diff --git a/lidar_pipeline/visualizations.py b/lidar_pipeline/visualizations.py
index 0c34a16..6fae2dd 100644
--- a/lidar_pipeline/visualizations.py
+++ b/lidar_pipeline/visualizations.py
@@ -394,6 +394,7 @@ def generate_hillshade(dem_file, basename, vis_dir, resolution, shared=None):
     logger.info(f"  → Hillshade multidirectionnel{gpu_tag}...")
     t0 = time.time()
     output = vis_dir / f"{basename}_hillshade_multi.tif"
+    used_gpu = _gpu_mod.HAS_GPU
 
     try:
         if shared:
@@ -446,7 +447,7 @@ def generate_hillshade(dem_file, basename, vis_dir, resolution, shared=None):
         combined_np = np.power(combined_np, gamma)
 
         _save_tif(output, combined_np.astype(np.float32), transform, crs, nan_mask=nan_mask)
-        logger.info(f"  ✓ Hillshade terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Hillshade terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur hillshade: {e}", exc_info=True)
@@ -475,7 +476,7 @@ def generate_slope(dem_file, basename, vis_dir, resolution, shared=None):
             slope = xp.arctan(xp.sqrt(dx**2 + dy**2)) * 180 / xp.pi
             nan_mask = np.isnan(dem_np)
         _save_tif(output, to_cpu(slope) if _gpu_mod.HAS_GPU else slope, transform, crs, nan_mask=nan_mask)
-        logger.info(f"  ✓ Pente terminée ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Pente terminée ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur slope: {e}", exc_info=True)
@@ -520,7 +521,7 @@ def generate_svf(dem_file, basename, vis_dir, resolution, shared=None):
         svf_np = to_cpu(svf_combined).astype(np.float32)
         svf_np[nan_mask] = np.nan
         _save_tif(output, svf_np, transform, crs)
-        logger.info(f"  ✓ SVF terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ SVF terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur SVF: {e}", exc_info=True)
@@ -568,7 +569,7 @@ def generate_openness(dem_file, basename, vis_dir, resolution, positive=True, sh
             openness_result = openness_result / std_val
 
         _save_tif(output, openness_result, transform, crs)
-        logger.info(f"  ✓ {name} terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ {name} terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur openness: {e}", exc_info=True)
@@ -637,7 +638,7 @@ def generate_mslrm(dem_file, basename, vis_dir, resolution, shared=None):
                 mslrm = np.sign(signed_mean) * rms_magnitude
         mslrm[nan_mask] = np.nan
         _save_tif(output, mslrm.astype(np.float32), transform, crs)
-        logger.info(f"  ✓ MSRM terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ MSRM terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur MSRM: {e}", exc_info=True)
@@ -718,7 +719,7 @@ def generate_sailore(dem_file, basename, vis_dir, resolution, shared=None):
         sailore[nan_mask] = np.nan
 
         _save_tif(output, sailore.astype(np.float32), transform, crs)
-        logger.info(f"  ✓ SAILORE terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ SAILORE terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur SAILORE: {e}", exc_info=True)
@@ -790,7 +791,7 @@ def generate_roughness(dem_file, basename, vis_dir, resolution, shared=None):
         roughness[nan_mask] = np.nan
 
         _save_tif(output, roughness, transform, crs)
-        logger.info(f"  ✓ Rugosité terminée ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Rugosité terminée ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur rugosité: {e}", exc_info=True)
@@ -922,7 +923,7 @@ def generate_wavelet(dem_file, basename, vis_dir, resolution, shared=None):
         combined[nan_mask] = np.nan
 
         _save_tif(output, combined.astype(np.float32), transform, crs)
-        logger.info(f"  ✓ Ondelette terminée ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Ondelette terminée ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur ondelette: {e}", exc_info=True)
@@ -1044,7 +1045,7 @@ def generate_flow_accumulation(dem_file, basename, vis_dir, resolution, shared=N
         flow_result[nan_mask] = np.nan
 
         _save_tif(output, flow_result, transform, crs)
-        logger.info(f"  ✓ Flow accumulation terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Flow accumulation terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur flow accumulation: {e}", exc_info=True)
@@ -1106,7 +1107,7 @@ def generate_aniso_open(dem_file, basename, vis_dir, resolution, shared=None):
             aniso_result = aniso_result / std_val
 
         _save_tif(output, aniso_result, transform, crs)
-        logger.info(f"  ✓ Openness anisotropique terminé ({time.time()-t0:.1f}s){gpu_tag}")
+        logger.info(f"  ✓ Openness anisotropique terminé ({time.time()-t0:.1f}s){' [GPU]' if _gpu_mod.HAS_GPU else ''}")
         return output
     except Exception as e:
         logger.error(f"  ✗ Erreur openness anisotropique: {e}", exc_info=True)