Merge pull request #812 from wjr-timmers/ada-draft

Ada draft

Author: peer35

tools/ada/_sidebar.yml

@@ -13,6 +13,7 @@ website:
           - tools/ada/contact_support.qmd
           - tools/ada/quick_start.qmd
           - tools/ada/hpc-updates.qmd
+          - tools/ada/hpc-training.qmd
           - section: Documentation
             contents:
             - tools/ada/login.qmd
@@ -33,3 +34,4 @@ website:
                 contents:
                 - tools/ada/1-R-multiprocessing.qmd
             - tools/ada/hpc-101.qmd
+            - tools/ada/faq.qmd

tools/ada/faq.qmd

@@ -0,0 +1,20 @@
+---
+title: FAQ
+date: last-modified
+---
+
+### Why is my job running much longer than expected?
+
+- Always check if your script is really benefitting from parallelism. Are you really using all the threads/cores you got allocated via slurm? (log in the compute node via ssh and check the processes running `htop -u *vunetid*`). 
+- Note that the cpu in high performance servers does not necessarily clocks faster than your laptop cpu, the real performance gain comes from parallelism. 
+- Is your dataset very big? Always use the local scratch space.
+- Use profilers to assess your code for bottlenecks. (Python: cProfile, R: profvis, C++: perf)
+
+### Why does the software I installed via conda return unexpected errors? 
+
+Conda injects settings in your .bashrc file once initialized and prepends directories to your $PATH variables. 
+This can result in dependency errors for software that is actually relying on native system dependencies. 
+
+
+
+

tools/ada/hpc-training.qmd

@@ -0,0 +1,24 @@
+---
+title: HPC Training Courses
+---
+
+Throughout the year, there are various opportunities to get more acquainted with HPC through several workshops and courses: 
+
+### Yearly HPC Winter Course VU
+
+Every year, the VU HPC Winter Course is organized in collaboration with SURF. For more information see [the course page](https://vu.nl/en/education/phd-courses/high-performance-computing-hpc-course) . 
+
+### SURF Training Courses
+
+[SURF Calendar](https://www.surf.nl/en/agenda)
+
+
+### EuroCC Project Training Courses
+
+[EuroCC Project Training Courses](https://eurocc-netherlands.nl/training/)
+
+
+### Taxila: hub for research data training courses and events
+
+[Taxila](https://taxila.nl/events)
+

tools/ada/login.qmd

@@ -6,7 +6,20 @@ date: last-modified
 - You must be comfortable with Bash and basic HPC concepts. See: [Unix Shell](https://swcarpentry.github.io/shell-novice/) and [HPC Introduction](https://carpentries-incubator.github.io/hpc-intro/).
 :::
 
-## SSH Login Setup (Linux and macOS, recommended)
+## SSH Password login
+
+To log in with the password you've received from ITVO, first connect to EduVPN or use ssh.data.vu.nl. Once connected, you can directly log in via terminal: 
+
+```sh
+ssh *vunetid*@ada.labs.vu.nl
+```
+
+On your first login, you are prompted to change your password. Follow the interactive prompts, filling in the old password first, followed by the new password + confirmation. 
+
+If you need assistance in resetting your password, you can reach out to ITvO (itvo.it@vu.nl)
+
+
+## SSH Key Login Setup (Linux and macOS, recommended)
 
 Here we will set-up passwordless SSH access to ADA. 
 
@@ -111,7 +124,7 @@ Here we provide the steps to connect to the cluster using MobaXterm.
 ## Login node policy
 
 ::: {.callout-danger title="Strict rule on login nodes"}
-Login nodes are only for light tasks: edit scripts, manage files, submit SLURM jobs. Do not run notebooks, VS Code Server, heavy compiles, or long‑running programs here.
+Login nodes are only for light tasks: edit scripts, manage files, submit SLURM jobs. Do not run notebooks, VS Code Server, heavy compiles, or long‑running programs here. User sessions that do not adhere to this policy, are automatically logged off every 5 minutes. 
 :::
 
 Use interactive nodes (`inter01`–`inter04`) for heavier interactive work, or see Open OnDemand in the Quick Start.

tools/ada/software.qmd

@@ -11,6 +11,7 @@ ADA offers several supported ways to access software depending on how much contr
 - [`Pixi`](#pixi-environments) – lightweight multi-language environments for reproducible projects.
 - [`Conda`/`virtualenv`](#conda-and-virtualenv) – established Python-first tooling for legacy workflows.
 - [`Apptainer`](#apptainer-containers) – container images for bespoke stacks or portable workflows.
+- [`Git`](#git) - version control software
 
 ::: {.callout-note title="Need a quick recommendation?"}
 Use modules whenever a supported version exists. Choose Pixi when you need custom packages or multi-language environments, fall back to Conda or virtualenv if you already rely on them, and build an Apptainer container when you must control the full user-space stack.
@@ -89,10 +90,23 @@ If you identify software that would benefit a broad cross-section of ADA users,
 Request extra modules **only** when they will measurably help many researchers. For niche or project-specific tools, use Pixi, Conda, or Apptainer so cluster admins can focus limited time on maintaining the shared stack.
 :::
 
+### European Environment for Scientific Software Installations (EESSI)
+
+The European Environment for Scientific Software Installations (EESSI, pronounced as "easy") is a collaboration between different European partners in HPC community. The goal of this project is to build a common stack of scientific software installations for HPC systems and beyond, including laptops, personal workstations and cloud infrastructure.
+
+A major advantage of the EESSI stack is that it provides an extensive library of software specifically optimized for various CPU and GPU architectures, significantly improving the computational performance of your code.
+
+To use EESSI on ADA, load in either the eessi-2023.06 or eessi-2026.06 stack, e.g.:
+
+```sh
+[abc123@login1 ~]$ module load eessi-2025.06
+```
+
 ### References
 
 - [Lmod user guide](https://lmod.readthedocs.io/en/latest/)
 - [Carpentries HPC modules lesson](https://carpentries-incubator.github.io/hpc-intro/15-modules/index.html)
+- [EESSI](https://www.eessi.io/docs/)
 
 ## Pixi Environments
 
@@ -254,6 +268,12 @@ Minimal patterns for running distributed and GPU workloads from SLURM through Ap
   - References: Apptainer GPU docs: https://apptainer.org/docs/user/main/gpu.html
 :::
 
+
+## Git
+
+Git is pre-installed on every login/inter/compute node by default. If you need a specific release of git, use `$ module spider git` to check out all installed module versions.
+
+
 ### References
 
 - [Apptainer user guide](https://apptainer.org/docs/user/main/quick_start.html)