[LANG/PASS] Support Vectorize (#37)

include/tvm/ir_mutator.h

@@ -62,6 +62,7 @@ class IRMutator {
   virtual Stmt Mutate_(const Realize* op, const Stmt& s);
   virtual Stmt Mutate_(const Store* op, const Stmt& s);
   virtual Stmt Mutate_(const Free* op, const Stmt& s);
+  virtual Stmt Mutate_(const IfThenElse* op, const Stmt& s);
   virtual Expr Mutate_(const Call* op, const Expr& e);
   virtual Expr Mutate_(const Load* op, const Expr& s);
   virtual Expr Mutate_(const Variable* op, const Expr& e);

include/tvm/ir_pass.h

@@ -112,6 +112,12 @@ Stmt StorageFlatten(Stmt stmt,
 Stmt UnrollLoop(Stmt stmt, int max_auto_step);
 
 /*!
+ * \brief vectorize the constant loops
+ * \param stmt The statment to be vectorized.
+ */
+Stmt VectorizeLoop(Stmt stmt);
+
+/*!
  * \brief Make an user callable API LoweredFunc.
  *
  *  The main task of this function is to create code to :

include/tvm/schedule.h

@@ -18,6 +18,8 @@ class StageNode;
 class ScheduleNode;
 // Node container for IterVarRelation
 class IterVarRelationNode;
+// Attribute of itervar.
+class IterVarAttrNode;
 
 /*! \brief the attachment type */
 enum AttachType : int {
@@ -27,6 +29,12 @@ enum AttachType : int {
   kScope = 3
 };
 
+/*! \brief IterVar type */
+enum IterVarType : int {
+  kUnrolled = 1,
+  kVectorized = 2
+};
+
 /*! \brief Stage, contains scheduling for a stage of computation. */
 class Stage : public NodeRef {
  public:
@@ -124,11 +132,22 @@ class Stage : public NodeRef {
               IterVar* p_x_inner, IterVar* p_y_inner,
               Expr x_factor, Expr y_factor);
   /*!
+   * \brief Vectorize iteration.
+   * \param var The axis to be vectorized.
+   * \return reference to self.
+   */
+  Stage& vectorize(IterVar var);   // NOLINT(*)
+  /*!
+   * \brief Unroll iteration.
+   * \param var The axis to be vectorized.
+   * \return reference to self.
+   */
+  Stage& unroll(IterVar var);   // NOLINT(*)
+  /*!
    * \brief whether the stage has been scheduled.
    * \return whether the stage has been scheduled.
    */
   inline bool is_scheduled() const;
-
   // declare container type
   using ContainerType = StageNode;
 };
@@ -193,6 +212,21 @@ class IterVarRelation : public NodeRef {
   inline const IterVarRelationNode* operator->() const;
 };
 
+/*!
+ * \brief Additional scheduable attributes about IterVar.
+ */
+class IterVarAttr : public NodeRef {
+ public:
+  IterVarAttr() {}
+  explicit IterVarAttr(IterVarType t);
+  explicit IterVarAttr(std::shared_ptr<Node> n) : NodeRef(n) {}
+  /*!
+   * \brief access the internal node container
+   * \return the pointer to the internal node container
+   */
+  inline const IterVarAttrNode* operator->() const;
+};
+
 // defintion of node containers
 /*!
  * \brief represents the schedule of the tensor
@@ -223,6 +257,8 @@ class StageNode : public Node {
   Array<IterVar> leaf_iter_vars;
   /*! \brief The relation bwteen of IterVars */
   Array<IterVarRelation> relations;
+  /*! \brief additional attributes about iter var. */
+  Map<IterVar, IterVarAttr> iter_var_attrs;
   /*! \brief The attachment type of the schedule */
   AttachType attach_type{kNone};
   /*! \brief The attach point of this schedule. */
@@ -236,6 +272,7 @@ class StageNode : public Node {
     v->Visit("all_iter_vars", &all_iter_vars);
     v->Visit("leaf_iter_vars", &leaf_iter_vars);
     v->Visit("relations", &relations);
+    v->Visit("iter_var_attrs", &iter_var_attrs);
     v->Visit("attach_type", &attach_type);
     v->Visit("attach_ivar", &attach_ivar);
     v->Visit("attach_stage", &attach_stage);
@@ -268,6 +305,20 @@ class ScheduleNode : public Node {
   TVM_DECLARE_NODE_TYPE_INFO(ScheduleNode);
 };
 
