diff --git a/paddle/fluid/operators/math/jit_kernel.cc b/paddle/fluid/operators/math/jit_kernel.cc
index 452a79e4907f30e5af408d4a2a4f7cb11d770c1d..81b56ef2e8aa083da270171be462cc5a7ba73507 100644
--- a/paddle/fluid/operators/math/jit_kernel.cc
+++ b/paddle/fluid/operators/math/jit_kernel.cc
@@ -16,23 +16,132 @@ limitations under the License. */
 #include <functional>
 #include <string>
 #include "paddle/fluid/operators/math/cpu_vec.h"
-#include "paddle/fluid/platform/cpu_info.h"
+
+#ifdef PADDLE_WITH_MKLML
+#include "paddle/fluid/platform/dynload/mklml.h"
+#endif
+
+#ifdef __AVX__
+#include <immintrin.h>
+#endif
 
 namespace paddle {
 namespace operators {
 namespace math {
 namespace jitkernel {
 
+namespace jit = platform::jit;
+
 KernelPool& KernelPool::Instance() {
   static KernelPool g_jit_kernels;
   return g_jit_kernels;
 }
+#define SEARCH_BLOCK(src, t, isa)       \
+  if (d < AVX_FLOAT_BLOCK) {            \
+    Compute = src<t, isa, kLT8>;        \
+  } else if (d == AVX_FLOAT_BLOCK) {    \
+    Compute = src<t, isa, kEQ8>;        \
+  } else if (d == AVX512_FLOAT_BLOCK) { \
+    Compute = src<t, isa, kEQ16>;       \
+  } else {                              \
+    Compute = src<t, isa, kGT16>;       \
+  }
+
+#define SEARCH_ISA_BLOCK(src, t)              \
+  if (jit::MayIUse(jit::avx512_common)) {     \
+    SEARCH_BLOCK(src, t, jit::avx512_common); \
+  } else if (jit::MayIUse(jit::avx2)) {       \
+    SEARCH_BLOCK(src, t, jit::avx2);          \
+  } else if (jit::MayIUse(jit::avx)) {        \
+    SEARCH_BLOCK(src, t, jit::avx);           \
+  } else {                                    \
+    SEARCH_BLOCK(src, t, jit::isa_any);       \
+  }
+
+#define FOR_EACH_BLOCK(macro_, isa) \
+  macro_(isa, kLT8) macro_(isa, kEQ8) macro_(isa, kEQ16) macro_(isa, kGT16)
+
+#define FOR_EACH_ISA_BLOCK(macro_)           \
+  FOR_EACH_BLOCK(macro_, jit::avx512_common) \
+  FOR_EACH_BLOCK(macro_, jit::avx2)          \
+  FOR_EACH_BLOCK(macro_, jit::avx)           \
+  FOR_EACH_BLOCK(macro_, jit::any)
+
+#define VMUL_ANY                \
+  for (int i = 0; i < n; ++i) { \
+    z[i] = x[i] * y[i];         \
+  }
+
+template <typename T, platform::jit::cpu_isa_t isa, jit_block>
+static void VMulCompute(const int n, const T* x, const T* y, T* z) {
+  VMUL_ANY
+}
+
+#ifdef PADDLE_USE_MKLML
+#define DEFINE_VMUL_COMPUTE_FLOAT(isa, block)                             \
+  template <>                                                             \
+  static void VMulCompute<float, isa, block>(const int n, const float* x, \
+                                             const float* y, float* z) {  \
+    platform::dynload::vsMul(n, x, y, z);                                 \
+  }
+
+#define DEFINE_VMUL_COMPUTE_DOUBLE(isa, block)                              \
+  template <>                                                               \
+  static void VMulCompute<double, isa, block>(const int n, const double* x, \
+                                              const double* y, float* z) {  \
+    platform::dynload::vdMul(n, x, y, z);                                   \
+  }
+
+FOR_EACH_ISA_BLOCK(DEFINE_VMUL_COMPUTE_FLOAT)
+FOR_EACH_ISA_BLOCK(DEFINE_VMUL_COMPUTE_DOUBLE)
+// TODO(TJ): add EQ8
+#endif
+
+#undef DEFINE_VMUL_COMPUTE_FLOAT
+#undef DEFINE_VMUL_COMPUTE_DOUBLE
+#undef VMUL_ANY
+
+template <>
+VMulKernel<float>::VMulKernel(int d) {
+  SEARCH_ISA_BLOCK(VMulCompute, float);
+}
+
+template <>
+VMulKernel<double>::VMulKernel(int d) {
+  SEARCH_ISA_BLOCK(VMulCompute, double);
+}
+
+template <>
+const std::shared_ptr<VMulKernel<float>> KernelPool::Get<VMulKernel<float>>(
+    int d) {
+  std::string key = "f" + std::to_string(d);
+  if (kers_.find(key) == kers_.end()) {
+    auto p = std::make_shared<VMulKernel<float>>(d);
+    kers_.insert({key, std::dynamic_pointer_cast<Kernel>(p)});
+    return p;
+  }
+  return std::dynamic_pointer_cast<VMulKernel<float>>(kers_.at(key));
+}
+
+template <>
+const std::shared_ptr<VMulKernel<double>> KernelPool::Get<VMulKernel<double>>(
+    int d) {
+  std::string key = "d" + std::to_string(d);
+  if (kers_.find(key) == kers_.end()) {
+    auto p = std::make_shared<VMulKernel<double>>(d);
+    kers_.insert({key, std::dynamic_pointer_cast<Kernel>(p)});
+    return p;
+  }
+  return std::dynamic_pointer_cast<VMulKernel<double>>(kers_.at(key));
+}
 
