diff --git a/docs/source/_static/swc-wiki-warning.md b/docs/source/_static/swc-wiki-warning.md index cbb3e28..968ffbc 100644 --- a/docs/source/_static/swc-wiki-warning.md +++ b/docs/source/_static/swc-wiki-warning.md @@ -1,6 +1,6 @@ :::{warning} Some links within this document point to the -[SWC internal wiki](https://wiki.ucl.ac.uk/display/SI/SWC+Intranet), +[SWC internal wiki](https://liveuclac.sharepoint.com/sites/SWCIntranet), which is only accessible from within the SWC network. We recommend opening these links in a new tab. ::: diff --git a/docs/source/conf.py b/docs/source/conf.py index 7cb3deb..ce9c7a5 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -84,7 +84,7 @@ # Ignore certain URLs from being checked linkcheck_ignore = [ "https://neuromorpho.org/", - "https://wiki.ucl.ac.uk/", # ignore everything on the internal wiki + "https://liveuclac.sharepoint.com/", # ignore everything on the internal wiki "https://linux.die.net/man/1/rsync", "https://www.uclb.com/", "https://support.zadarastorage.com", diff --git a/docs/source/data_analysis/HPC-module-SLEAP.md b/docs/source/data_analysis/HPC-module-SLEAP.md index f62553b..79f2151 100644 --- a/docs/source/data_analysis/HPC-module-SLEAP.md +++ b/docs/source/data_analysis/HPC-module-SLEAP.md @@ -89,7 +89,7 @@ To minimise the risk of issues due to incompatibilities between versions, ensure ### Mount the SWC filesystem on your local PC/laptop The rest of this guide assumes that you have mounted the SWC filesystem on your local PC/laptop. If you have not done so, please follow the relevant instructions on the -[SWC internal wiki](https://wiki.ucl.ac.uk/display/SSC/SWC+Storage+Platform+Overview). +[SWC internal wiki](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-SWC-Storage-Platform-Overview-198905992.aspx). We will also assume that the data you are working with are stored in a `ceph` directory to which you have access to. In the rest of this guide, we will use the path @@ -341,7 +341,7 @@ $ cat slurm.gpu-sr670-20.3445652.err If you encounter out-of-memory errors, keep in mind that there two main sources of memory usage: - CPU memory (RAM), specified via the `--mem` argument in the SLURM batch script. This is the memory used by the Python process running the training job and is shared among all the CPU cores. -- GPU memory, this is the memory used by the GPU card(s) and depends on the GPU card type you requested via the `--gres gpu:1` argument in the SLURM batch script. To increase it, you can request a specific GPU card type with more GPU memory (e.g. `--gres gpu:a4500:1`). The SWC wiki provides a [list of all GPU card types and their specifications](https://wiki.ucl.ac.uk/display/SSC/CPU+and+GPU+Platform+architecture). +- GPU memory, this is the memory used by the GPU card(s) and depends on the GPU card type you requested via the `--gres gpu:1` argument in the SLURM batch script. To increase it, you can request a specific GPU card type with more GPU memory (e.g. `--gres gpu:a4500:1`). The SWC wiki provides a [list of all GPU card types and their specifications](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-CPU-and-GPU-Platform-architecture-165449857.aspx). - If requesting more memory doesn't help, you can try reducing the size of your SLEAP models. You may tweak the model backbone architecture, or play with *Input scaling*, *Max stride* and *Batch size*. See SLEAP's [documentation](https://sleap.ai/) and [discussion forum](https://github.com/talmolab/sleap/discussions) for more details. ``` @@ -439,7 +439,7 @@ sleap-track $VIDEO_DIR/M708149_EPM_20200317_165049331-converted.mp4 \ The script is very similar to the training script, with the following differences: - The time limit `-t` is set lower, since inference is normally faster than training. This will however depend on the size of the video and the number of models used. - The requested number of cores `n` and memory `--mem` are higher. This will depend on the requirements of the specific job you are running. It's best practice to try with a scaled-down version of your data first, to get an idea of the resources needed. -- The requested GPU