+/*! \brief node container for IterVar attr */
+class IterVarAttrNode : public Node {
+ public:
+  /*! \brief The iteration type. */
+  IterVarType iter_type;
+
+  void VisitAttrs(AttrVisitor* v) final {
+    v->Visit("iter_type", &iter_type);
+  }
+
+  static constexpr const char* _type_key = "IterVarAttr";
+  TVM_DECLARE_NODE_TYPE_INFO(IterVarAttrNode);
+};
+
 /*! \brief base node of iteration var */
 class IterVarRelationNode : public Node {
 };
@@ -372,5 +423,9 @@ inline const IterVarRelationNode* IterVarRelation::operator->() const {
   return static_cast<const IterVarRelationNode*>(node_.get());
 }
 
+inline const IterVarAttrNode* IterVarAttr::operator->() const {
+  return static_cast<const IterVarAttrNode*>(node_.get());
+}
+
 }  // namespace tvm
 #endif  // TVM_SCHEDULE_H_

python/tvm/build.py

@@ -69,6 +69,7 @@ def build(sch,
     stmt = schedule.ScheduleOps(sch, bounds)
     stmt = ir_pass.StorageFlatten(stmt, binds)
     stmt = ir_pass.CanonicalSimplify(stmt)
+    stmt = ir_pass.VectorizeLoop(stmt)
     stmt = ir_pass.UnrollLoop(stmt, max_auto_unroll_step)
     stmt = ir_pass.Simplify(stmt)
     fapi = ir_pass.MakeAPI(stmt, name, arg_list, len(arg_list))

python/tvm/schedule.py

@@ -177,3 +177,23 @@ class Stage(NodeBase):
         x_outer, y_outer, x_inner, y_inner = _api_internal._StageTile(
             self, x_parent, y_parent, x_factor, y_factor)
         return x_outer, y_outer, x_inner, y_inner
+
+    def vectorize(self, var):
+        """Vectorize the iteration.
+
+        Parameters
+        ----------
+        var : IterVar
+            The iteration to be vectorize
+        """
+        _api_internal._StageVectorize(self, var)
+
+    def unroll(self, var):
+        """Unroll the iteration.
+
+        Parameters
+        ----------
+        var : IterVar
+            The iteration to be unrolled.
+        """
+        _api_internal._StageUnroll(self, var)

src/api/api_lang.cc

@@ -253,6 +253,18 @@ TVM_REGISTER_API(_StageTile)
     *ret = Array<IterVar>({x_outer, y_outer, x_inner, y_inner});
   });
 
+TVM_REGISTER_API(_StageUnroll)
+  .set_body([](TVMArgs args, TVMRetValue* ret) {
+    args[0].operator Stage()
+        .unroll(args[1]);
+  });
+
+TVM_REGISTER_API(_StageVectorize)
+  .set_body([](TVMArgs args, TVMRetValue* ret) {
+    args[0].operator Stage()
+        .vectorize(args[1]);
+  });
+
 TVM_REGISTER_API(_ScheduleNormalize)
 .set_body([](TVMArgs args, TVMRetValue* ret) {
     args[0].operator Schedule()

src/api/api_pass.cc

@@ -62,6 +62,7 @@ REGISTER_PASS1(VerifySSA);
 REGISTER_PASS1(CanonicalSimplify);
 REGISTER_PASS4(Inline);
 REGISTER_PASS2(StorageFlatten);
+REGISTER_PASS1(VectorizeLoop);
 REGISTER_PASS2(UnrollLoop);
 REGISTER_PASS2(StorageSync);
 REGISTER_PASS4(MakeAPI);

src/arithmetic/compute_expr.h

@@ -9,6 +9,7 @@
 
 #include <tvm/ir.h>
 #include <pass/Interval.h>
+#include <limits>
 
 namespace tvm {
 namespace arith {
@@ -52,6 +53,23 @@ inline bool GetConst<uint64_t>(Expr e, uint64_t *out) {
   }
 }
 
+// get a small constant int
+inline bool GetConstInt(Expr e, int* out) {
+  int64_t v1 = 0;
+  uint64_t v2 = 0;
+  if (GetConst(e, &v1)) {
+    if (v1 > static_cast<int64_t>(
+            std::numeric_limits<int>::max())) return false;
+    *out = static_cast<int>(v1); return true;
+  }
+  if (GetConst(e, &v2)) {
+    if (v2 > static_cast<uint64_t>(
+            std::numeric_limits<int>::max())) return false;
+    *out = static_cast<int>(v2); return true;
+  }
+  return false;
+}
+
 #define TVM_CONST_PROPAGATION(OP_NAME, OP)                       \
   int64_t ia = 0, ib = 0;                                        \
   if (GetConst(a, &ia) && GetConst(b, &ib)) {                    \

