nvcc fatal : Unsupported gpu architecture 'compute_86'

Question

I have a Nvidia RTX 3090 ti 24GB with this drivers

CUDA Version: 11.4 

Driver Version: 470.74

18.04.1-Ubuntu SMP

Cuda compilation tools, release 9.1, V9.1.85

I've looked for this card architecture and it is Ampere so the version of library are compute_86 or sm_86(if I am not wrong). But while compiling with nvcc it gives me back

nvcc fatal : Unsupported gpu architecture 'compute_86'

I've runned nvcc --help and I've found something strange, it returned me that for gpu-code and gpu-architecture

Allowed values for this option: 'compute_30','compute_32','compute_35', 'compute_37','compute_50','compute_52','compute_53','compute_60','compute_61', 'compute_62','compute_70','compute_72','sm_30','sm_32','sm_35','sm_37','sm_50', 'sm_52','sm_53','sm_60','sm_61','sm_62','sm_70','sm_72'.

So I'm missing any driver version or some library that has to be donwloaded or I can't compile with my GPU?

Answer 1

In your posted system information, the last line

Cuda compilation tools, release 9.1, V9.1.85

indicates that your NVCC is currently V9.1 (use nvcc -V to know for sure). NVCC of this version is too old to support compute_86. A possible reason for which this happens is that you have installed the CUDA toolkit (including NVCC) and the GPU drivers separately, with different CUDA versions. You can solve it by updating it to V11.4 by following the instructions on this official page: developer.nvidia.com/cuda-11-4-2-download-archive. In my experience, managing NVIDIA drivers and CUDA toolkits with apt often messes up the system. So it is recommended to use the official installer instead. Remember to reset the CUDA-related environment variables to link to the new version if you have set them before.

To get another specific version of CUDA, you can just google "cuda toolkit (version number) download" and look for the official nvidia website results.

Answer 2

You nvcc version is too old to support compute_86.

Since you installed cuda 11.4, you can add the cuda 11.4 bin fold to path so that you can use nvcc 11.4 to compile.

export PATH=/usr/local/cuda-11.4/bin:$PATH

then compile.

or

echo "export PATH=/usr/local/cuda-11.4/bin:$PATH" >> ~/.bashrc
source ~/.bashrc

if you are using zsh

echo "export PATH=/usr/local/cuda-11.4/bin:$PATH" >> ~/.zshrc
source ~/.zshrc

Answer 3

this is how to easy install openpose

copy the following script and save it in new text file and save as bash file. example: rename text file as install.sh

also change the desired instal location in the second line

export SOFTWARE_INSTALL_DIR=/usr/local/soft

#!/bin/bash

export SOFTWARE_INSTALL_DIR=/usr/local/soft

# Prerequisites Installation
sudo apt update
sudo apt full-upgrade -y
sudo apt autoremove -y
sudo apt install gcc g++ make autoconf git libtool curl unzip python3-pip cmake-qt-gui caffe-cpu libopencv-dev python-dev libgoogle-glog-dev libboost-all-dev libhdf5-dev libatlas-base-dev -y
sudo apt clean
pip3 install -U pip numpy opencv-python

# Directory Configuration
sudo mkdir -p $SOFTWARE_INSTALL_DIR
cd $SOFTWARE_INSTALL_DIR
sudo chown -R $USERNAME:$USERNAME $SOFTWARE_INSTALL_DIR

# Protocol Buffers Installation
git clone https://github.com/protocolbuffers/protobuf.git
cd protobuf
git submodule update --init --recursive
./autogen.sh
./configure
make
make check
sudo make install
sudo ldconfig

# OpenPose Installation
cd $SOFTWARE_INSTALL_DIR
git clone https://github.com/CMU-Perceptual-Computing-Lab/openpose
cd openpose
git submodule update --init --recursive --remote
sudo mkdir build/
cd build/
sudo cmake-gui ..
make -j`nproc`

# Running Example
# cd $SOFTWARE_INSTALL_DIR/openpose
# ./build/examples/openpose/openpose.bin --video examples/media/video.avi

then run following command in terminal

sudo bash install.sh

Answer 4

Using cuda 12 fixed it for me.