Use 'sudo apt autoremove' to remove them. Libxcb-present0:i386 libxcb-randr0:i386 libxcb-sync1:i386 The following packages were automatically installed and are no longer required: Let me share the logs: sudo apt install cuda-9-1 I am not able to download anything other then CUDA 11.4 in my machine I wonder why 😕
I suppose the PyTorch version v1.3.1 supports CUDA 10.1 only. I want to use Pytorch and for my card I will need to build it from source. ( 2) Multiprocessors, (192) CUDA Cores/MP: 384 CUDA Cores Total amount of global memory: 981 MBytes (1028980736 bytes) I am looking into using cuda-9-1 as suggested above, also, but I’m expecting a bit of a struggle installing it on ubuntu 20.04 since it was built for /on17.04.ĬUDA Driver Version / Runtime Version 11.2 / 11.2ĬUDA Capability Major/Minor version number: 3.5 I’m guessing that the memory test did not really run at all? Can the experts confirm my suspicion? Thanks. Moving Inversions (ones and zeros): 4294967295 errors (0 ms)
Test iteration 1 (GPU 0, 4 MiB): 0 errors so far When I ran the memtestG80, it reported 4e9 errors in a very short time, as seen here: However, what I really wanted to do was to test the memory of my gt730 card using memtestG80, which I compiled using cuda-11-2. I tried cuda-11-2 with a GeForce gt730, and some of the /usr/local/cuda/samples programs seemed to run okay. I’m hoping for an expert opinion on the following case: | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. What the result after you command “nvidia-smi”? is it no supported like below
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