Skip to content

Mention default recipe resources in FAQs #110

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
schlunma merged 1 commit into from
Sep 9, 2026
Merged

Mention default recipe resources in FAQs #110

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion doc/customization.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ To run custom recipes in addition to the default recipes, use
iconeval path/to/ICON_output --recipe_templates='["/path/to/recipe_1_*.yml", "/path/to/recipe_2.yml"]' --always_use_default_recipe_templates=True
```

The default recipes are designed to run effectively on 1/8 of a compute on
The default recipes are designed to run effectively on 1/8 of a compute node on
DKRZ's Levante (16 cores, 32 GB of RAM).

The following placeholders are required in the recipe templates:
Expand Down
6 changes: 4 additions & 2 deletions doc/faqs.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -234,5 +234,7 @@
This will request all memory (`--mem=0`) of a single compute node
(`--nodes=1`, `--partition=compute`) with [128 CPUs and 256 GB of main
memory](https://docs.dkrz.de/doc/levante/configuration.html). Since 1 recipe
run = 1 task and 16 CPUs per task are requested, this results in 8 (= 128 /
16) recipe runs in parallel.
run = 1 task and 16 CPUs per task are requested, this results in 8 (= 128
CPUs / 16 CPUs) recipe runs in parallel. This is an optimal setting for the
default recipes, which are designed to run effectively on 1/8 of a compute
node (16 CPUs, 32 GB of RAM).
Loading