Final run.

workflow/config.ini

 [container]
 ogs_commit: cdb32989b54b47f059c697cc12fef62338c9702c
-guix_channel_ogs_commit: 901d7522bfdb710814f26f7858fb55f57769371f
-guix_channel_commit: ebb715aabfc4e59ed14b964ac7fdd2a9f9f44526
+guix_channel_ogs_commit: f13a74511a5d9cf245940b71226c2f4e5ec81ab7
+guix_channel_commit: 522732d5c15e44fc9e061f36a41f7129edfee66f
 guix_tune_option: --tune=skylake-avx512

workflow/requirements.txt

-aiida-core~=2.6
+aiida-core[rest]~=2.6
 #git+https://github.com/aiidateam/aiida-core.git@main#egg=aiida-core
 aiida-shell>=0.8.0
 pandas
-Jinja2
+Jinja2
\ No newline at end of file

workflow/run.py

@@ -3,14 +3,13 @@ import warnings
 from pathlib import Path
 
 import aiida
-from aiida.engine import run, submit, await_processes, run_get_node
+from aiida.engine import run, submit, await_processes
 from aiida.orm import load_computer, Bool
 from aiida.orm.utils.loaders import load_node
 from aiida.tools.visualization.graph import Graph
 
 from create_container import create_container
 from run_mpi_tests import run_mpi_tests
-# from create_container_workchain import CreateContainerWorkChain
 from helper import JobSettings, launch_batch_job, compare_for_equality
 from aiida.plugins.factories import DataFactory
 
@@ -30,17 +29,19 @@ warnings.filterwarnings(action='ignore',module='.*paramiko.*')
 
 def run_arehs(container_file, hpc_envs, graph_nodes=None): # build_envs, hpc_envs, graph_nodes
     nodes = []
-    job_settings = Dict(dict=JobSettings(ntasks=1, cpus_per_task=48, time=120, mem_per_cpu="2GB")._asdict())  # 8, 10
     for hpc_env in hpc_envs.get_list():
+        computer = load_computer(hpc_env)
+        tasks = computer.get_default_mpiprocs_per_machine()
+        job_settings = Dict(
+            dict=JobSettings(ntasks=tasks, cpus_per_task=1, time=120, mem_per_cpu="2GB")._asdict())  # 8, 10
         node = submit(
             RunWorkflowWorkChain,
             container_file=container_file,
             computer_name=Str(hpc_env),
             input_repo="https://gitlab.opengeosys.org/bilke/dgr.git",
-            # TODO: 3D coupled, run the following
-            workflow_command="snakemake --cores 48 --profile profiles/developer \
-            results/plot/3D/Salz-Kissen_prism-id_1-xres_400/glacialcycle/simTH/{{temporal,spatial}}/report.pdf \
-            results/plot/2D/{{Ton-Nord,Ton-Sued}}_prism-id_{{1,2}}-xres_200/glacialcycle/simTHM/{{temporal,spatial}}/report.pdf \
+            workflow_command=f"snakemake --cores {tasks} --profile profiles/developer " +
+            "results/plot/3D/Salz-Kissen_prism-id_1-xres_400/glacialcycle/simTH/parts_8/{{temporal,spatial}}/report.pdf \
+            results/plot/2D/{{Ton-Nord,Ton-Sued}}_prism-id_{{1,2}}-xres_200/glacialcycle/simTHM/parts_8/{{temporal,spatial}}/report.pdf \
             results/plot/2D/{{Salz-Kissen,Salz-flach,Ton-Nord,Ton-Sued}}_prism-id_{{1,2}}-xres_200/glacialcycle/simT{{,H}}/{{temporal,spatial}}/report.pdf",
             # parts_8
             job_settings=job_settings,
@@ -96,7 +97,7 @@ def run_ogs_sim(container_file, hpc_envs, graph_nodes=None):
 
         job_settings = Dict(
             dict=JobSettings(
-                ntasks=partitions.value, mem_per_cpu="2G", time=5
+                ntasks=partitions.value, mem_per_cpu="2G", time=20
             )._asdict()
         )
         input_folder = FolderData(tree=Path("../tests/LiquidFlowOnCube").absolute())
@@ -133,14 +134,19 @@ if __name__ == "__main__":
     aiida.load_profile()
     graph_nodes = []  # collect interesting nodes for graph generation
 
-    build_envs = List(list=["envinf3", "envinf4"])  # , "envinf5", "nuc"
-    # if False:
-    #     ogs_container_file = create_container("ogs-template.scm", build_envs)
-    #     arehs_container_file = create_container("arehs-template.scm", build_envs, "ogs-petsc-mkl", compare_hashes=False)
+    # build_envs = List(list=["envinf3", "envinf4"])  # , "envinf5", "nuc"
+    build_envs = List(list=["envinf4", "envinf6"]) # "envinf3"
+    ogs_container_file = create_container("ogs-template.scm", build_envs)
+
+    # guix hash -S nar ...
+    # tar.gz hash: 1dw5kqd4qww2bjcxkafimfbx23a9slzsdrkm1dm8kxwiiiscq1gi
+    # squashfs hash: 1rl7dychp2rr88g1f2p29mlrpp7gjh1jmi5jz4ww5dgi7g999qm5
+    # squashfs size: 734.2 MiB
+    #ogs_container_file = load_node(pk=53247)
 
-    ogs_container_file = load_node(pk=50289)
-    arehs_container_file = load_node(pk=51510)
-    # arehs_container_file = create_container("arehs-template.scm", build_envs, "ogs-petsc-mkl", compare_hashes=False)
+    # squashfs size: 2182.7 MiB
+    #arehs_container_file = load_node(pk=53317)
+    arehs_container_file = create_container("arehs-template.scm", build_envs, "ogs-petsc-mkl", compare_hashes=False)
 
     hpc_envs = List(
         list=[
@@ -150,14 +156,16 @@ if __name__ == "__main__":
         ]
     )
 
+    ### AREHS workflow
+    run_arehs(arehs_container_file, hpc_envs, graph_nodes)
+
     ### mpi bandwidth benchmark and simple petsc sim
     run_mpi_tests(ogs_container_file, hpc_envs, graph_nodes)
 
     #### liquid_flow.prj with structured mesh ####
     run_ogs_sim(ogs_container_file, hpc_envs, graph_nodes)
 
-    ### AREHS workflow
-    run_arehs(arehs_container_file, hpc_envs, graph_nodes)
+    #graph_nodes = [load_node(pk=53226), load_node(pk=53296), load_node(pk=54696), load_node(pk=54394), load_node(pk=54452), load_node(pk=54369)]
 
     # Render diagram
     graph = Graph(node_sublabel_fn=custom_node_sublabels)