diff --git a/cmake/external/xpu.cmake b/cmake/external/xpu.cmake
index 16c69a7b503722b8adbc7cda145993775af14c8f..f846623602ed79a5bd84268436a59ede1957364b 100644
--- a/cmake/external/xpu.cmake
+++ b/cmake/external/xpu.cmake
@@ -13,7 +13,7 @@ if(NOT XPU_SDK_ROOT)
   elseif(WITH_SUNWAY)
       SET(XPU_URL    "https://baidu-kunlun-public.su.bcebos.com/paddle_depence/sunway/xpu_2021_01_13.tar.gz" CACHE STRING "" FORCE)
   else()
-      SET(XPU_URL    "https://baidu-kunlun-public.su.bcebos.com/paddle_depence/xpu_2021_03_30.tar.gz" CACHE STRING "" FORCE)
+      SET(XPU_URL    "https://baidu-kunlun-public.su.bcebos.com/paddle_depence/xpu_2021_04_09.tar.gz" CACHE STRING "" FORCE)
   endif()
 
   SET(XPU_SOURCE_DIR              "${THIRD_PARTY_PATH}/xpu")
diff --git a/paddle/fluid/operators/concat_op_xpu.cc b/paddle/fluid/operators/concat_op_xpu.cc
index aa0002cc6d1777dab6e598fc7c123e5255d0f094..be299babdba7a4f450bafdf5dce8e686f0493fce 100644
--- a/paddle/fluid/operators/concat_op_xpu.cc
+++ b/paddle/fluid/operators/concat_op_xpu.cc
@@ -132,16 +132,14 @@ class ConcatGradXPUKernel : public framework::OpKernel<T> {
     axis = ComputeAxis(static_cast<int64_t>(axis),
                        static_cast<int64_t>(ins[0]->dims().size()));
     // get output tensor that the name is not kEmptyVarName
-    std::vector<framework::Tensor*> outputs;
-    std::vector<int> choose_idx;
-    int n = 0;
+    std::vector<T*> ptrs(outs.size());
     for (size_t j = 0; j < outs.size(); ++j) {
       if (out_var_names[j] != framework::kEmptyVarName &&
           outs[j]->numel() != 0UL) {
         outs[j]->mutable_data<T>(ctx.GetPlace());
-        outputs.push_back(outs[j]);
-        choose_idx.push_back(j);
-        n++;
+        ptrs[j] = outs[j]->data<T>();
+      } else {
+        ptrs[j] = nullptr;
       }
     }
     PADDLE_ENFORCE_GE(axis, 0, platform::errors::InvalidArgument(
@@ -157,10 +155,10 @@ class ConcatGradXPUKernel : public framework::OpKernel<T> {
             axis, out_grad->dims().size()));
 
     auto input_dims = ins[0]->dims();
-    std::vector<int> split_list(n);
+    std::vector<int> split_list(ins.size());
     std::vector<int> xdims_list(input_dims.size());
     int total_length = 0;
-    for (int i = 0; i < n; ++i) {
+    for (size_t i = 0; i < ins.size(); ++i) {
       split_list[i] = ins[i]->dims()[axis];
       total_length += ins[i]->dims()[axis];
     }
@@ -172,11 +170,6 @@ class ConcatGradXPUKernel : public framework::OpKernel<T> {
     }
     xdims_list[axis] = total_length;
 
-    std::vector<T*> ptrs(n);
-    for (int i = 0; i < n; ++i) {
-      ptrs[i] = outputs[i]->data<T>();
-    }
-
     auto& dev_ctx = ctx.template device_context<DeviceContext>();
     int r = xpu::split<T>(dev_ctx.x_context(), out_grad->data<T>(), ptrs,
                           xdims_list, split_list, axis);