src/codegen/codegen_c.h

@@ -102,6 +102,20 @@ class CodeGenC {
   virtual void PrintExpr(const ir::Ramp* op, std::ostream& os);  // NOLINT(*)
   virtual void PrintExpr(const ir::Broadcast* op, std::ostream& os);  // NOLINT(*)
   virtual void PrintExpr(const ir::Select* op, std::ostream& os);  // NOLINT(*)
+  // Binary vector op.
+  virtual void PrintVecBinaryOp(
+      const std::string&op, Type op_type,
+      Expr lhs, Expr rhs, std::ostream& os);  // NOLINT(*)
+  virtual void PrintVecLoad(const Variable* buffer,
+                            Type t, Expr base,
+                            std::ostream& os);  // NOLINT(*)
+  virtual void PrintVecStore(const Variable* buffer,
+                             Type t, Expr base,
+                             const std::string& value);  // NOLINT(*)
+  virtual void PrintVecElemLoad(
+      const std::string& vec, Type t, int i, std::ostream& os);  // NOLINT(*)
+  virtual void PrintVecElemStore(
+      const std::string& vec, Type t, int i, const std::string& value);
   /*! \brief function print into the ostream */
   using FPrintExpr = IRFunctor<void(const NodeRef&, std::ostream& os, CodeGenC *)>; // NOLINT(*)
   /*! \brief function to to print normal code */
@@ -116,17 +130,10 @@ class CodeGenC {
   std::ostringstream stream;
 
  protected:
-  // additional string for arg addr_space.
-  std::string arg_addr_space_;
-
- private:
-  /*! \brief entry in ssa assign map */
-  struct SSAEntry {
-    /*! \brief The value id */
-    std::string vid;
-    /*! \brief The scope id */
-    int scope_id;
-  };
+  // print reference to a buffer as type t in index.
+  void PrintBufferRef(const Variable* buffer,
+                      Type t, Expr index,
+                      std::ostream& os);  // NOLINT(*)
   /*!
    * \brief Get the SSA ID corresponds to src
    *  If necessary, generate new assignment
@@ -135,6 +142,19 @@ class CodeGenC {
    */
   std::string SSAGetID(std::string src, Type t);
   /*!
+   * \brief get a unique name with the corresponding prefix
+   * \param prefix The prefix of the name
+   * \return The returned name.
+   */
+  std::string GetUniqueName(std::string prefix);
+  /*! \brief entry in ssa assign map */
+  struct SSAEntry {
+    /*! \brief The value id */
+    std::string vid;
+    /*! \brief The scope id */
+    int scope_id;
+  };
+  /*!
    * \brief mark the beginning of a new scope
    * \return The scope id.
    */
@@ -155,25 +175,28 @@ class CodeGenC {
    * \param buf_var The buffer variable.
    * \param t The type to be checked.
    */
-  void HandleTypeRegister(const Variable* buf_var, Type t);
+  void RegisterHandleType(const Variable* buf_var, Type t);
   /*!
-   * \brief get a unique name with the corresponding prefix
-   * \param prefix The prefix of the name
-   * \return The returned name.
+   * \brief Get the storage scope of buf_var.
+   * \param buf_var The buf_var to be queryed.
+   * \return The storage scope.
    */
-  std::string GetUniqueName(std::string prefix);
-  /*! \brief whether to print in SSA form */
-  bool print_ssa_form_{true};
-  /*! \brief name of each variable */
-  std::unordered_map<const Variable*, std::string> var_idmap_;
-  /*! \brief the data type of allocated buffers */
-  std::unordered_map<const Variable*, Type> handle_data_type_;
+  std::string GetStorageScope(const Variable* buf_var) const;
+
   /*! \brief the storage scope of allocation */
   std::unordered_map<const Variable*, std::string> alloc_storage_scope_;
+
+ private:
+  /*! \brief whether to print in SSA form */
+  bool print_ssa_form_{true};
   /*! \brief name allocation map */
   std::unordered_map<std::string, int> name_alloc_map_;
   /*! \brief assignment map of ssa */
   std::unordered_map<std::string, SSAEntry> ssa_assign_map_;
+  /*! \brief name of each variable */
+  std::unordered_map<const Variable*, std::string> var_idmap_;
+  /*! \brief the data type of allocated buffers */
+  std::unordered_map<const Variable*, Type> handle_data_type_;
   /*! \brief array to check whether we are inside certain scope */
   std::vector<bool> scope_mark_;
 };

src/codegen/codegen_cuda.cc

@@ -22,6 +22,108 @@ std::string CodeGenCUDA::Compile(
   return CodeGenC::Compile(f, output_ssa);
 }
 
