2nd Monitor Blank X Cursor Ubuntu 20.04

Ubuntu 20.04 all drivers from 435-455

I just upgraded my old, very old gtx780 to DUAL (identical) RTX2060 8GB Supers. I have monitor 0 plugged into gpu0’s dvi, and monitor 1 plugged into gpu1’s dvi.

My problem in that nothing I do can get monitor 1 to do anything but show the “X” cursor and generally be useless. If I “DISPLAY=:0.1 xclock” the clock shows up in monitor 1. If I use the noveaux X drivers both screens work like expected.

How do I get both screens working under the Nvidia driver so I can use both cards to do DeepFakes and Mine Bitcoin using Cuda?

GPU0 will not allow ANY of these functions. GPU1 will, but will not show anything on monitor1 .

8 Core Opteron, 32GB ram, 8GB drive space. Any help appreciated.

Most modern desktop environments don’t support more than one X screen and will just ignore additional X screens. It sounds like that’s what’s happening here.

If you want to have two monitors on one desktop, I’d recommend just plugging both of them into one GPU. You can use the other GPU with CUDA without having an X screen on it.

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The strange part is even with only 1 card installed NOTHING I do can get the single 2060 to do Cuda tasks. My old 780 was the only card in the computer and it ran cuda tasks while driving two monitors.

Will driving BOTH cards off GPU0 make it so gpu0 and gpu1 BOTH can do cuda tasks?

Many thanks for the fast reply.

Yeah, you should be able to use CUDA with one or both GPUs. What error are you getting?

My displayport to dvi adapter came this morning. I plugged monitor1 into gpu0. And Gnome came up using both screens as it did with my old single card. My guess is the Nvidia driver just doesn’t want to have display0 plugged into gpu0 and display1 plugged into gpu1. It wants them both plugged into gpu0. That is working now.

Still can’t get GPU0 to do cuda tasks. Always says it can’t allocate the memory on the card.

2020-10-01 22:41:27.315577: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 5.06G (5437426176 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory

Cuda is sometimes working. Getting TONS of OOM warnings/errors

2020-10-03 11:28:47.721067: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_1_bfc) ran out of memory trying to allocate 2.83GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2020-10-03 11:28:50.738949: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.29G (2462352128 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory

nvidia-smi reports memory available.

| NVIDIA-SMI 455.23.04 Driver Version: 455.23.04 CUDA Version: 11.1 |
| 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 GeForce RTX 206… Off | 00000000:01:00.0 On | N/A |
| 35% 51C P2 45W / 175W | 5682MiB / 7979MiB | 2% Default |
| | | N/A |
| 1 GeForce RTX 206… Off | 00000000:02:00.0 Off | N/A |
| 29% 46C P2 43W / 175W | 5657MiB / 7982MiB | 2% Default |
| | | N/A |

| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
| 0 N/A N/A 1551 G /usr/lib/xorg/Xorg 153MiB |
| 0 N/A N/A 1948 G /usr/bin/gnome-shell 99MiB |
| 0 N/A N/A 7093 G …AAAAAAAAA= --shared-files 64MiB |
| 0 N/A N/A 9687 C …/envs/faceswap/bin/python 5359MiB |
| 1 N/A N/A 1551 G /usr/lib/xorg/Xorg 4MiB |
| 1 N/A N/A 1948 G /usr/bin/gnome-shell 0MiB |
| 1 N/A N/A 7093 G …AAAAAAAAA= --shared-files 0MiB |
| 1 N/A N/A 9687 C …/envs/faceswap/bin/python 5649MiB |

Ubuntu 20.04, 5.4 and 5.8 kernel, 435-455 driver all acting the same.