From d8dd2e28f33c5f92c3de34b2fbc82ad565e56a0b Mon Sep 17 00:00:00 2001 From: Ho Duc Hieu <150573299+hieu-jan@users.noreply.github.com> Date: Sat, 6 Jan 2024 12:52:38 +0700 Subject: [PATCH 1/5] docs: improve gpu not used --- .../07-troubleshooting/03-gpu-not-used.mdx | 136 ++++++++++++------ 1 file changed, 95 insertions(+), 41 deletions(-) diff --git a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx index edf29fad4..849142f10 100644 --- a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx +++ b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx @@ -11,45 +11,57 @@ keywords: [ no-subscription fee, large language model, troubleshooting, + using GPU, ] --- -## Requirements for running Jan App in GPU mode on Windows and Linux +This guide provides steps to troubleshoot and resolve issues when Jan app does not utilize the GPU on Windows and Linux systems. + +## Requirements for Running Jan in Gpu Mode on Windows and Linux + - You must have an NVIDIA driver that supports CUDA 11.4 or higher. Refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). - To check if the NVIDIA driver is installed, open PowerShell or Terminal and enter the following command: - ```bash - nvidia-smi - ``` - If you see a result similar to the following, you have successfully installed the NVIDIA driver: - ```bash - +-----------------------------------------------------------------------------+ - | NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 | - |-------------------------------+----------------------+----------------------+ - | 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 GeForce ... Off | 00000000:01:00.0 On | N/A | - | 0% 51C P8 10W / 170W | 364MiB / 7982MiB | 0% Default | - | | | N/A | - +-------------------------------+----------------------+----------------------+ - ``` + To check if the NVIDIA driver is installed, open PowerShell or Terminal and enter the following command: + + ```bash + nvidia-smi + ``` + + If you see a result similar to the following, you have successfully installed the NVIDIA driver: + + ```bash + +-----------------------------------------------------------------------------+ + | NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 | + |-------------------------------+----------------------+----------------------+ + | 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 GeForce ... Off | 00000000:01:00.0 On | N/A | + | 0% 51C P8 10W / 170W | 364MiB / 7982MiB | 0% Default | + | | | N/A | + +-------------------------------+----------------------+----------------------+ + ``` - You must have CUDA 11.4 or higher (refer [here](https://developer.nvidia.com/cuda-toolkit-archive)). - To check if CUDA is installed, open PowerShell or Terminal and enter the following command: - ```bash - nvcc --version - ``` - If you see a result similar to the following, you have successfully installed CUDA: - ```bash - nvcc: NVIDIA (R) Cuda compiler driver + To check if CUDA is installed, open PowerShell or Terminal and enter the following command: - Cuda compilation tools, release 11.4, V11.4.100 - Build cuda_11.4.r11.4/compiler.30033411_0 - ``` + ```bash + nvcc --version + ``` + + If you see a result similar to the following, you have successfully installed CUDA: + + ```bash + nvcc: NVIDIA (R) Cuda compiler driver + + Cuda compilation tools, release 11.4, V11.4.100 + Build cuda_11.4.r11.4/compiler.30033411_0 + ``` - Specifically for Linux: + - you must have `gcc-11`, `g++-11`, `cpp-11` or higher, refer [here](https://gcc.gnu.org/projects/cxx-status.html#cxx17). For Ubuntu, you can install g++ 11 by following the instructions [here](https://linuxconfig.org/how-to-switch-between-multiple-gcc-and-g-compiler-versions-on-ubuntu-20-04-lts-focal-fossa). + ```bash # Example for ubuntu # Add the following PPA repository @@ -69,7 +81,9 @@ keywords: [ # Check the default g++ version g++ --version ``` + - You must add the `.so` libraries of CUDA to the `LD_LIBRARY_PATH` environment variable, refer [here](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions). + ```bash # Example for ubuntu with CUDA 11.4 sudo nano /etc/environment @@ -80,7 +94,8 @@ keywords: [ # Save and exit # Restart your computer or log out and log in again, the changes will take effect ``` -## How to switch mode CPU/GPU Jan app + +## Switching Between CPU/GPU Modes in Jan By default, Jan app will run in CPU mode. When starting Jan app, the program will automatically check if your computer meets the requirements to run in GPU mode. If it does, we will automatically enable GPU mode and pick the GPU has highest VGRAM for you (feature allowing users to select one or more GPU devices for use - currently in planning). You can check whether you are using CPU mode or GPU mode in the settings/advance section of Jan app. (see image below). ![](../../../static/img/usage/jan-gpu-enable-setting.png) @@ -92,26 +107,65 @@ If you have GPU mode but it is not enabled by default, the following possibiliti 3. You have not installed a CUDA compatible driver, refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver), and you must add the `.so` libraries of CUDA and the CUDA compatible driver to the `LD_LIBRARY_PATH` environment variable, refer [here](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions). For Windows, add the `.dll` libraries of CUDA and the CUDA compatible driver to the `PATH` environment variable. Usually, when installing CUDA on Windows, this environment variable is automatically added, but if you do not see it, you can add it manually by referring [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#environment-setup). -## To check the current GPU-related settings that Jan app has detected, you can go to the Settings/Advanced section as shown in the image below. -![](../../../static/img/usage/jan-open-home-directory.png) -![](../../../static/img/usage/jan-open-settings-1.png) -![](../../../static/img/usage/jan-open-settings-2.png) -![](../../../static/img/usage/jan-open-settings-3.png) +## Checking GPU Settings in Jan -When you have an issue with GPU mode, share the `settings.json` with us will help us to solve the problem faster. +To verify the current GPU-related settings that Jan has detected, navigate to `Settings` > `Advanced` > `Open App Directory` -## Tested on +![OpenAppDirectory](../../../static/img/usage/jan-open-home-directory.png) + +Then, open the `settings.json` file under the `settings` folder. The following is an example of the `settings.json` file: + +```json title="~/jan/settings/settings.json" +{ + "notify": true, + "run_mode": "gpu", + "nvidia_driver": { + "exist": true, + "version": "531.18" + }, + "cuda": { + "exist": true, + "version": "12" + }, + "gpus": [ + { + "id": "0", + "vram": "12282" + }, + { + "id": "1", + "vram": "6144" + }, + { + "id": "2", + "vram": "6144" + } + ], + "gpu_highest_vram": "0" +} +``` + +:::tip + +Troubleshooting tips: + +- Ensure `nvidia_driver` and `cuda` fields indicates that requirements software are installed. +- If `gpus` field is empty or does not list your GPU, verify the installation of the NVIDIA driver and CUDA toolkit. +- For futher assistance, please share the `settings.json` with us. + +::: + +## Tested Configurations - Windows 11 Pro 64-bit, NVIDIA GeForce RTX 4070ti GPU, CUDA 12.2, NVIDIA driver 531.18 (Bare metal) - Ubuntu 22.04 LTS, NVIDIA GeForce RTX 4070ti GPU, CUDA 12.2, NVIDIA driver 545 (Bare metal) - Ubuntu 18.04 LTS, NVIDIA GeForce GTX 1660ti GPU, CUDA 12.1, NVIDIA driver 535 (Proxmox VM passthrough GPU) - Ubuntu 20.04 LTS, NVIDIA GeForce GTX 1660ti GPU, CUDA 12.1, NVIDIA driver 535 (Proxmox VM passthrough GPU) - -## If you are experiencing this issue +## Common Issues and Solutions 1. If the issue persists, please install the [Nightly version](/install/nightly) instead. -1. If the issue persists, ensure your (V)RAM is accessible by the application. Some folks have virtual RAM and needs additional configuration. +2. If the issue persists, ensure your (V)RAM is accessible by the application. Some folks have virtual RAM and need