+void CodeGenCUDA::PrintType(Type t, std::ostream& os) const {  // NOLINT(*)
+  int lanes = t.lanes();
+  if (t.is_handle()) {
+    CHECK_EQ(lanes, 1)
+        << "do not yet support vector types";
+    os << "void*"; return;
+  }
+  bool fail = false;
+  if (t.is_float()) {
+    switch (t.bits()) {
+      case 16: os << "half"; break;
+      case 32: os << "float"; break;
+      case 64: os << "double"; break;
+      default: fail = true; break;
+    }
+    if (!fail && lanes == 1) return;
+    if (!fail && (lanes >= 2 && lanes <= 4)) {
+      os << lanes; return;
+    }
+  } else if (t.is_uint() || t.is_int()) {
+    if (t.is_uint()) {
+      os << 'u';
+    }
+    if (t.bits() == 8 && t.lanes() == 4) {
+      // directly 4 8 bit int in integer.
+      os << "int"; return;
+    }
+    switch (t.bits()) {
+      case 8: os << "char"; break;
+      case 16: os << "short"; break;
+      case 32: os << "int"; break;
+      case 64: {
+        if (lanes != 1 && sizeof(long) == 64) {  // NOLINT(*)
+          os << "long"; break;
+        } else {
+          os << "int64_t"; break;
+        }
+      }
+      case 1: os << "int"; break;
+      default: fail = true; break;
+    }
+    if (!fail && lanes == 1) return;
+    if (!fail && (lanes >= 2 && lanes <= 4)) {
+      os << lanes; return;
+    }
+  }
+  LOG(FATAL) << "Cannot convert type " << t << " to CUDA type";
+}
+
+void CodeGenCUDA::PrintVecBinaryOp(
+    const std::string&op, Type t,
+    Expr lhs, Expr rhs, std::ostream& os) {  // NOLINT(*)
+  // unpacking operations.
+  int lanes = t.lanes();
+
+  {
+    // default: unpack into individual ops.
+    std::string vlhs = SSAGetID(PrintExpr(lhs), lhs.type());
+    std::string vrhs = SSAGetID(PrintExpr(rhs), rhs.type());
+    std::string sret = GetUniqueName("_");
+    {
+      // delcare type.
+      this->PrintIndent();
+      this->PrintType(t, stream);
+      stream << ' ' << sret << ";\n";
+    }
+    for (int i = 0; i < lanes; ++i) {
+      std::ostringstream value_temp;
+      if (isalpha(op[0])) {
+        value_temp << op << "(";
+        PrintVecElemLoad(vlhs, lhs.type(), i, value_temp);
+        value_temp << ", ";
+        PrintVecElemLoad(vrhs, rhs.type(), i, value_temp);
+        value_temp << ")";
+      } else {
+        value_temp << "(";
+        PrintVecElemLoad(vlhs, lhs.type(), i, value_temp);
+        value_temp << op;
+        PrintVecElemLoad(vrhs, rhs.type(), i, value_temp);
+        value_temp << ")";
+      }
+      PrintVecElemStore(sret, t, i, value_temp.str());
+    }
+    os << sret;
+  }
+}
+
+void CodeGenCUDA::PrintVecElemLoad(
+    const std::string& vec, Type t, int i, std::ostream& os) {  // NOLINT(*)
+  const char access[] = {'x', 'y', 'z', 'w'};
+  CHECK(i >= 0 && i < 4);
+  os << vec << "." << access[i];
+}
+
+void CodeGenCUDA::PrintVecElemStore(
+    const std::string& vec, Type t, int i, const std::string& value) {
+  this->PrintIndent();
+  const char access[] = {'x', 'y', 'z', 'w'};
+  CHECK(i >= 0 && i < 4);
+  stream << vec << "." << access[i] << " = " << value << ";\n";
+}
+
 void CodeGenCUDA::PrintStorageSync(const std::string& sync) {
   if (sync == "shared") {
     this->PrintIndent();
@@ -43,8 +145,6 @@ void CodeGenCUDA::PrintStorageScope(
 std::unordered_map<LoweredFunc, PackedFunc>
 MakeNVRTC(Array<LoweredFunc> funcs) {
   std::ostringstream os;
-  os << "typedef int int32_t;\n"
-     << "typedef unsigned unt32_t;\n";
   bool output_ssa = false;
   for (LoweredFunc f : funcs) {
     os << CodeGenCUDA().Compile(f, output_ssa);
@@ -56,6 +156,7 @@ MakeNVRTC(Array<LoweredFunc> funcs) {
     const auto& f = PackedFunc::GetGlobal("tvm_callback_cuda_postproc");
     code = f(code).operator std::string();
   }
+    LOG(INFO) << code;
   std::string ptx;
   if (PackedFunc::GlobalExist("tvm_callback_cuda_compile")) {
     const auto& f = PackedFunc::GetGlobal("tvm_callback_cuda_compile");

