diff --git a/mshadow b/mshadow
index cce0b32a892f..da390521662f 160000
--- a/mshadow
+++ b/mshadow
@@ -1 +1 @@
-Subproject commit cce0b32a892fbf5de28fa1feabea50b8cf85441b
+Subproject commit da390521662f99adcc7963e97141738b57974573
diff --git a/ps-lite b/ps-lite
index e99b0f288096..55ee9bdbf7e5 160000
--- a/ps-lite
+++ b/ps-lite
@@ -1 +1 @@
-Subproject commit e99b0f288096c21ab943dff55dc3ff854c7904b4
+Subproject commit 55ee9bdbf7e5bf1cbde423ba118041e1a7dcca1b
diff --git a/src/operator/upsampling_nearest-inl.h b/src/operator/upsampling_nearest-inl.h
new file mode 100644
index 000000000000..305e740f903e
--- /dev/null
+++ b/src/operator/upsampling_nearest-inl.h
@@ -0,0 +1,153 @@
+/*!
+ * Copyright (c) 2015 by Contributors
+ * \file upsampling-inl.h
+ * \brief
+ * \author Bing Xu
+*/
+#ifndef MXNET_OPERATOR_UPSAMPLING_NEAREST_INL_H_
+#define MXNET_OPERATOR_UPSAMPLING_NEAREST_INL_H_
+
+#include <dmlc/logging.h>
+#include <dmlc/parameter.h>
+#include <mxnet/operator.h>
+#include <algorithm>
+#include <map>
+#include <vector>
+#include <string>
+#include <utility>
+#include "./operator_common.h"
+
+namespace mxnet {
+namespace op {
+
+namespace up_enum {
+enum UpSamplingNearestOpInputs {kData};
+enum UpSamplingNearestOpOutputs {kOut};
+}  // namespace up_enum
+
+struct UpSamplingNearestParam : public dmlc::Parameter<UpSamplingNearestParam> {
+  index_t scale;
+  DMLC_DECLARE_PARAMETER(UpSamplingNearestParam) {
+    DMLC_DECLARE_FIELD(scale)
+    .set_range(1, 1000)
+    .describe("Up sampling scale");
+  }
+};  // struct UpSamplingNearestParam
+
+template<typename xpu>
+class UpSamplingNearestOp : public Operator {
+ public:
+  explicit UpSamplingNearestOp(UpSamplingNearestParam p) {
+    this->param_ = p;
+  }
+
+  virtual void Forward(const OpContext &ctx,
+                       const std::vector<TBlob> &in_data,
+                       const std::vector<OpReqType> &req,
+                       const std::vector<TBlob> &out_data,
+                       const std::vector<TBlob> &aux_args) {
+    using namespace mshadow;
+    using namespace mshadow::expr;
+    CHECK_EQ(in_data.size(), 1);
+    CHECK_EQ(out_data.size(), 1);
+    Stream<xpu> *s = ctx.get_stream<xpu>();
+    Tensor<xpu, 4> data = in_data[up_enum::kData].get<xpu, 4, real_t>(s);
+    Tensor<xpu, 4> out = out_data[up_enum::kOut].get<xpu, 4, real_t>(s);
+    Assign(out, req[up_enum::kOut], upsampling_nearest(data, param_.scale));
+  }
+
+  virtual void Backward(const OpContext &ctx,
+                        const std::vector<TBlob> &out_grad,
+                        const std::vector<TBlob> &in_data,
+                        const std::vector<TBlob> &out_data,
+                        const std::vector<OpReqType> &req,
+                        const std::vector<TBlob> &in_grad,
+                        const std::vector<TBlob> &aux_args) {
+    using namespace mshadow;
+    using namespace mshadow::expr;
+    CHECK_EQ(out_grad.size(), 1);
+    CHECK_EQ(in_grad.size(), 1);
+    Stream<xpu> *s = ctx.get_stream<xpu>();
+    Tensor<xpu, 4> grad = out_grad[up_enum::kOut].get<xpu, 4, real_t>(s);
+    Tensor<xpu, 4> input_grad = in_grad[up_enum::kData].get<xpu, 4, real_t>(s);
+    mshadow::Shape<2> in_shape = Shape2(input_grad.shape_[2], input_grad.shape_[3]);
+    Assign(input_grad, req[up_enum::kData],
+           static_cast<float>(1.0f / param_.scale / param_.scale) * \
+           pool<mshadow::red::sum>(grad,
+                                   in_shape,
+                                   param_.scale,
+                                   param_.scale,
+                                   param_.scale));
+  }
+
+ private:
