NVIDIA Blackwell B200, RTX 5090 & CUDA 12.8/13 Acceleration¶

Authoritative engineering specification for NVIDIA Open Kernel Modules, Blackwell (B200 / RTX 5090) Day-0 enablement, CUDA 12.8/13 unified memory, and GPUDirect RDMA.

1. Architectural Evolution: NVIDIA Open Kernel Modules¶

The NVIDIA GPU computing architecture on Linux has transitioned to open-source kernel modules (nvidia.ko, nvidia-modeset.ko, nvidia-drm.ko, nvidia-uvm.ko), licensed under dual MIT/GPLv2:

Legacy Architectures (Volta/Turing): Maintained on the 535.x LTS branch for older enterprise infrastructure.
Production Enterprise (Ada Lovelace / Hopper): Powered by the 565.x driver series across H100, H200, GH200 Grace Hopper, and RTX 4090 hosts.
Bleeding Edge (Blackwell Microarchitecture): Supported by the 615.x driver family in the bleeding (7.3-rc2) stream for B100, B200, GB200 NVL72 rack systems, and consumer GeForce RTX 5090 / 5080 hardware.

graph TD
    subgraph UserSpace["User-Space AI Stack"]
        LLM["vLLM / TensorRT-LLM / Triton Server"]
        CUDA["CUDA 12.8 / 13 Toolkit & CUDNN 9"]
        NVRUN["NVIDIA Container Toolkit (nvidia-ctk)"]
    end

    subgraph KernelSpace["Linux Kernel (nucleus)"]
        NV_OPEN["NVIDIA Open Kernel Module (nvidia.ko)"]
        NV_UVM["Unified Virtual Memory (nvidia-uvm.ko)"]
        NV_PEER["GPUDirect RDMA (nvidia-peermem.ko)"]
        HMM["Linux Virtual Memory Subsystem (HMM Mirror)"]
        DMA["Direct DMA Mapping & IOMMU"]
    end

    subgraph Hardware["Blackwell & Datacenter Fabric"]
        B200["NVIDIA Blackwell B200 / RTX 5090"]
        NVLINK["NVLink 5.0 (1.8 TB/s per GPU)"]
        CX7["ConnectX-7 400Gb/s RoCEv2 NIC"]
    end

    LLM --> CUDA
    CUDA --> NVRUN
    NVRUN --> NV_OPEN
    CUDA --> NV_UVM

    NV_OPEN --> DMA
    NV_UVM --> HMM
    NV_PEER --> DMA

    DMA --> B200
    NV_OPEN --> NVLINK
    NV_PEER --> CX7

2. Kernel Configuration Baseline for NVIDIA Acceleration¶

To compile and execute NVIDIA Open Kernel Modules without symbol mismatches or memory fragmentation, the following options are enforced across kconfig/drivers/nvidia.config:

# Core PCI, PAT and Memory Management
CONFIG_PCI_MSI=y
CONFIG_X86_PAT=y
CONFIG_MTRR=y
CONFIG_ZONE_DEVICE=y
CONFIG_DEVICE_PRIVATE=y
CONFIG_HMM_MIRROR=y
CONFIG_MIGRATION=y

# DMA and DRM Invariants
CONFIG_DMA_SHARED_BUFFER=y
CONFIG_SYNC_FILE=y
CONFIG_DRM=m
CONFIG_DRM_KMS_HELPER=m

# GPUDirect RDMA & InfiniBand Peer-to-Peer
CONFIG_INFINIBAND=m
CONFIG_INFINIBAND_USER_ACCESS=m
CONFIG_INFINIBAND_USER_MEM=y
CONFIG_PCI_P2PDMA=y

# MicroVM Virtualization & KVM Passthrough
CONFIG_VFIO=m
CONFIG_VFIO_PCI=m
CONFIG_VFIO_IOMMU_TYPE1=m
CONFIG_IOMMU_SUPPORT=y
CONFIG_INTEL_IOMMU=y
CONFIG_AMD_IOMMU=y

