMU investigation, the host kernel modifications, the BAR allocation fix — and marks a new item as "in_progress": launching the SGLang server and benchmarking. This is a classic pattern in the assistant's workflow: each message serves as both a status update and a planning document, with the todo list providing explicit traceability of what has been accomplished and what remains.

How Decisions Were Made

The most significant decision reflected in this message is the choice to proceed with benchmarking despite P2P remaining unsupported. This decision reveals several layers of reasoning.

The assistant could have continued down the P2P rabbit hole — investigating ACS (Access Control Services) disable, exploring nv_peer_mem kernel modules, or attempting to merge IOMMU groups. Indeed, earlier in the conversation, the assistant had explored exactly these avenues, including modifying the Proxmox host kernel to disable ACS on the PCIe bridges. However, those investigations had revealed a fundamental hardware topology constraint: each GPU sits on its own dedicated PCIe root complex on the AMD EPYC platform, with no shared PCIe switch. This design, while maximizing per-GPU bandwidth, creates separate IOMMU domains that VFIO cannot bridge.

The decision to benchmark first and optimize P2P later is a pragmatic one. The assistant implicitly assumes that the Q35+PCIe topology improvement alone may yield measurable throughput gains, and that understanding the current baseline is necessary before investing more time in P2P enablement. This reflects a "measure first, then optimize" philosophy that is characteristic of performance engineering.

The assistant also makes an implicit decision about what constitutes "success." After the BAR allocation fix, all 8 GPUs are visible, each with its full 96 GB VRAM, and the NVIDIA driver loads without errors. For the immediate goal of deploying the GLM-5-NVFP4 model, this is sufficient. P2P would improve performance — especially for the all-to-all communication patterns in tensor-parallel inference — but it is not a prerequisite for the model to run.

Assumptions Embedded in the Message

Several assumptions underpin this message, some explicit and some implicit.

Explicit assumption: P2P requires VFIO/IOMMU configuration. The assistant states that P2P being NS is "expected since P2P between GPUs on separate PCIe root ports in a VM requires additional VFIO/IOMMU configuration." This assumes that the VFIO/IOMMU layer is the correct path to enabling P2P in a virtualized environment. While this is technically accurate — VFIO does mediate DMA transfers in KVM — the deeper assumption is that the IOMMU groups can be made to cooperate. As later investigation would show, the hardware topology (separate root complexes) may fundamentally prevent this regardless of software configuration.

Implicit assumption: the PHB topology is "much better." The assistant asserts that PHB is better than the flat i440FX bus. This is true in terms of PCIe hierarchy correctness — each GPU having its own root port is how the hardware was designed to operate. However, the assumption that this will translate into measurable throughput gains is unverified at this point. The assistant is about to test this assumption by benchmarking.

Implicit assumption: the BAR allocation fix is stable. The assistant assumes that because the GPUs initialized successfully once, they will continue to do so on subsequent reboots. Given that the fix involved a kernel command-line parameter (pci=realloc) that is persistent across boots, this is a reasonable assumption, but it has not been tested with multiple power cycles.

Implicit assumption: the remaining work is benchmarking, not debugging. The todo list marks the BAR allocation problem as "completed" and moves on to "launch sglang server and benchmark." This assumes that no further hardware configuration issues will surface when the GPUs are placed under load — an assumption that, given the complexity of the system, is optimistic.

Input Knowledge Required

To fully understand this message, a reader needs knowledge spanning several domains.

Virtualization and PCIe architecture: One must understand what BARs are, why a 128 GB BAR2 region is needed for a 96 GB GPU, and how the Q35 chipset differs from i440FX in terms of PCIe topology. The distinction between a flat bus and a hierarchical PCIe root port topology is central to the message's significance.

Proxmox VE and KVM configuration: The message references pci=realloc, Q35, and pcie=1 — all Proxmox/KVM configuration parameters. Understanding that pci=realloc is a Linux kernel parameter that tells the kernel to reassign PCI resources that the firmware failed to allocate is essential. Similarly, knowing that Q35 enables PCIe native hotplug and proper PCIe hierarchy (as opposed to i440FX's PCI-only bus) explains why the migration was necessary.