+  UpSamplingNearestParam param_;
+};  // class UpSamplingNearestOp
+
+template<typename xpu>
+Operator *CreateOp(UpSamplingNearestParam param);
+
+
+#if DMLC_USE_CXX11
+class UpSamplingNearestProp : public OperatorProperty {
+ public:
+  void Init(const std::vector<std::pair<std::string, std::string> >& kwargs) override {
+    param_.Init(kwargs);
+  }
+
+  std::map<std::string, std::string> GetParams() const override {
+    return param_.__DICT__();
+  }
+
+  bool InferShape(std::vector<TShape> *in_shape,
+                  std::vector<TShape> *out_shape,
+                  std::vector<TShape> *aux_shape) const override {
+    CHECK_EQ(in_shape->size(), 1);
+    const TShape &dshape = (*in_shape)[0];
+    CHECK_EQ(dshape.ndim(), 4) << \
+      "UpSamplingNearest: Input data should be 4D in (batch, channel, y, x)";
+    if (dshape.ndim() ==  0) return false;
+    TShape oshape = dshape;
+    oshape[2] = dshape[2] * param_.scale;
+    oshape[3] = dshape[3] * param_.scale;
+    out_shape->clear();
+    out_shape->push_back(oshape);
+    return true;
+  }
+
+  OperatorProperty* Copy() const override {
+    auto ptr = new UpSamplingNearestProp();
+    ptr->param_ = this->param_;
+    return ptr;
+  }
+
+  std::string TypeString() const override {
+    return "UpSamplingNearest";
+  }
+
+  std::vector<int> DeclareBackwardDependency(
+    const std::vector<int> &out_grad,
+    const std::vector<int> &in_data,
+    const std::vector<int> &out_data) const override {
+    return {out_grad[up_enum::kOut]};
+  }
+
+  std::vector<std::pair<int, void*> > BackwardInplaceOption(
+    const std::vector<int> &out_grad,
+    const std::vector<int> &in_data,
+    const std::vector<int> &out_data,
+    const std::vector<void*> &in_grad) const override {
+    return {{in_data[up_enum::kData], in_grad[up_enum::kData]}};
+  }
+
+  Operator* CreateOperator(Context ctx) const override;
+
+ private:
+  UpSamplingNearestParam param_;
+};  // class UpSamplingNearestProp
+#endif  // DMLC_USE_CXX11
+}  // namespace op
+}  // namespace mxnet
+
+#endif  // MXNET_OPERATOR_UPSAMPLING_NEAREST_INL_H_
+
diff --git a/src/operator/upsampling_nearest.cc b/src/operator/upsampling_nearest.cc
new file mode 100644
index 000000000000..dc377974466d
--- /dev/null
+++ b/src/operator/upsampling_nearest.cc
@@ -0,0 +1,29 @@
+/*!
+ * Copyright (c) 2015 by Contributors
+ * \file upsampling_nearest.cc
+ * \brief
+ * \author Bing Xu
+*/
+
+
+#include "./upsampling_nearest-inl.h"
+
+namespace mxnet {
+namespace op {
+template<>
+Operator *CreateOp<cpu>(UpSamplingNearestParam param) {
+  return new UpSamplingNearestOp<cpu>(param);
+}
+
+Operator* UpSamplingNearestProp::CreateOperator(Context ctx) const {
+  DO_BIND_DISPATCH(CreateOp, param_);
+}
+
+DMLC_REGISTER_PARAMETER(UpSamplingNearestParam);
+
+MXNET_REGISTER_OP_PROPERTY(UpSamplingNearest, UpSamplingNearestProp)
+.describe("Perform simple nearest neighboor up sampling to inputs")
+.add_argument("data", "Symbol", "Input data to the up sampling operator.")
+.add_arguments(UpSamplingNearestParam::__FIELDS__());
+}  // namespace op
+}  // namespace mxnet
diff --git a/src/operator/upsampling_nearest.cu b/src/operator/upsampling_nearest.cu
new file mode 100644
index 000000000000..b6f64e42ead9
--- /dev/null
+++ b/src/operator/upsampling_nearest.cu
@@ -0,0 +1,19 @@
+/*!
+ * Copyright (c) 2015 by Contributors
+ * \file upsampling.cc
+ * \brief
+ * \author Bing Xu
+*/
+
+
+#include "./upsampling_nearest-inl.h"
+
+namespace mxnet {
+namespace op {
+template<>
+Operator *CreateOp<gpu>(UpSamplingNearestParam param) {
+  return new UpSamplingNearestOp<gpu>(param);
+}
+
+}  // namespace op
+}  // namespace mxnet