Critical Rationale:¶

CONFIG_HMM_MIRROR=y & CONFIG_DEVICE_PRIVATE=y: Enables the CUDA Unified Virtual Memory (UVM) driver to transparently migrate memory pages between physical system DDR5/LPDDR5 memory and GPU HBM3e/GDDR7 memory upon hardware page fault.
CONFIG_PCI_P2PDMA=y & CONFIG_INFINIBAND_USER_MEM=y: Prerequisite for nvidia-peermem, allowing high-speed NICs (Mellanox ConnectX-6/7/8) to directly read and write GPU memory over PCIe/NVLink without copying buffers through system RAM.

3. CUDA 12.8 / 13 Features on Blackwell¶

The Blackwell architecture introduces major hardware breakthroughs enabled by the bleeding kernel stream:

3.1 Second-Generation Transformer Engine (FP4 & Microscaling)¶

Blackwell integrates native 4-bit floating point (NVFP4) and microscaling formats with hardware decompression, doubling token generation throughput over Hopper. The kernel UVM driver allocates contiguous 2 MB physical pages to maximize TLB coverage for high-dimensional tensor weights.

3.2 NVLink 5.0 Fabric & Multi-Node Scaling¶

Delivers up to 1.8 TB/s bidirectional bandwidth per GPU.
Supports 576 GPUs interconnected in a single NVLink cluster domain (GB200 NVL72).
The kernel exposes the NVLink management interface via /dev/nvidia-caps/nvidia-cap* device nodes with fine-grained POSIX access control.

3.3 Enhanced Multi-Instance GPU (MIG)¶

Blackwell allows hardware partitioning of a single physical B200 GPU into up to 7 isolated GPU instances, each with dedicated high-bandwidth memory controllers, cache slices, and compute engines:

# Example: Configuring 7x 1g.24gb MIG instances on B200
nvidia-smi -i 0 -mig 1
nvidia-smi mig -cgi 19,19,19,19,19,19,19 -C

4. Kernel Module Runtime Parameters¶

To maximize inference performance, prevent PCIe ASPM power state latency, and ensure reliable persistence in container nodes:

# /etc/modprobe.d/nvidia.conf
options nvidia \
  NVreg_OpenRmEnableUnsupportedGpus=1 \
  NVreg_PreserveVideoMemoryAllocations=1 \
  NVreg_TemporaryFilePath=/var/tmp \
  NVreg_EnablePCIeGenSpeed=5

options nvidia_uvm \
  uvm_perf_prefetch_enable=1 \
  uvm_perf_fault_coalesce=1

Parameter	Function & Operational Value
`NVreg_OpenRmEnableUnsupportedGpus=1`	Allows the open kernel module to initialize non-datacenter Blackwell GPUs (e.g. GeForce RTX 5090)
`NVreg_PreserveVideoMemoryAllocations=1`	Saves VRAM allocations across power transitions, preventing pod eviction during sleep/resume cycles
`uvm_perf_prefetch_enable=1`	Enables hardware-guided proactive memory prefetching across NVLink interconnects
`uvm_perf_fault_coalesce=1`	Coalesces concurrent GPU memory page faults into batched TLB invalidation operations

5. Verification & Diagnostics¶

To verify the open kernel module installation and hardware health:

# Verify kernel module origin and license
modinfo nvidia | grep -E "filename|license|version"

# Validate GPUDirect RDMA peermem binding
lsmod | grep -E "nvidia_peermem|ib_core"

# Check device node creation and permissions
ls -l /dev/nvidia* /dev/nvidia-uvm*

# Run hardware device query
nvidia-smi -q -d MEMORY,UTILIZATION,ECC

A correctly configured system indicates License: Dual MIT/GPL in modinfo nvidia and displays zero ECC double-bit errors.