additional configuration. -1. Get help in [Jan Discord](https://discord.gg/mY69SZaMaC). +3. Get help in [Jan Discord](https://discord.gg/mY69SZaMaC). From 4802d19a0ff2e6e4d00cefeb3251c161584776bc Mon Sep 17 00:00:00 2001 From: Ho Duc Hieu <150573299+hieu-jan@users.noreply.github.com> Date: Sat, 6 Jan 2024 13:48:07 +0700 Subject: [PATCH 2/5] docs: refactor jan not used gpu --- .../07-troubleshooting/03-gpu-not-used.mdx | 152 ++++++++++-------- 1 file changed, 85 insertions(+), 67 deletions(-) diff --git a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx index 849142f10..d6b402bcd 100644 --- a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx +++ b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx @@ -19,101 +19,119 @@ This guide provides steps to troubleshoot and resolve issues when Jan app does n ## Requirements for Running Jan in Gpu Mode on Windows and Linux -- You must have an NVIDIA driver that supports CUDA 11.4 or higher. Refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). - To check if the NVIDIA driver is installed, open PowerShell or Terminal and enter the following command: +### NVIDIA Driver - ```bash - nvidia-smi - ``` +Ensure that you have installed the NVIDIA driver that supports CUDA 11.4 or higher. For a detailed of CUDA compatibility, please refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). - If you see a result similar to the following, you have successfully installed the NVIDIA driver: +To verify, open PowerShell or Terminal and enter the following command: - ```bash - +-----------------------------------------------------------------------------+ - | NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 | - |-------------------------------+----------------------+----------------------+ - | 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 GeForce ... Off | 00000000:01:00.0 On | N/A | - | 0% 51C P8 10W / 170W | 364MiB / 7982MiB | 0% Default | - | | | N/A | - +-------------------------------+----------------------+----------------------+ - ``` +```bash +nvidia-smi +``` -- You must have CUDA 11.4 or higher (refer [here](https://developer.nvidia.com/cuda-toolkit-archive)). - To check if CUDA is installed, open PowerShell or Terminal and enter the following command: +If you see a result similar to the following, you have successfully installed the NVIDIA driver: - ```bash - nvcc --version - ``` +```bash ++-----------------------------------------------------------------------------+ +| NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 | +|-------------------------------+----------------------+----------------------+ +| 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 GeForce ... Off | 00000000:01:00.0 On | N/A | +| 0% 51C P8 10W / 170W | 364MiB / 7982MiB | 0% Default | +| | | N/A | ++-------------------------------+----------------------+----------------------+ +``` - If you see a result similar to the following, you have successfully installed CUDA: +### CUDA Toolkit - ```bash - nvcc: NVIDIA (R) Cuda compiler driver +Ensure that you have installed the CUDA toolkit that is compatible with your NVIDIA driver. For a detailed of CUDA compatibility, please refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). - Cuda compilation tools, release 11.4, V11.4.100 - Build cuda_11.4.r11.4/compiler.30033411_0 - ``` +To verify, open PowerShell or Terminal and enter the following command: -- Specifically for Linux: +```bash +nvcc --version +``` - - you must have `gcc-11`, `g++-11`, `cpp-11` or higher, refer [here](https://gcc.gnu.org/projects/cxx-status.html#cxx17). For Ubuntu, you can install g++ 11 by following the instructions [here](https://linuxconfig.org/how-to-switch-between-multiple-gcc-and-g-compiler-versions-on-ubuntu-20-04-lts-focal-fossa). +If you see a result similar to the following, you have successfully installed CUDA: - ```bash - # Example for ubuntu - # Add the following PPA repository - sudo add-apt-repository ppa:ubuntu-toolchain-r/test - # Update the package list - sudo apt