NVIDIA GPU topology reporting: The message uses abbreviations like "PHB" (PCIe Host Bridge) and "NS" (Not Supported) from nvidia-smi topo -m and nvidia-smi topo -p2p r. Understanding these topology codes is necessary to interpret the assistant's assessment of the current state.

The GLM-5-NVFP4 deployment context: The broader goal — deploying a large language model with tensor parallelism across 8 GPUs — explains why P2P matters. In tensor-parallel inference, GPUs must frequently exchange activations and gradients. Without P2P DMA, these exchanges go through host memory via the CPU, adding latency and consuming memory bandwidth. The message's concern about P2P is directly tied to this workload characteristic.

Output Knowledge Created

This message creates several valuable pieces of knowledge for the session.

A verified solution to the BAR allocation problem. The message confirms that the combination of Q35 chipset, PCIe passthrough (pcie=1), and the pci=realloc kernel parameter successfully enables all 8 GPUs with full VRAM. This is a concrete, reproducible configuration that can be applied to similar setups.

A documented baseline for P2P status. The message explicitly records that P2P is "NS" after the configuration changes. This is important negative knowledge — it tells future readers that the Q35 migration alone does not enable P2P, and that additional work is needed if P2P is required.

A decision point for the project. By marking the BAR allocation as completed and moving to benchmarking, the message creates a clear transition in the project's workflow. Future readers can see that after this point, the focus shifts from hardware configuration to performance measurement.

A todo list that tracks progress. The embedded todo list provides explicit traceability of what has been accomplished (IOMMU investigation, host kernel modifications, BAR fix) and what remains (SGLang server launch, benchmarking). This is a form of process documentation that would be valuable if someone needed to reproduce or extend this work.

The Thinking Process Visible in the Message

The assistant's thinking is visible in several aspects of this message.

The prioritization of concerns. The assistant immediately addresses the two most important questions: "Did all GPUs come up?" (yes) and "Is P2P working?" (no). This reflects a mental model where the primary goal (all GPUs functional) takes precedence over the optimization goal (P2P). The assistant is triaging: first ensure the system works, then optimize.

The causal reasoning about P2P. The assistant explains why P2P is still NS — "GPUs on separate PCIe root ports in a VM requires additional VFIO/IOMMU configuration." This is not a guess; it reflects the assistant's understanding of how VFIO mediates DMA in KVM. Each GPU being on its own root port means they are in separate IOMMU groups, and VFIO by default does not allow DMA between devices in different groups for security isolation.

The comparative assessment of topology. The assistant notes that PHB is "much better than the old flat i440FX bus." This comparative judgment shows that the assistant is evaluating the current state against the previous state, not against an ideal. The improvement is relative, not absolute.

The forward-looking plan. The message ends with a plan to benchmark, implicitly hypothesizing that the topology improvement alone may improve throughput. The assistant is forming a testable hypothesis and preparing to gather data.

Significance and Implications

This message represents a genuine breakthrough in a complex debugging session. The BAR allocation problem had been the primary blocker for hours, preventing the deployment of the GLM-5-NVFP4 model across all 8 GPUs. Solving it required understanding the interplay between guest firmware (SeaBIOS), the QEMU virtual chipset (Q35), the guest kernel's PCI resource management, and the NVIDIA driver's BAR requirements.

The broader implication is that virtualized GPU deployments at this scale — 8 GPUs with 96 GB VRAM each — push the boundaries of what Proxmox and KVM can handle out of the box. The default configurations (i440FX chipset, no pci=realloc) are designed for more modest hardware. Getting all 8 GPUs to work required explicit configuration at every layer: host kernel, VM chipset, guest firmware, and guest kernel.

The message also highlights the tension between virtualization and high-performance GPU computing. Even with all GPUs functional, P2P DMA — critical for tensor-parallel inference performance — remains elusive in this virtualized setup. The assistant's decision to benchmark anyway reflects a pragmatic acceptance that some performance may be sacrificed for the operational benefits of virtualization (flexibility, isolation, management).

For anyone attempting a similar deployment — large-scale GPU passthrough in Proxmox with modern NVIDIA GPUs — this message and its surrounding context provide a valuable case study. The solution is not a single magic parameter but a combination of changes at multiple layers, each addressing a different aspect of the problem. And the message itself, brief as it is, serves as the milestone that marks the transition from "can we make it work?" to "how well does it work?"