diff --git a/README.md b/README.md
index 424fc304..42116a54 100644
--- a/README.md
+++ b/README.md
@@ -78,8 +78,8 @@ uv run pytest
 ## Environment variables
 | Environment Variable  | Description                                      | Default Value |
 |-----------------------|--------------------------------------------------|---------------|
-| `GLOBAL_UNIQUE_ID`    | Unique identifier worker in global store.        | `""` (empty string) |
-| `GLOBAL_ADDR`         | IP Address of the global store                   | `""` (empty string) |
-| `GLOBAL_PORT`         | Port number of the global store.                 | `-1` |
+| `GLOBAL_UNIQUE_ID`    | Unique identifier worker in global store.        | `None`  |
+| `GLOBAL_ADDR`         | IP Address of the global store                   | `None`  |
+| `GLOBAL_PORT`         | Port number of the global store.                 | `None` |
 | `GLOBAL_WORLD_SIZE`   | The size of the global process group.            | `1` |
 | `GLOBAL_RANK`         | Rank of the process in the global process group. | `0` |
diff --git a/scripts/simulate_multi_node_diloco.sh b/scripts/simulate_multi_node_diloco.sh
index 858c1805..cbbd8737 100755
--- a/scripts/simulate_multi_node_diloco.sh
+++ b/scripts/simulate_multi_node_diloco.sh
@@ -59,7 +59,7 @@ export GLOBAL_WORLD_SIZE=$N
 for i in $(seq 0 $(($N - 1 )))
 do
     > logs/log$i
-    TORCH_UNIQUE_ID=$i GLOBAL_RANK=$i CUDA_VISIBLE_DEVICES=$(get_cuda_devices $NUM_GPU $i) uv run torchrun --nproc_per_node=$NUM_GPU --node-rank 0 --rdzv-endpoint localhost:$((10001 + $i)) --nnodes=1  $@  > logs/log$i 2>&1 &
+    GLOBAL_UNIQUE_ID=$i GLOBAL_RANK=$i CUDA_VISIBLE_DEVICES=$(get_cuda_devices $NUM_GPU $i) uv run torchrun --nproc_per_node=$NUM_GPU --node-rank 0 --rdzv-endpoint localhost:$((10001 + $i)) --nnodes=1  $@  > logs/log$i 2>&1 &
     child_pids+=($!)
 done
 
diff --git a/src/zeroband/diloco.py b/src/zeroband/diloco.py
index 9d9c12fc..73fc23dd 100644
--- a/src/zeroband/diloco.py
+++ b/src/zeroband/diloco.py
@@ -1,5 +1,5 @@
-import os
 import shutil
+import os
 from pydantic_config import BaseConfig
 import torch
 from torch import nn
@@ -16,6 +16,9 @@ class DilocoConfig(BaseConfig):
     inner_steps: int
 
 
+SHARED_MEMORY_PATH = "/dev/shm/zeroband"
+
+
 class Diloco:
     """
     This class implements the diloco algorithm from  https://arxiv.org/abs/2311.08105 and https://arxiv.org/abs/2407.07852.
@@ -99,12 +102,12 @@ def get_offloaded_param(self, model: nn.Module) -> list[nn.Parameter]:
         # All the processes use the same shared memory file to create a storage for each parameter. Only rank 0 will do the copy.
         # A barrier is added to ensure that after the function completes, the parameters are all offloaded. Otherwise, the non 0 ranks might access uninitialized memory.
         offloaded_params = []
-        os.makedirs(f"/dev/shm/zeroband/{self.world_info.global_unique_id}", exist_ok=True)
+        os.makedirs(f"{SHARED_MEMORY_PATH}/{self.world_info.global_unique_id}", exist_ok=True)
 
         for param_name, param in model.named_parameters():
             if param.requires_grad:
                 storage = torch.UntypedStorage.from_file(
-                    f"/dev/shm/zeroband/{self.world_info.global_unique_id}/{param_name}",
+                    f"{SHARED_MEMORY_PATH}/{self.world_info.global_unique_id}/{param_name}",
                     True,
                     param.data.untyped_storage().size(),
                 )
@@ -136,4 +139,4 @@ def step(self, model: nn.Module):
             self._logger.debug("Post meow diloco step %s", get_module_signature(model))
 
     def __del__(self):
-        shutil.rmtree(f"/dev/shm/zeroband/{self.world_info.global_unique_id}", ignore_errors=True)
+        shutil.rmtree(f"{SHARED_MEMORY_PATH}/{self.world_info.global_unique_id}", ignore_errors=True)