update - # Install g++ 11 - sudo apt-get install -y gcc-11 g++-11 cpp-11 +```bash +nvcc: NVIDIA (R) Cuda compiler driver - # Update the default g++ version - sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 110 \ - --slave /usr/bin/g++ g++ /usr/bin/g++-11 \ - --slave /usr/bin/gcov gcov /usr/bin/gcov-11 \ - --slave /usr/bin/gcc-ar gcc-ar /usr/bin/gcc-ar-11 \ - --slave /usr/bin/gcc-ranlib gcc-ranlib /usr/bin/gcc-ranlib-11 - sudo update-alternatives --install /usr/bin/cpp cpp /usr/bin/cpp-11 110 - # Check the default g++ version - g++ --version - ``` +Cuda compilation tools, release 11.4, V11.4.100 +Build cuda_11.4.r11.4/compiler.30033411_0 +``` - - You must add the `.so` libraries of CUDA to the `LD_LIBRARY_PATH` environment variable, refer [here](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions). +### Additional Requirements for Linux - ```bash - # Example for ubuntu with CUDA 11.4 - sudo nano /etc/environment - # Add /usr/local/cuda-11.4/bin to the PATH environment variable - the first line - # Add the following line to the end of the file - LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64 +**GCC and G++ Version**: Ensure that you have installed `gcc-11`, `g++-11`, `cpp-11` or higher, refer [here](https://gcc.gnu.org/projects/cxx-status.html#cxx17). For Ubuntu, you can install g++ 11 by following the instructions [here](https://linuxconfig.org/how-to-switch-between-multiple-gcc-and-g-compiler-versions-on-ubuntu-20-04-lts-focal-fossa). - # Save and exit - # Restart your computer or log out and log in again, the changes will take effect - ``` +```bash +# Example for ubuntu +# Add the following PPA repository +sudo add-apt-repository ppa:ubuntu-toolchain-r/test +# Update the package list +sudo apt update +# Install g++ 11 +sudo apt-get install -y gcc-11 g++-11 cpp-11 + +# Update the default g++ version +sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 110 \ + --slave /usr/bin/g++ g++ /usr/bin/g++-11 \ + --slave /usr/bin/gcov gcov /usr/bin/gcov-11 \ + --slave /usr/bin/gcc-ar gcc-ar /usr/bin/gcc-ar-11 \ + --slave /usr/bin/gcc-ranlib gcc-ranlib /usr/bin/gcc-ranlib-11 +sudo update-alternatives --install /usr/bin/cpp cpp /usr/bin/cpp-11 110 +# Check the default g++ version +g++ --version +``` + +**Post-Installation Actions**: You must add the `.so` libraries of CUDA to the `LD_LIBRARY_PATH` environment variable by following the [Post-installation Actions instruction](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions). + +```bash +# Example for ubuntu with CUDA 11.4 +sudo nano /etc/environment +# Add /usr/local/cuda-11.4/bin to the PATH environment variable - the first line +# Add the following line to the end of the file +LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64 + +# Save and exit +# Restart your computer or log out and log in again, the changes will take effect +``` ## Switching Between CPU/GPU Modes in Jan -By default, Jan app will run in CPU mode. When starting Jan app, the program will automatically check if your computer meets the requirements to run in GPU mode. If it does, we will automatically enable GPU mode and pick the GPU has highest VGRAM for you (feature allowing users to select one or more GPU devices for use - currently in planning). You can check whether you are using CPU mode or GPU mode in the settings/advance section of Jan app. (see image below). ![](../../../static/img/usage/jan-gpu-enable-setting.png) +By default, Jan runs in CPU mode. Upon start, Jan checks if your system is capable of running in GPU mode. If compatible, GPU mode is enabled automatically, and the GPU with the highest VRAM is selected. This setting can be verified in the `Settings` > `Advanced` section. -If you have GPU mode but it is not enabled by default, the following possibilities may exist, you can follow the next steps to fix the error: +![](../../../static/img/usage/jan-gpu-enable-setting.png) -1. You have not installed the NVIDIA driver, refer to the NVIDIA driver that supports CUDA 11.4 [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). +If you find that GPU mode is available but not enabled by default, consider the following troubleshooting steps: -2. You have not installed the CUDA toolkit or your CUDA toolkit is not compatible with the NVIDIA driver, refer to CUDA compatibility [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). +:::tip -3. You have not installed a CUDA compatible driver, refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver), and you must add the `.so` libraries of CUDA and the CUDA compatible driver to the `LD_LIBRARY_PATH` environment variable, refer [here](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions). For Windows, add the `.dll` libraries of CUDA and the CUDA compatible driver to the `PATH` environment variable. Usually, when installing CUDA on Windows, this environment variable is automatically added, but if you do not see it, you can add it manually by referring [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#environment-setup). +1. Check if you have installed the NVIDIA driver that supports CUDA 11.4 or higher. For a detailed of CUDA compatibility, please refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). + +2. Ensure that the CUDA toolkit is installed and compatible with your NVIDIA driver. For a detailed of CUDA compatibility, please refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). + +3. For Linux, it's crucial to add the `.so` libraries of CUDA and the CUDA compatible driver to the `LD_LIBRARY_PATH` environment variable. For Windows, users should ensure that the `.dll` libraries of CUDA and the CUDA compatible driver are included in the PATH environment variable. Usually when installing CUDA on Windows, this environment variable is automatically added, but if you do not see it, you can add it manually by referring [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#environment-setup). + +::: ## Checking GPU Settings in Jan -To verify the current GPU-related settings that Jan has detected, navigate to `Settings` > `Advanced` > `Open App Directory` +1. To check the current GPU settings detected by Jan, navigate to `Settings` > `Advanced` > `Open App Directory` + +

![OpenAppDirectory](../../../static/img/usage/jan-open-home-directory.png) -Then, open the `settings.json` file under the `settings` folder. The following is an example of the `settings.json` file: +

+ +2. Open the `settings.json` file under the `settings` folder. The following is an example of the `settings.json` file: + +

```json title="~/jan/settings/settings.json" { From d697f43297dd06a2e9cd8649d36640d8a9db9810 Mon Sep 17 00:00:00 2001 From: Ho Duc Hieu <150573299+hieu-jan@users.noreply.github.com> Date: Sat, 6 Jan 2024 13:58:49 +0700 Subject: [PATCH 3/5] docs: re-order tested configurations --- docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx index d6b402bcd..f3ce489ea 100644 --- a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx +++ b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx @@ -105,7 +105,7 @@ LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64 By default, Jan runs in CPU mode. Upon start, Jan checks if your system is capable of running in GPU mode. If compatible, GPU mode is enabled automatically, and the GPU with the highest VRAM is selected. This setting can be verified in the `Settings` > `Advanced` section. -![](../../../static/img/usage/jan-gpu-enable-setting.png) +![jan-gpu-enable-setting](../../../static/img/usage/jan-gpu-enable-setting.png) If you find that GPU mode is available but not enabled by default, consider the following troubleshooting steps: @@ -177,8 +177,8 @@ Troubleshooting tips: - Windows 11 Pro 64-bit, NVIDIA GeForce RTX 4070ti GPU, CUDA 12.2, NVIDIA driver 531.18 (Bare metal) - Ubuntu 22.04 LTS, NVIDIA GeForce RTX 4070ti GPU, CUDA 12.2, NVIDIA driver 545 (Bare metal) -- Ubuntu 18.04 LTS, NVIDIA GeForce GTX 1660ti GPU, CUDA 12.1, NVIDIA driver 535 (Proxmox VM passthrough GPU) - Ubuntu 20.04 LTS, NVIDIA GeForce GTX 1660ti