 template <>
 LSTMKernel<float>::LSTMKernel(int d, const std::string& act_gate_str,
                               const std::string& act_cand_str,
                               const std::string& act_cell_str)
     : Kernel(), d_(d) {
+  d2_ = d * 2;
+  d3_ = d * 3;
   if (platform::jit::MayIUse(platform::jit::avx512_common)) {
     math::VecActivations<float, platform::jit::avx512_common> act_functor;
     act_gate_ = act_functor(act_gate_str);
@@ -48,6 +157,22 @@ LSTMKernel<float>::LSTMKernel(int d, const std::string& act_gate_str,
     act_gate_ = act_functor(act_gate_str);
     act_cell_ = act_functor(act_cell_str);
     act_cand_ = act_functor(act_cand_str);
+    //   ComputeCtHt = [&](float*gates,const float*ct_1,float*ct, float*ht) {
+    // // gates: W_ch, W_ih, W_fh, W_oh
+    // act_gate(d3_, gates + d_, gates + d_);
+
+    // /* C_t = C_t-1 * fgated + cand_gated * igated */
+    // act_cand(d_, gates, gates);
+    // blas.VMUL(d_, gates, gates + d_, gates + d_);
+    // blas.VMUL(d_, ct_1, gates + d2_, gates + d2_);
+    // blas.VADD(d_, gates + d_, gates + d2_, ct);
+
+    // /* H_t = act_cell(C_t) * ogated */
+    // act_cell(d_, ct, gates + d2_);
+    // blas.VMUL(d_, gates + d2_, gates + d3_, ht)
+    // GET_Ct(ct_1, gates, ct);
+    // GET_Ht(ct, gates, ht);
+    //   };
   } else {
     math::VecActivations<float, platform::jit::isa_any> act_functor;
     act_gate_ = act_functor(act_gate_str);
diff --git a/paddle/fluid/operators/math/jit_kernel.h b/paddle/fluid/operators/math/jit_kernel.h
index 29aac71060f520b6c8c4b3c813f6da0062e1a983..b65653498318625d8abb17e9f846aaa2d56ac4eb 100644
--- a/paddle/fluid/operators/math/jit_kernel.h
+++ b/paddle/fluid/operators/math/jit_kernel.h
@@ -17,6 +17,7 @@ limitations under the License. */
 #include <memory>  // for shared_ptr
 #include <string>
 #include <unordered_map>
+#include "paddle/fluid/platform/cpu_info.h"
 #include "paddle/fluid/platform/macros.h"
 
