diff --git a/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerLifeCycle.java b/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerLifeCycle.java
index e1e9407070..a15202e1b3 100644
--- a/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerLifeCycle.java
+++ b/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerLifeCycle.java
@@ -48,13 +48,19 @@ public void startWorker(int port) throws WorkerInitializationException, Interrup
             throw new WorkerInitializationException("Failed get TS home directory", e);
         }
 
-        String[] args = new String[6];
+        String[] args = new String[12];
         args[0] = EnvironmentUtils.getPythonRunTime(model);
-        args[1] = new File(workingDir, "ts/model_service_worker.py").getAbsolutePath();
-        args[2] = "--sock-type";
-        args[3] = connector.getSocketType();
-        args[4] = connector.isUds() ? "--sock-name" : "--port";
-        args[5] = connector.getSocketPath();
+        args[1] = "-m";
+        args[2] = "intel_extension_for_pytorch.cpu.launch";
+        args[3] = "--ninstances";
+        args[4] = "1";
+        args[5] = "--ncore_per_instance";
+        args[6] = "22";
+        args[7] = new File(workingDir, "ts/model_service_worker.py").getAbsolutePath();
+        args[8] = "--sock-type";
+        args[9] = connector.getSocketType();
+        args[10] = connector.isUds() ? "--sock-name" : "--port";
+        args[11] = connector.getSocketPath();
 
         String[] envp =
                 EnvironmentUtils.getEnvString(
diff --git a/ts/torch_handler/base_handler.py b/ts/torch_handler/base_handler.py
index 199b4a8894..d23bb68a75 100644
--- a/ts/torch_handler/base_handler.py
+++ b/ts/torch_handler/base_handler.py
@@ -9,6 +9,13 @@
 import time
 import torch
 
+ipex_enabled = False
+try:
+    import intel_extension_for_pytorch as ipex
+    ipex_enabled = True
+except:
+    pass
+
 from ..utils.util import list_classes_from_module, load_label_mapping
 
 logger = logging.getLogger(__name__)
@@ -73,6 +80,9 @@ def initialize(self, context):
             self.model = self._load_torchscript_model(model_pt_path)
 
         self.model.eval()
+        if ipex_enabled:
+            self.model = self.model.to(memory_format=torch.channels_last)
+            self.model = ipex.optimize(self.model, dtype=torch.float32, level='O1')
 
         logger.debug('Model file %s loaded successfully', model_pt_path)
 
@@ -141,7 +151,10 @@ def preprocess(self, data):
         Returns:
             tensor: Returns the tensor data of the input
         """
-        return torch.as_tensor(data, device=self.device)
+        t = torch.as_tensor(data, device=self.device)
+        if ipex_enabled:
+            t = t.to(memory_format=torch.channels_last)
+        return t
 
     def inference(self, data, *args, **kwargs):
         """