is of a specific kind (RTX 5000). This will again depend on the requirements of your job, as the different GPU kinds vary in GPU memory size and compute capabilities (see [the SWC wiki](https://wiki.ucl.ac.uk/display/SSC/CPU+and+GPU+Platform+architecture)). +- The requested GPU is of a specific kind (RTX 5000). This will again depend on the requirements of your job, as the different GPU kinds vary in GPU memory size and compute capabilities (see [the SWC wiki](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-CPU-and-GPU-Platform-architecture-165449857.aspx)). - The `./train-script.sh` line is replaced by the `sleap-track` command. - The `\` character is used to split the long `sleap-track` command into multiple lines for readability. It is not necessary if the command is written on a single line. diff --git a/docs/source/programming/SLURM-arguments.md b/docs/source/programming/SLURM-arguments.md index 346ddde..33465da 100644 --- a/docs/source/programming/SLURM-arguments.md +++ b/docs/source/programming/SLURM-arguments.md @@ -105,7 +105,7 @@ If needed, the systems administrator can extend long-running jobs. :::{warning} No GPU will be allocated to you unless you specify it via the `--gres` argument (even if you are on the 'gpu' partition). To request 1 GPU of any kind, use `--gres gpu:1`. To request a specific GPU type, you have to include its name, e.g. `--gres gpu:rtx2080:1`. -You can view the available GPU types on the [SWC internal wiki](https://wiki.ucl.ac.uk/display/SSC/CPU+and+GPU+Platform+architecture). +You can view the available GPU types on the [SWC internal wiki](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-CPU-and-GPU-Platform-architecture-165449857.aspx). ::: ### Standard Output File diff --git a/docs/source/programming/SSH-SWC-cluster.md b/docs/source/programming/SSH-SWC-cluster.md index 4c3aeed..866287e 100644 --- a/docs/source/programming/SSH-SWC-cluster.md +++ b/docs/source/programming/SSH-SWC-cluster.md @@ -27,7 +27,7 @@ the connection is much more straightforward than described here ## Prerequisites - You have an SWC account and know your username and password. -- You have read the [SWC wiki's section on High Performance Computing (HPC)](https://wiki.ucl.ac.uk/display/SSC/High+Performance+Computing), especially the [Logging into the Cluster page](https://wiki.ucl.ac.uk/display/SSC/Logging+into+the+Cluster). +- You have read the [SWC wiki's section on High Performance Computing (HPC)](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-High-Performance-Computing-147954090.aspx), especially the [Logging into the Cluster page](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-Logging-into-the-Cluster-194972967.aspx). - You know the basics of using the command line, i.e. using the terminal to navigate the file system and run commands. - You have an SSH client installed on your computer. This is usually pre-installed on Linux and macOS. SSH is also available on Windows (since Windows 10), however some steps will differ. If you are a Windows user, read the note below before proceeding. @@ -130,11 +130,11 @@ a Windows or a Linux image. These machines are already part of the SWC's trusted network domain, meaning you can access the HPC cluster without having to go through the *bastion* node. -- If you are using a [managed Windows desktop](https://wiki.ucl.ac.uk/display/SSC/SWC+Desktops), +- If you are using a [managed Windows desktop](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-SWC-Desktops-147956857.aspx), you can SSH directly into the *gateway* node with `ssh hpc-gw2` from the Windows `cmd` or PowerShell. You may use that node to prepare your scripts and submit SLURM jobs. -- If you are using a [managed Linux desktop](https://wiki.ucl.ac.uk/display/SSC/Managed+Linux+Desktop), +- If you are using a [managed Linux desktop](https://liveuclac.sharepoint.com/sites/SSC/SitePages/SSC-Managed-Linux-Desktop-69502751.aspx), you can even bypass the *gateway* node. In fact, you may directly submit SLURM jobs from your terminal, without having to SSH at all. That's because managed Linux desktops use the same platform as the HPC nodes