src/codegen/codegen_cuda.h

@@ -25,9 +25,18 @@ class CodeGenCUDA : public CodeGenC {
    */
   std::string Compile(LoweredFunc f,
                       bool output_ssa);
+
   // override behavior
   void PrintStorageSync(const std::string& sync) final;
   void PrintStorageScope(const std::string& scope, std::ostream& os) final;  // NOLINT(*)
+  void PrintVecBinaryOp(
+      const std::string&op, Type t,
+      Expr lhs, Expr rhs, std::ostream& os) final;  // NOLINT(*)
+  void PrintType(Type t, std::ostream& os) const final; // NOLINT(*)
+  void PrintVecElemLoad(
+      const std::string& vec, Type t, int i, std::ostream& os) final;  // NOLINT(*)
+  void PrintVecElemStore(
+      const std::string& vec, Type t, int i, const std::string& value) final;
 };
 
 }  // namespace codegen

src/codegen/codegen_opencl.cc

@@ -19,7 +19,11 @@ std::string CodeGenOpenCL::Compile(
     LoweredFunc f,
     bool output_ssa) {
   this->stream << " __kernel ";
-  this->arg_addr_space_ = "__global ";
+  for (Var arg : f->args) {
+    if (arg.type().is_handle()) {
+      alloc_storage_scope_[arg.get()] = "global";
+    }
+  }
   return CodeGenC::Compile(f, output_ssa);
 }
 
@@ -34,6 +38,80 @@ void CodeGenOpenCL::PrintThreadIndexExpr(
   }
 }
 
+void CodeGenOpenCL::PrintType(Type t, std::ostream& os) const {  // NOLINT(*)
+  int lanes = t.lanes();
+  if (t.is_handle()) {
+    CHECK_EQ(lanes, 1)
+        << "do not yet support vector types";
+    os << "void*"; return;
+  }
+  bool fail = false;
+  if (t.is_float()) {
+    switch (t.bits()) {
+      case 16: os << "half"; break;
+      case 32: os << "float"; break;
+      case 64: os << "double"; break;
+      default: fail = true; break;
+    }
+    if (!fail && lanes == 1) return;
+    if (!fail && (lanes >= 2 && lanes <= 16)) {
+      os << lanes; return;
+    }
+  } else if (t.is_uint() || t.is_int()) {
+    if (t.is_uint()) {
+      os << 'u';
+    }
+    if (t.bits() == 8 && t.lanes() == 4) {
+      // directly 4 8 bit int in integer.
+      os << "int"; return;
+    }
+    switch (t.bits()) {
+      case 8: os << "char"; break;
+      case 16: os << "short"; break;
+      case 32: os << "int"; break;
+      case 64: os << "long"; break;
+      case 1: os << "int"; break;
+      default: fail = true; break;
+    }
+    if (!fail && lanes == 1) return;
+    if (!fail && (lanes >= 2 && lanes <= 16)) {
+      os << lanes; return;
+    }
+  }
+  LOG(FATAL) << "Cannot convert type " << t << " to OpenCL type";
+}
+
+void CodeGenOpenCL::PrintVecAddr(const Variable* buffer, Type t,
+                                 Expr base, std::ostream& os) {  // NOLINT(*)
+  if (!HandleTypeMatch(buffer, t.element_of())) {
+    os << '(';
+    auto it = alloc_storage_scope_.find(buffer);
+    if (it != alloc_storage_scope_.end()) {
+      PrintStorageScope(it->second, os);
+    }
+    os << ' ';
+    PrintType(t.element_of(), os);
+    os << "*)";
+  }
+  os << GetVarID(buffer) << " + ";
+  PrintExpr(base, os);
+}
+void CodeGenOpenCL::PrintVecLoad(const Variable* buffer,
+                                 Type t, Expr base,
+                                 std::ostream& os) {
+  os << "vload" << t.lanes() << "(0, ";
+  PrintVecAddr(buffer, t, base, os);
+  os << ")";
+}
+
+void CodeGenOpenCL::PrintVecStore(const Variable* buffer,
+                                  Type t, Expr base,
+                                  const std::string& value) {
+  this->PrintIndent();
+  stream << "vstore" << t.lanes() << "(" << value << ", 0, ";
+  PrintVecAddr(buffer, t, base, stream);
+  stream << ");\n";
+}
 
 void CodeGenOpenCL::PrintStorageSync(const std::string& sync) {
   if (sync == "shared") {
@@ -45,8 +123,9 @@ void CodeGenOpenCL::PrintStorageSync(const std::string& sync) {
 }
 
