diff --git a/paddle/fluid/operators/jit/README.md b/paddle/fluid/operators/jit/README.md
index 6b2f2b2848e47fa5fadf0e5874cbbc80ffb2c1a7..28d21f40af37e5298f4645b02049c284796ae556 100644
--- a/paddle/fluid/operators/jit/README.md
+++ b/paddle/fluid/operators/jit/README.md
@@ -45,6 +45,8 @@ PaddlePaddle/Paddle/paddle/fluid/
 
 - 在`KernelType` 中添加 `your_key` .
 - 实现Reference 的逻辑，每个jitkernel的Reference 实现是必须的。不要依赖任何第三方库。并在`refer/CmakeLists.txt`中`USE_JITKERNEL_REFER(your_key)`.
+- (optional) 实现更多的算法在`more`目录下，可以依赖mkl，openblas，或者mkldnn等第三方库。
+- (optional) 实现基于Xbyak的生成code，在`gen`目下。
 - 必要时可以添加新的`KernelTuples`，可以参考`XYZNTuples`，新加的Attr类型需要特例化`JitCodeKey`方法。
 - 添加unit test，需要测试float和double
 - 添加benchmark确保get得到的速度是最快。
diff --git a/paddle/fluid/operators/jit/more/mkl/CMakeLists.txt b/paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
index 0c15c7060d2d497c4881b27b72bb9aa205abd55f..ffecb732975a652456b154a61feb8a20a727d306 100644
--- a/paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
+++ b/paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
@@ -4,3 +4,5 @@ set(JIT_KERNEL_DEPS ${JIT_KERNEL_DEPS} dynload_mklml jit_kernel_mkl PARENT_SCOPE
 
 # use mkl kernels by name and type
 USE_JITKERNEL_MORE(vmul, mkl)
+USE_JITKERNEL_MORE(vadd, mkl)
+USE_JITKERNEL_MORE(vscal, mkl)
diff --git a/paddle/fluid/operators/jit/more/mkl/mkl.cc b/paddle/fluid/operators/jit/more/mkl/mkl.cc
index 0ffe1d565f1b2a1639c82b85e9c0825d64461de7..3d963cbf1dd5468afc717178f1a53234d8e14a99 100644
--- a/paddle/fluid/operators/jit/more/mkl/mkl.cc
+++ b/paddle/fluid/operators/jit/more/mkl/mkl.cc
@@ -13,7 +13,9 @@
  * limitations under the License. */
 
 #include "paddle/fluid/operators/jit/more/mkl/mkl.h"
+#include "paddle/fluid/operators/jit/refer/refer.h"
 #include "paddle/fluid/operators/jit/registry.h"
+#include "paddle/fluid/platform/cpu_info.h"
 #include "paddle/fluid/platform/dynload/mklml.h"
 
 namespace paddle {
@@ -32,6 +34,61 @@ void VMul<double>(const double* x, const double* y, double* z, int n) {
   platform::dynload::vdMul(n, x, y, z);
 }
 
+template <>
+void VAdd<float>(const float* x, const float* y, float* z, int n) {
+  platform::dynload::vsAdd(n, x, y, z);
+}
+
+template <>
+void VAdd<double>(const double* x, const double* y, double* z, int n) {
+  platform::dynload::vdAdd(n, x, y, z);
+}
+
+template <>
+void VScal<float>(const float* a, const float* x, float* y, int n) {
+  if (x == y) {
+    platform::dynload::cblas_sscal(n, *a, y, 1);
+  } else {
+    refer::VScal<float>(a, x, y, n);
+  }
+}
+
+template <>
+void VScal<double>(const double* a, const double* x, double* y, int n) {
+  if (x == y) {
+    platform::dynload::cblas_dscal(n, *a, y, 1);
+  } else {
+    refer::VScal<double>(a, x, y, n);
+  }
+}
+
+// TODO(TJ): tuning me carefully on AVX, AVX2 and AVX512
+template <>
+bool VMulKernel<float>::UseMe(int d) const {
+  return platform::MayIUse(platform::avx512f) && d > 512;
+}
+
+template <>
+bool VAddKernel<float>::UseMe(int d) const {
+  return platform::MayIUse(platform::avx512f) && d > 512;
+}
+
+template <>
+bool VScalKernel<float>::UseMe(int d) const {
+  return platform::MayIUse(platform::avx512f) && d > 512;
+}
+
+#define AWALYS_USE_ME_WITH_DOUBLE(func)           \
+  template <>                                     \
+  bool func##Kernel<double>::UseMe(int d) const { \
+    return true;                                  \
+  }
+
+AWALYS_USE_ME_WITH_DOUBLE(VMul);
+AWALYS_USE_ME_WITH_DOUBLE(VAdd);
+AWALYS_USE_ME_WITH_DOUBLE(VScal);
+
+#undef AWALYS_USE_ME_WITH_DOUBLE
 }  // namespace mkl
 }  // namespace more
 }  // namespace jit
@@ -40,5 +97,12 @@ void VMul<double>(const double* x, const double* y, double* z, int n) {
 
 namespace mkl = paddle::operators::jit::more::mkl;
 
