diff --git a/GPU_version/vio/include/vio/cl_class.h b/GPU_version/vio/include/vio/cl_class.h
index eb62562..66ac2df 100644
--- a/GPU_version/vio/include/vio/cl_class.h
+++ b/GPU_version/vio/include/vio/cl_class.h
@@ -56,8 +56,11 @@ public:
     int32_t reload(size_t id,T* buf,cl::CommandQueue* queue){
         for(auto&& i:_buffers)if(i.second==id){
             T* Map_buf=(T*)queue->enqueueMapBuffer(i.first.first,CL_TRUE,CL_MAP_WRITE,0,sizeof(T) * i.first.second);
+            std::cerr<<"\n reload class L:59,\t";
             memcpy(Map_buf,buf,sizeof(T) * i.first.second);
+             std::cerr<<"L:61\t";
             if(queue->enqueueUnmapMemObject(i.first.first,Map_buf)!=CL_SUCCESS)std::cerr<<"Reload buffer on GPU failed"<<'\n';
+            std::cerr<<"L:63\n";
         }
         return CL_SUCCESS;
     };
diff --git a/GPU_version/vio/src/sparse_img_align_gpu.cpp b/GPU_version/vio/src/sparse_img_align_gpu.cpp
index 7f1e175..fc5369e 100644
--- a/GPU_version/vio/src/sparse_img_align_gpu.cpp
+++ b/GPU_version/vio/src/sparse_img_align_gpu.cpp
@@ -91,21 +91,31 @@ double SparseImgAlignGpu::computeResiduals(
     cl_float3 J[300]={0.0};
     float chi2_[300]={0.0};
     float scale=(float)scale_;
+    std::cerr<<"computeResiduals line: 94,\t";
     residual_->write_buf(1,11,scale);
+    std::cerr<<"96,\t";
     residual_->reload_buf(1,10,chi2_);
+    std::cerr<<"computeResiduals line: 98,\t";
     residual_->reload_buf(1,8,H);
+    std::cerr<<"computeResiduals line: 100,\t";
     residual_->reload_buf(1,9,J);
+    std::cerr<<"computeResiduals line: 102,\t";
     /// TODO GPU compute based on the feature
     residual_->run(1,feature_counter_);
+    std::cerr<<"105,\t";
     float error[300]={0.0};
     float chi[300]={0.0};
     residual_->read(1,10,feature_counter_,chi);
+    std::cerr<<"109,\t";
     residual_->read(1,7,feature_counter_,error);
+    std::cerr<<"111,\t";
     for(int i = 1; i < feature_counter_; ++i){
         error[0] += error[i];
         chi[0] += chi[i];
     }
+    std::cerr<<"116,\t";
     scale_ = error[0]*(1.48f / feature_counter_);
+    std::cerr<<"118\n";
     return chi[0]/(feature_counter_*8);
 }