 void CodeGenOpenCL::PrintStorageScope(const std::string& scope, std::ostream& os) { // NOLINT(*)
-  CHECK_NE(scope, "global");
-  if (scope == "shared") {
+  if (scope == "global") {
+    os << "__global";
+  } else if (scope == "shared") {
     os << "__local ";
   }
 }
@@ -55,8 +134,6 @@ void CodeGenOpenCL::PrintStorageScope(const std::string& scope, std::ostream& os
 std::unordered_map<LoweredFunc, PackedFunc>
 MakeOpenCL(Array<LoweredFunc> funcs) {
   std::ostringstream os;
-  os << "typedef int int32_t;\n"
-     << "typedef unsigned unt32_t;\n";
   bool output_ssa = false;
   for (LoweredFunc f : funcs) {
     os << CodeGenOpenCL().Compile(f, output_ssa);

src/codegen/codegen_opencl.h

@@ -30,6 +30,16 @@ class CodeGenOpenCL : public CodeGenC {
       std::string tag, std::ostream& os) final;  // NOLINT(*)
   void PrintStorageScope(const std::string& scope, std::ostream& os) final; // NOLINT(*)
   void PrintStorageSync(const std::string& scope) final;  // NOLINT(*)
+  void PrintType(Type t, std::ostream& os) const final; // NOLINT(*)
+  void PrintVecLoad(const Variable* buffer,
+                    Type t, Expr base,
+                    std::ostream& os) final;  // NOLINT(*)
+  void PrintVecStore(const Variable* buffer,
+                      Type t, Expr base,
+                      const std::string& value) final;  // NOLINT(*)
+  // the address of load/store
+  void PrintVecAddr(const Variable* buffer, Type t,
+                    Expr base, std::ostream& os);  // NOLINT(*)
 };
 
 }  // namespace codegen

src/pass/ir_mutator.cc

@@ -74,6 +74,7 @@ TVM_STATIC_IR_FUNCTOR(IRMutator, vtable_stmt)
 .DISPATCH_TO_MUTATE_STMT(Provide)
 .DISPATCH_TO_MUTATE_STMT(Realize)
 .DISPATCH_TO_MUTATE_STMT(Store)
+.DISPATCH_TO_MUTATE_STMT(IfThenElse)
 .DISPATCH_TO_MUTATE_STMT(For)
 .DISPATCH_TO_MUTATE_STMT(Allocate)
 .DISPATCH_TO_MUTATE_STMT(Free);
@@ -195,6 +196,22 @@ Stmt IRMutator::Mutate_(const Free *op, const Stmt& s) {
   return s;
 }
 
+Stmt IRMutator::Mutate_(const IfThenElse *op, const Stmt& s) {
+  Expr condition = this->Mutate(op->condition);
+  Stmt then_case = this->Mutate(op->then_case);
+  Stmt else_case;
+  if (else_case.defined()) {
+    else_case = this->Mutate(op->else_case);
+  }
+  if (condition.same_as(op->condition) &&
+      then_case.same_as(op->then_case) &&
+      else_case.same_as(op->else_case)) {
+    return s;
+  } else {
+    return IfThenElse::make(condition, then_case, else_case);
+  }
+}
+
 TVM_STATIC_IR_FUNCTOR(IRMutator, vtable_expr)
 .DISPATCH_TO_MUTATE_EXPR(Call)
 .DISPATCH_TO_MUTATE_EXPR(Let)
@@ -363,21 +380,6 @@ TVM_STATIC_IR_FUNCTOR(IRMutator, vtable_stmt)
       return Block::make(first, rest);
     }
   })
-.set_dispatch<IfThenElse>([](const IfThenElse *op, const Stmt& s, IRMutator* m) {
-    Expr condition = m->Mutate(op->condition);
-    Stmt then_case = m->Mutate(op->then_case);
-    Stmt else_case;
-    if (else_case.defined()) {
-      else_case = m->Mutate(op->else_case);
-    }
-    if (condition.same_as(op->condition) &&
-        then_case.same_as(op->then_case) &&
-        else_case.same_as(op->else_case)) {
-      return s;
-    } else {
-      return IfThenElse::make(condition, then_case, else_case);
-    }
-  })
 .set_dispatch<Evaluate>([](const Evaluate *op, const Stmt& s, IRMutator* m) {
     Expr v = m->Mutate(op->value);
     if (v.same_as(op->value)) {

src/pass/split_host_device.cc

@@ -101,9 +101,14 @@ class IRUseDefAnalysis : public IRMutator {
   }
 
   void HandleDef(const Variable* v) {
+    CHECK(!def_count_.count(v))
+        << "variable " << v->name_hint
+        << " has already been defined, the Stmt is not SSA";
     CHECK(!use_count_.count(v))
-        << "variable is already defined";
+        << "variable " << v->name_hint
+        << " has been used before definition!";
     use_count_[v] = 0;
+    def_count_[v] = 1;
   }
 
