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Failes on 1xRTX4090 and 1xRTX6000 Ada #38

Description

@wlarsong

NVIDIA Open GPU Kernel Modules Version

610.57.04-p2p

Please confirm this issue does not happen with the proprietary driver (of the same version). This issue tracker is only for bugs specific to the open kernel driver.

  • I confirm that this does not happen with the proprietary driver package.

Operating System and Version

Description: Ubuntu 26.04 LTS

Kernel Release

Linux definitely-not-a-banana 7.0.0-29-generic #29-Ubuntu SMP PREEMPT_DYNAMIC Fri Jul 17 20:52:35 UTC 2026 x86_64 GNU/Linux

Please confirm you are running a stable release kernel (e.g. not a -rc). We do not accept bug reports for unreleased kernels.

  • I am running on a stable kernel release.

Hardware: GPU

GPU 0: NVIDIA RTX 6000 Ada Generation (UUID: GPU-00a1e30c-c092-d1da-65a8-5732c0b37891) GPU 1: NVIDIA GeForce RTX 4090 (UUID: GPU-8c42a17f-068b-943a-329e-e30d56449953)

Describe the bug

Driver is installed Libcuda is modified simplep2p passes:

./cuda-samples/build/cpp/0_Introduction/simpleP2P/simpleP2P
[./cuda-samples/build/cpp/0_Introduction/simpleP2P/simpleP2P] - Starting...
Checking for multiple GPUs...
CUDA-capable device count: 2

Checking GPU(s) for support of peer to peer memory access...

Peer access from NVIDIA RTX 6000 Ada Generation (GPU0) -> NVIDIA GeForce RTX 4090 (GPU1) : Yes
Peer access from NVIDIA GeForce RTX 4090 (GPU1) -> NVIDIA RTX 6000 Ada Generation (GPU0) : Yes
Enabling peer access between GPU0 and GPU1...
CUDA error at /home/will/cuda-samples/cpp/0_Introduction/simpleP2P/simpleP2P.cu:130 code=205(cudaErrorMapBufferObjectFailed) "cudaDeviceEnablePeerAccess(gpuid[1], 0)"

p2pLatenencyTest Fails

will@definitely-not-a-banana:~$ ./cuda-samples/build/cpp/5_Domain_Specific/p2pBandwidthLatencyTest/p2pBandwidthLatencyTest
[P2P (Peer-to-Peer) GPU Bandwidth Latency Test]
Device: 0, NVIDIA RTX 6000 Ada Generation, pciBusID: 1, pciDeviceID: 0, pciDomainID:0
Device: 1, NVIDIA GeForce RTX 4090, pciBusID: 4b, pciDeviceID: 0, pciDomainID:0
Device=0 CAN Access Peer Device=1
Device=1 CAN Access Peer Device=0

***NOTE: In case a device doesn't have P2P access to other one, it falls back to normal memcopy procedure.
So you can see lesser Bandwidth (GB/s) and unstable Latency (us) in those cases.

P2P Connectivity Matrix
D\D 0 1
0 1 1
1 1 1
Unidirectional P2P=Disabled Bandwidth Matrix (GB/s)
D\D 0 1
0 806.66 21.64
1 21.77 950.43
Unidirectional P2P=Enabled Bandwidth (P2P Writes) Matrix (GB/s)
Cuda failure /home/will/cuda-samples/cpp/5_Domain_Specific/p2pBandwidthLatencyTest/p2pBandwidthLatencyTest.cu:280: 'mapping of buffer object failed'

Thu Aug 20 00:51:43 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 610.57.04 KMD Version: 610.57.04 CUDA UMD Version: 13.3 |
+-----------------------------------------+------------------------+----------------------+
| 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 6000 Ada Gene... Off | 00000000:01:00.0 Off | Off |
| 30% 44C P0 66W / 300W | 0MiB / 49140MiB | 2% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA GeForce RTX 4090 Off | 00000000:4B:00.0 Off | Off |
| 30% 37C P0 69W / 450W | 0MiB / 49140MiB | 2% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+

will@definitely-not-a-banana:~$ cat /etc/modprobe.d/nvidia-gdr.conf
options nvidia NVreg_ExperimentalDmaBufP2P=1

To Reproduce

Install driver for 610 per directions.

Install the modified version of cuda via the python script.

Add the : /etc/modprobe.d/nvidia-gdr.conf
options nvidia NVreg_ExperimentalDmaBufP2P=1

Run p2pLatenecyTest

Bug Incidence

Once

nvidia-bug-report.log.gz

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