 // Note: Only support on CPU yet.
@@ -25,6 +26,18 @@ namespace operators {
 namespace math {
 namespace jitkernel {
 
+#define SIGMOID_THRESHOLD_MIN -40.0
+#define SIGMOID_THRESHOLD_MAX 13.0
+
+#define AVX_FLOAT_BLOCK 8
+#define AVX_DOUBLE_BLOCK 4
+#define AVX2_FLOAT_BLOCK 8
+#define AVX2_DOUBLE_BLOCK 4
+#define AVX512_FLOAT_BLOCK 16
+#define AVX512_DOUBLE_BLOCK 8
+
+typedef enum { kLT8, kEQ8, kEQ16, kGT16 } jit_block;
+
 class Kernel {
  public:
   Kernel() {}
@@ -36,7 +49,7 @@ class Kernel {
 
 class KernelPool {
  public:
-  static KernelPool& Instance();
+  static KernelPool &Instance();
 
   template <typename Ker, typename... ARGS>
   const std::shared_ptr<Ker> Get(ARGS... args);
@@ -48,17 +61,24 @@ class KernelPool {
   DISABLE_COPY_AND_ASSIGN(KernelPool);
 };
 
+template <typename T>
+class VMulKernel : public Kernel {
+ public:
+  explicit VMulKernel(int n);
+  void (*Compute)(const int n, const T *, const T *, T *);
+};
+
 template <typename T>
 class LSTMKernel : public Kernel {
  public:
-  explicit LSTMKernel(int d, const std::string& act_gate,
-                      const std::string& act_cand, const std::string& act_cell);
+  explicit LSTMKernel(int d, const std::string &act_gate,
+                      const std::string &act_cand, const std::string &act_cell);
 
-  void ComputeCtHt(T* gates, const T* ct_1, T* ct);
-  void ComputeCtHt_NoC0H0(T* gates, const T* ct_1, T* ct);
+  void (*jit_ker)(T *, const T *, T *, T *);
+  std::function<void(T *, const T *, T *, T *)> ComputeCtHt, ComputeCtHt_NoC0H0;
 
  private:
-  int d_;
+  int d_, d2_, d3_;
   std::function<void(const int, const T *, T *)> act_gate_, act_cell_,
       act_cand_;
 };
diff --git a/paddle/fluid/operators/math/jit_kernel_test.cc b/paddle/fluid/operators/math/jit_kernel_test.cc
index 15193f0d940a9abac4f7d1be642001c2674fda1f..041234442d372df8deacb3663cff1fef478bac2c 100644
--- a/paddle/fluid/operators/math/jit_kernel_test.cc
+++ b/paddle/fluid/operators/math/jit_kernel_test.cc
@@ -23,10 +23,25 @@ TEST(JitKernel, pool) {
   namespace jit = paddle::operators::math::jitkernel;
   const int frame_size = 4;
   std::string act_gate = "sigmoid", act_cand = "tanh", act_cell = "tanh";
-  const auto& t =
+  const auto& p1 =
       jit::KernelPool::Instance()
           .template Get<jit::LSTMKernel<float>, int, const std::string&,
                         const std::string&, const std::string&>(
               frame_size, act_gate, act_cand, act_cell);
-  LOG(INFO) << t;
+  const auto& p2 =
+      jit::KernelPool::Instance()
+          .template Get<jit::LSTMKernel<float>, int, const std::string&,
+                        const std::string&, const std::string&>(
+              frame_size, act_gate, act_cand, act_cell);
+  EXPECT_EQ(p1, p2);
+
+  const auto& p3 =
+      jit::KernelPool::Instance().template Get<jit::VMulKernel<float>>(4);
+  EXPECT_TRUE(std::dynamic_pointer_cast<jit::Kernel>(p2) !=
+              std::dynamic_pointer_cast<jit::Kernel>(p3));
+
+  const auto& p4 =
+      jit::KernelPool::Instance().template Get<jit::VMulKernel<double>>(4);
+  EXPECT_TRUE(std::dynamic_pointer_cast<jit::Kernel>(p3) !=
+              std::dynamic_pointer_cast<jit::Kernel>(p4));
 }