   void HandleUse(const Expr& v) {
@@ -127,6 +132,7 @@ class IRUseDefAnalysis : public IRMutator {
   Array<IterVar> thread_axis_;
   Array<Expr> thread_extent_;
   std::unordered_map<const Variable*, int> use_count_;
+  std::unordered_map<const Variable*, int> def_count_;
 };
 
 class HostDeviceSplitter : public IRMutator {

src/pass/unroll_loop.cc

 /*!
- *  Copyright (c) 2016 by Contributors
- *  SSA related checks and pass.
- * \file ssa.cc
+ *  Copyright (c) 2017 by Contributors
+ *  Loop unrolling.
+ * \file unroll_loop.cc
  */
 #include <tvm/ir.h>
 #include <tvm/ir_pass.h>
@@ -9,7 +9,7 @@
 #include <unordered_set>
 #include <unordered_map>
 #include <vector>
-#include "../arithmetic//compute_expr.h"
+#include "../arithmetic/compute_expr.h"
 
 namespace tvm {
 namespace ir {
@@ -33,7 +33,8 @@ class LoopUnroller : public IRMutator {
     if (v2 != nullptr) {
       value = static_cast<int>(v2->value);
     }
-    bool allow_unroll = value >= 0 && value <= max_auto_step_;
+    bool allow_unroll = (op->for_type == ForType::Serial &&
+                         value >= 0 && value <= max_auto_step_);
     if (op->for_type == ForType::Unrolled) {
       CHECK_GE(value, 0)
           << "Cannot unroll non-constant loop";

src/schedule/schedule_lang.cc

@@ -57,6 +57,14 @@ TVM_STATIC_IR_FUNCTOR(IRPrinter, vtable)
             << ")";
 });
 
+TVM_STATIC_IR_FUNCTOR(IRPrinter, vtable)
+.set_dispatch<IterVarAttrNode>([](const IterVarAttrNode *op, IRPrinter *p) {
+    switch (op->iter_type) {
+      case kUnrolled: p->stream << "unroll"; break;
+      case kVectorized: p->stream << "vectorize"; break;
+    }
+  });
+
 Stage::Stage(Operation op) {
   auto n = std::make_shared<StageNode>();
   n->op = op;
@@ -246,7 +254,38 @@ void Schedule::normalize() {
   }
 }
 
+IterVarAttr::IterVarAttr(IterVarType t) {
+  std::shared_ptr<IterVarAttrNode> n = std::make_shared<IterVarAttrNode>();
+  n->iter_type = t;
+  node_ = n;
+}
+
+inline void SetAttr(StageNode* self, IterVar var, IterVarAttr attr) {
+  ArrayNode* all_vars = self->all_iter_vars.CopyOnWrite();
+  ArrayNode* leaf_vars = self->leaf_iter_vars.CopyOnWrite();
+  FindLeafVar(all_vars, leaf_vars, var);
+  auto it = self->iter_var_attrs.find(var);
+  if (it != self->iter_var_attrs.end()) {
+    CHECK_EQ((*it).second->iter_type, attr->iter_type)
+        << "IterVar's is already set to "
+        << (*it).second << " instead of " << attr;
+  } else {
+    self->iter_var_attrs.Set(var, attr);
+  }
+}
+
+Stage& Stage::vectorize(IterVar var) {   // NOLINT(*)
+  SetAttr(operator->(), var, IterVarAttr(kVectorized));
+  return *this;
+}
+
+Stage& Stage::unroll(IterVar var) {   // NOLINT(*)
+  SetAttr(operator->(), var, IterVarAttr(kUnrolled));
+  return *this;
+}
+
 TVM_REGISTER_NODE_TYPE(StageNode);
+TVM_REGISTER_NODE_TYPE(IterVarAttrNode);
 TVM_REGISTER_NODE_TYPE(SplitNode);
 TVM_REGISTER_NODE_TYPE(FuseNode);
 TVM_REGISTER_NODE_TYPE(RebaseNode);

