diff --git a/research/fed-bpt/job_templates/fedbpt/config_fed_server.conf b/research/fed-bpt/job_templates/fedbpt/config_fed_server.conf
index a142fbcf33..66422969c4 100644
--- a/research/fed-bpt/job_templates/fedbpt/config_fed_server.conf
+++ b/research/fed-bpt/job_templates/fedbpt/config_fed_server.conf
@@ -33,32 +33,22 @@
 
             # seed for CMA-ES algorithm
             seed = 42
-
-            # The GlobalES controller use an persistor to load the model and save the model.
-            # The persistent component can be identified by component ID specified here.
-            # persistor_id = "persistor"
         }
       }
   ]
 
   # List of components used in the server side workflow.
   components = [
-#    {
-#      # This is the persistence component used in above workflow.
-#      # PTFileModelPersistor is a Pytorch persistor which save/read the model to/from file.
-
-#     id = "persistor"
-#     path = "nvflare.app_opt.pt.file_model_persistor.PTFileModelPersistor"
-#
-#  # the persitor class take model class as argument
-#  # This imply that the model is initialized from the server-side.
-#  # The initialized model will be broadcast to all the clients to start the training.
-#  args.model.path = "{model_class_path}"
-#},
     {
       id = "receiver"
       path = "nvflare.app_opt.tracking.tb.tb_receiver.TBAnalyticsReceiver"
       args.events = ["fed.analytix_log_stats"]
+    },
+    {
+      # we use this component so the client api `flare.init()` can get required information
+      id = "register_decomposer"
+      path = "decomposer_widget.RegisterDecomposer"
+      args {}
     }
   ]
 
diff --git a/research/fed-bpt/src/global_es.py b/research/fed-bpt/src/global_es.py
index bee3bd2256..572922e582 100644
--- a/research/fed-bpt/src/global_es.py
+++ b/research/fed-bpt/src/global_es.py
@@ -16,7 +16,6 @@
 
 import cma
 import numpy as np
-from cma_decomposer import register_decomposers
 
 from nvflare.app_common.abstract.fl_model import FLModel
 from nvflare.app_common.workflows.fedavg import FedAvg
@@ -63,9 +62,6 @@ def __init__(self, *args, frac=1, sigma=1, intrinsic_dim=500, seed=42, bound=0,
         self.bound = bound
 
     def run(self) -> None:
-        # We serialize CMAEvolutionStrategy object directly. This requires registering custom decomposers.
-        register_decomposers()
-
         local_cma_mu = 0.0
 
         m = max(int(self.frac * self._min_clients), 1)