GPU, CUDA 12.1, NVIDIA driver 535 (Proxmox VM passthrough GPU) +- Ubuntu 18.04 LTS, NVIDIA GeForce GTX 1660ti GPU, CUDA 12.1, NVIDIA driver 535 (Proxmox VM passthrough GPU) ## Common Issues and Solutions From 18a521e84c68d5f3286b337bf7eb27d85641f885 Mon Sep 17 00:00:00 2001 From: Ho Duc Hieu <150573299+hieu-jan@users.noreply.github.com> Date: Sat, 6 Jan 2024 14:03:08 +0700 Subject: [PATCH 4/5] docs: change better title --- docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx index f3ce489ea..e3818d603 100644 --- a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx +++ b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx @@ -64,7 +64,7 @@ Cuda compilation tools, release 11.4, V11.4.100 Build cuda_11.4.r11.4/compiler.30033411_0 ``` -### Additional Requirements for Linux +### Specific Requirements for Linux **GCC and G++ Version**: Ensure that you have installed `gcc-11`, `g++-11`, `cpp-11` or higher, refer [here](https://gcc.gnu.org/projects/cxx-status.html#cxx17). For Ubuntu, you can install g++ 11 by following the instructions [here](https://linuxconfig.org/how-to-switch-between-multiple-gcc-and-g-compiler-versions-on-ubuntu-20-04-lts-focal-fossa). From 5f641c881abb1ea4a503b4b48dc464380dab21b4 Mon Sep 17 00:00:00 2001 From: Ho Duc Hieu <150573299+hieu-jan@users.noreply.github.com> Date: Sat, 6 Jan 2024 14:18:23 +0700 Subject: [PATCH 5/5] docs: correct small typo --- .../docs/guides/07-troubleshooting/03-gpu-not-used.mdx | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx index e3818d603..64f20ee3e 100644 --- a/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx +++ b/docs/docs/guides/07-troubleshooting/03-gpu-not-used.mdx @@ -17,7 +17,7 @@ keywords: [ This guide provides steps to troubleshoot and resolve issues when Jan app does not utilize the GPU on Windows and Linux systems. -## Requirements for Running Jan in Gpu Mode on Windows and Linux +## Requirements for Running Jan in GPU Mode on Windows and Linux ### NVIDIA Driver @@ -115,7 +115,7 @@ If you find that GPU mode is available but not enabled by default, consider the 2. Ensure that the CUDA toolkit is installed and compatible with your NVIDIA driver. For a detailed of CUDA compatibility, please refer [here](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver). -3. For Linux, it's crucial to add the `.so` libraries of CUDA and the CUDA compatible driver to the `LD_LIBRARY_PATH` environment variable. For Windows, users should ensure that the `.dll` libraries of CUDA and the CUDA compatible driver are included in the PATH environment variable. Usually when installing CUDA on Windows, this environment variable is automatically added, but if you do not see it, you can add it manually by referring [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#environment-setup). +3. For Linux, it's crucial to add the `.so` libraries of CUDA and the CUDA compatible driver to the `LD_LIBRARY_PATH` environment variable. For Windows, users should ensure that the `.dll` libraries of CUDA and the CUDA compatible driver are included in the PATH environment variable. Usually, when installing CUDA on Windows, this environment variable is automatically added, but if you do not see it, you can add it manually by referring [here](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#environment-setup). ::: @@ -167,9 +167,9 @@ If you find that GPU mode is available but not enabled by default, consider the Troubleshooting tips: -- Ensure `nvidia_driver` and `cuda` fields indicates that requirements software are installed. -- If `gpus` field is empty or does not list your GPU, verify the installation of the NVIDIA driver and CUDA toolkit. -- For futher assistance, please share the `settings.json` with us. +- Ensure the `nvidia_driver` and `cuda` fields indicate that requirements software are installed. +- If the `gpus` field is empty or does not list your GPU, verify the installation of the NVIDIA driver and CUDA toolkit. +- For further assistance, please share the `settings.json` with us. :::