diff --git a/Pillar_II/esm/src/dummy_prune_analysis.py b/Pillar_II/esm/src/dummy_prune_analysis.py
index 0f1b69b..98e151f 100644
--- a/Pillar_II/esm/src/dummy_prune_analysis.py
+++ b/Pillar_II/esm/src/dummy_prune_analysis.py
@@ -17,26 +17,32 @@
 CHECK_FOR_PRUNING_SLEEP_TIME_SECS = 5
 """How long should we sleep for"""
 
+# TODO: remove me later
+MEMBERS_PRUNED = [2]
+
 logger = logging.getLogger(__name__)
 
 
-@task(expid=IN)
-def esm_analysis_prune(expid: str):
+@on_failure(management='IGNORE', returns=0)
+@task(expid=IN, member=IN, returns=bool, time_out=480)
+def esm_analysis_prune(expid: str, member: int) -> bool:
     """This has to be called by PYCOMPSs as analysis.
 
     Args:
         expid: The experiment ID.
+        member: The ensemble member.
+    Returns:
+        bool: True if the ensemble member was pruned.
     """
     # N.B.: importing this results in a network query to Hecuba servers,
     #       which fails if the servers are not available.
 
     # TODO: Suvi: call the AI code here
-    member = int(expid.split('_')[1])
-    if member != 2:
-        logging.info("We only prune the ensemble member #2!")
-        return
+    if member not in MEMBERS_PRUNED:
+        logging.info(f"We only prune the ensemble members #{str(MEMBERS_PRUNED)}!")
+        return False
 
-    logging.info("Pruning ensemble member #2!")
+    logging.info(f"Pruning ensemble member #{str(member)}!")
 
     logging.info("Importing Hecuba")
     from hecuba import StorageDict  # type: ignore
@@ -58,25 +64,28 @@ class MetaDictClass(StorageDict):
         #      RuntimeError: StorageDict: missed specification.
         #      Type of Primary Key or Column undefined
 
-
     # This is an infinite-loop, with a sleep time. The execution
     # must be wrapped in an existing COMPSs or Slurm job, with a
     # walltime or some limit to control the maximum execution
     # time, and kill this task.
+    expid_member = f'{expid}_{str(member)}'
     while True:
-        logging.info(f"MetaDictClass.get_by_alias('{expid}')")
+        logging.info(f"MetaDictClass.get_by_alias('{expid_member}')")
         try:
-            mdc = MetaDictClass.get_by_alias(expid)
+            mdc = MetaDictClass.get_by_alias(expid_member)
             break
         except RuntimeError:
-            logging.info(f"Simulation {expid} not found sleeping +{CHECK_FOR_PRUNING_SLEEP_TIME_SECS} seconds...")
+            logging.info(
+                f"Simulation member {expid_member} not found sleeping +{CHECK_FOR_PRUNING_SLEEP_TIME_SECS} seconds...")
             sleep(CHECK_FOR_PRUNING_SLEEP_TIME_SECS)
 
     prune_sec = randint(10, 20)
     sleep(prune_sec)
     logging.info("Setting prune to TRUE!")
     mdc['prune'] = "true"
-    logging.info(f"Pruned {expid} after {prune_sec} seconds")
+    logging.info(f"Pruned member [{str(member)}] from experiment [{expid}] after {prune_sec} seconds")
+
+    return True
 
 
 __all__ = ['esm_analysis_prune']
diff --git a/Pillar_II/esm/src/esm_simulation.py b/Pillar_II/esm/src/esm_simulation.py
index 0554b24..ae2cb6f 100644
--- a/Pillar_II/esm/src/esm_simulation.py
+++ b/Pillar_II/esm/src/esm_simulation.py
@@ -193,6 +193,15 @@ def _run_esm(*, expid: str, model: str, prune: bool, config_parser: ConfigParser
     processes = runtime_config_parser['pycompss']['processes']
     processes_per_node = runtime_config_parser['pycompss']['processes_per_node']
 
+    # N.B.: Apparently giving all nodes to mpirun/FESOM2 results in resource
+    #       starvation as COMPSs will be trying to run a task to prune as well.
+    #       Thus, we always allocate one node less to leave it for COMPSs and
+    #       Hecuba.
+    cores_in_one_node = int(processes_per_node)
+    cores_requested = int(processes)
+    if cores_requested > cores_in_one_node:
+        processes = str(cores_requested - cores_in_one_node)
+
     # This is where we delegate the ESM execution to a model's module code
     # (e.g. FESOM2, AWICM3, etc.).
     ensemble_start_dates = runtime_config_parser['common']['ensemble_start_dates'].split(",")
@@ -206,16 +215,14 @@ def _run_esm(*, expid: str, model: str, prune: bool, config_parser: ConfigParser
             member = str(member_idx)
             task_group = f"{expid}_{start_date}_{member}"
 
+            if prune:
+                esm_analysis_prune(expid, member_idx)
+
             with TaskGroup(task_group, implicit_barrier=False):
                 # Launch each SIM, create an implicit dependence by passing the result to the next task (checkpoint).
                 number_simulations = int(runtime_config_parser['common']['chunks'])
                 logger.info(f"Total of chunks configured: {number_simulations}")
 
-                if prune:
-                    member_expid = f"{expid}_{member}"
-                    logger.info(f"Starting the ESM analysis prune for {member_expid}...")
-                    esm_analysis_prune(member_expid)
-
                 for sim in range(1, number_simulations + 1):
                     working_dir_exe = top_working_dir / start_date / member
                     log_file = str(working_dir_exe / f"fesom2_{expid}_{start_date}_{member}_{str(sim)}.out")
diff --git a/Pillar_II/esm/src/fesom2/__init__.py b/Pillar_II/esm/src/fesom2/__init__.py
index 3d8c5ab..f9d1308 100644
--- a/Pillar_II/esm/src/fesom2/__init__.py
+++ b/Pillar_II/esm/src/fesom2/__init__.py
@@ -324,7 +324,7 @@ def esm_simulation(
             StdIOStream: STDOUT
         },
         working_dir_exe={
-            Type: INOUT,
+            Type: IN,
             Prefix: "#"
         },
         returns=int)