-REGISTER_JITKERNEL_MORE(vmul, mkl, mkl::VMulKernel<float>,
-                        mkl::VMulKernel<double>);
+#define REGISTER_MKL_KERNEL(key, func)                        \
+  REGISTER_JITKERNEL_MORE(key, mkl, mkl::func##Kernel<float>, \
+                          mkl::func##Kernel<double>)
+
+REGISTER_MKL_KERNEL(vmul, VMul);
+REGISTER_MKL_KERNEL(vadd, VAdd);
+REGISTER_MKL_KERNEL(vscal, VScal);
+
+#undef REGISTER_MKL_KERNEL
diff --git a/paddle/fluid/operators/jit/more/mkl/mkl.h b/paddle/fluid/operators/jit/more/mkl/mkl.h
index 4173d1f3de0ce4a7ee727d0261d2fede86bb72b7..84a93f408f51e444c62ea3b70fba8daab280fed0 100644
--- a/paddle/fluid/operators/jit/more/mkl/mkl.h
+++ b/paddle/fluid/operators/jit/more/mkl/mkl.h
@@ -16,7 +16,6 @@
 
 #include <type_traits>
 #include "paddle/fluid/operators/jit/kernel_base.h"
-#include "paddle/fluid/platform/cpu_info.h"
 
 namespace paddle {
 namespace operators {
@@ -28,17 +27,27 @@ template <typename T>
 void VMul(const T* x, const T* y, T* z, int n);
 
 template <typename T>
-class VMulKernel : public KernelImpl<XYZNTuples<T>> {
- public:
-  VMulKernel() { this->func = VMul<T>; }
-  bool UseMe(int d) const override {
-    if (std::is_same<T, float>::value) {
-      return platform::MayIUse(platform::avx512f) && d > 512;
-    } else {
-      return true;
-    }
+void VAdd(const T* x, const T* y, T* z, int n);
+
+template <typename T>
+void VScal(const T* a, const T* x, T* y, int n);
+
+#define DECLARE_MKL_KERNEL(name, tuples)                      \
+  template <typename T>                                       \
+  class name##Kernel : public KernelImpl<tuples<T>> {         \
+   public:                                                    \
+    name##Kernel() { this->func = name<T>; }                  \
+    bool UseMe(typename tuples<T>::attr_type) const override; \
   }
-};
+
+// XYZN
+DECLARE_MKL_KERNEL(VMul, XYZNTuples);
+DECLARE_MKL_KERNEL(VAdd, XYZNTuples);
+
+// AXYN
+DECLARE_MKL_KERNEL(VScal, AXYNTuples);
+
+#undef DECLARE_MKL_KERNEL
 
 }  // namespace mkl
 }  // namespace more
diff --git a/paddle/fluid/operators/math/jit_kernel_blas.cc b/paddle/fluid/operators/math/jit_kernel_blas.cc
index 8cf588efba52314650bfd376b95b10e6d4336b2e..682e51e89d67f36f4da14ba4b80416f9ad8a1fa1 100644
--- a/paddle/fluid/operators/math/jit_kernel_blas.cc
+++ b/paddle/fluid/operators/math/jit_kernel_blas.cc
@@ -31,56 +31,6 @@ namespace operators {
 namespace math {
 namespace jitkernel {
 
-#ifdef PADDLE_WITH_MKLML
-template <typename T>
-void VMulMKL(const T* x, const T* y, T* z, int n);
-
-template <>
-void VMulMKL<float>(const float* x, const float* y, float* z, int n) {
-  platform::dynload::vsMul(n, x, y, z);
-}
-
-template <>
-void VMulMKL<double>(const double* x, const double* y, double* z, int n) {
-  platform::dynload::vdMul(n, x, y, z);
-}
-
-template <typename T>
-void VAddMKL(const T* x, const T* y, T* z, int n);
-
-template <>
-void VAddMKL<float>(const float* x, const float* y, float* z, int n) {
-  platform::dynload::vsAdd(n, x, y, z);
-}
-
-template <>
-void VAddMKL<double>(const double* x, const double* y, double* z, int n) {
-  platform::dynload::vdAdd(n, x, y, z);
-}
-
-template <typename T>
-void VScalMKL(const T* a, const T* x, T* y, int n);
-
-template <>
-void VScalMKL<float>(const float* a, const float* x, float* y, int n) {
-  if (x == y) {
-    platform::dynload::cblas_sscal(n, *a, y, 1);
-  } else {
-    refer::VScal<float>(a, x, y, n);
-  }
-}
-
-template <>
-void VScalMKL<double>(const double* a, const double* x, double* y, int n) {
-  if (x == y) {
-    platform::dynload::cblas_dscal(n, *a, y, 1);
-  } else {
-    refer::VScal<double>(a, x, y, n);
-  }
-}
-
-#endif
-
 /* VMUL JitKernel */
 template <typename T>
 class VMulKernelImpl : public VMulKernel<T> {