Absolutely no begging for anything on the subreddit. Please visit r/hardwareswap buying, selling, or trading. Rule 11: No Buying/Selling/Trading - No buying/selling/trading on this subreddit. This includes pictures of boxes, straw polls, fake news, complaints, or other contents deemed low quality by community moderators. Rule 10: Low Quality & Duplicate Content - Low quality content will be removed. For non-English submission, please use generic titles for ease of searching. Please use suggested title for link submission or copy the title of the original link. Rule 9: No Editorialization - News/Reviews/Benchmarks related posts should not have editorialized titles and should be posted in whole. Discuss the specific rumor in the respective rumor thread that was posted. Additionally, to prevent the spread of potentially incorrect information or fake rumors, there will be no standalone discussion regarding specific rumors. Rumor posts are allowed but it must link back to a reputable source. Rule 8: No Unsubstantiated Rumors & Discussions - No unsubstantiated rumors or conspiracies. Rule 7: No Memes and Shitposts - Memes and shitposts will be removed Please send a modmail if you'd like to discuss an exception. That includes your youtube channel and website. Rule 6: No Self Advertising - Self advertising is not allowed here. Repeat offenders will be banned without notice. Rule 5: No Referral or Affiliate Links - Referral or affiliate links are not allowed here. Absolutely no politics and religion talk on the subreddit. No brigading, personal attack bashing, mudslinging, or witch hunting. No Religion or Politics - Be nice, civil and follow rediquette. This means the article must be talking specifically about Nvidia as a company, Nvidia's product, or other products using Nvidia's technology. Rule 3: Relevant Content - All posts must be primarily related to Nvidia. Please follow Rule #10 regarding low quality content when posting your build and please only post builds with Nvidia products clearly visible. Rule 2: Build Pictures Related Posts - Build pictures related posts are only allowed on Friday, Saturday, and Sunday. You can also use /r/TechSupport community. Latest thread is linked in the sidebar or pinned on the front page. Rule 1: Tech Support & Issues - Tech Support posts are not allowed. This Subreddit is community run and does not represent NVIDIA in any capacity unless specified. A place for everything NVIDIA, come talk about news, rumours, GPUs, the industry, show-off your build and more. Here, I do understand that it need some dependencies.Welcome to /r/NVIDIA. Recommends: nvidia-visual-profiler (= 10.1.243-3) but it is not going to be installedĮ: Unable to correct problems, you have held broken packages. Or been Recommends: nvidia-visual-profiler (= 10.1.243-3) but it is not going to be installedĮ: Unable to correct problems, you have held broken packages.oing to be installed Requested an impossible situation or if you are using the unstableĭistribution that some required packages have not yet been created Are the newer versions back-compatible?Īs per Nmath's suggestion, I went on to install CUDA from the Ubuntu repository as follows. I found an old article which says my GPU supports CUDA 2.1. Or should I download CUDA separately in case I wish to run some Tensorflow code. I want to download Pytorch but I am not sure which CUDA version should I download. In other answers for example in this one Nvidia-smi shows CUDA version, but CUDA is not installed there is CUDA version next to the Driver version. AAgAAAAAAAAACAAAAAAAAAA= -shared-files 142MiB | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. When I type nvidia-smi in my terminal I can see the following. I've got a supercomputer from my university to train bigger models. I want to use my GPU (Nvidia Quadro 2000 1GB GDDR5) for very basic machine learning models. This is the first GPU I am using and unfortunately, I am using Ubuntu 20.04 not easy easy Windows.
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