src/schedule/schedule_ops.cc

@@ -177,6 +177,13 @@ MakeLoopNest(const Stage& sch,
     }
     // Mark the iter var in the IR, to remember the point
     if (iv->thread_tag.length() == 0) {
+      ForType for_type = ForType::Serial;
+      if (sch->iter_var_attrs.count(iv)) {
+        switch (sch->iter_var_attrs[iv]->iter_type) {
+          case kUnrolled: for_type = ForType::Unrolled; break;
+          case kVectorized: for_type = ForType::Vectorized; break;
+        }
+      }
       if (is_one(dom->extent)) {
         nest[i + 1].emplace_back(
             LetStmt::make(var, dom->min, no_op));
@@ -184,13 +191,13 @@ MakeLoopNest(const Stage& sch,
       } else if (is_zero(dom->min)) {
         nest[i + 1].emplace_back(
             For::make(var, 0, dom->extent,
-                      ForType::Serial, DeviceAPI::None, no_op));
+                      for_type, DeviceAPI::None, no_op));
         value_map[iv] = var;
       } else {
         Var idx(iv->var->name_hint + ".idx", iv->var.type());
         nest[i + 1].emplace_back(
             For::make(idx, 0, dom->extent,
-                      ForType::Serial, DeviceAPI::None, no_op));
+                      for_type, DeviceAPI::None, no_op));
         Expr new_value = dom->min + idx;
         value_map[iv] = new_value;
         nest[i + 1].emplace_back(

tests/python/integration/test_ewise.py

@@ -3,7 +3,7 @@ import numpy as np
 
 def test_add():
     # graph
-    n = tvm.Var('n')
+    n = tvm.convert(1024)
     A = tvm.placeholder((n,), name='A')
     B = tvm.placeholder((n,), name='B')
     C = tvm.compute(A.shape, lambda *i: A(*i) + B(*i), name='C')
@@ -13,26 +13,28 @@ def test_add():
     num_thread = 256
     block_x = tvm.IterVar(thread_tag="blockIdx.x")
     thread_x = tvm.IterVar((0, num_thread), thread_tag="threadIdx.x")
-    _, x = s[C].split(C.op.axis[0], factor=num_thread, outer=block_x)
+    _, x = s[C].split(C.op.axis[0], factor=num_thread*4, outer=block_x)
     _, x = s[C].split(x, outer=thread_x)
+    _, x = s[C].split(x, factor=4)
+    s[C].vectorize(x)
 
     # one line to build the function.
-    codes = []
-    fadd = tvm.build(s,
-                     args=[A, B, C],
-                     target="cuda", name="myadd",
-                     record_codes=codes)
-    for c in codes:
-        print(c)
-
-    # call the function
-    num_device = 1
-    for i in range(num_device):
-        ctx = tvm.gpu(i)
+    def check_device(target):
+        codes = []
+        fadd = tvm.build(s, [A, B, C],
+                      target, record_codes=codes,
+                      name="myadd")
+        if target == "cuda":
+            ctx = tvm.gpu(0)
+        else:
+            ctx = tvm.cl(0)
         if not ctx.enabled:
-            continue
+            return
+
+        for c in codes[1:]:
+            print(c)
         # launch the kernel.
-        n = 1027
+        n = 1024
         a = tvm.nd.array(np.random.uniform(size=n).astype(A.dtype), ctx)
         b = tvm.nd.array(np.random.uniform(size=n).astype(B.dtype), ctx)
         c = tvm.nd.array(np.zeros(n, dtype=C.dtype), ctx)
@@ -40,6 +42,10 @@ def test_add():
         np.testing.assert_allclose(
             c.asnumpy(), a.asnumpy() + b.asnumpy())
 
+    tvm.init_opencl()
+    check_device("cuda")
+    check_device("opencl")
+
 
 if __name__ == "__main__":
     test_add()

tests/python/unittest/test_lang_schedule.py

@@ -76,6 +76,21 @@ def test_fuse():
     assert any(isinstance(x, tvm.schedule.Fuse) for x in s[T].relations)
     assert tuple(s[T].leaf_iter_vars) == (fused, xi, yi)
 
+def test_vectorize():
+    m = tvm.Var('m')
+    n = tvm.Var('n')
+    A = tvm.placeholder((m, n), name='A')
+    T = tvm.compute((m, n), lambda i, j: A[i, j])
+
+    s = tvm.Schedule(T.op)
+    xo, yo, xi, yi = s[T].tile(T.op.axis[0], T.op.axis[1], x_factor=10, y_factor=5)
+    s[T].vectorize(yi)
+    s[T].unroll(xi)
+    UNROLL = 1
+    VECTORIZE = 2
+    assert s[T].iter_var_attrs[xi].iter_type == UNROLL
+    assert s[T].iter_var_attrs[yi].iter_type == VECTORIZE
+
 
 if __name__ == "__main__":
     test_schedule_create()
@@ -83,3 +98,4 @@ if __name__ == "__main__":
     test_tile()
     test_split()
     test_fuse()
+    test_vectorize()

tests/python/unittest/test_pass_unroll.py

@@ -9,11 +9,13 @@ def test_unroll_loop():
     # for i in 0 to n-1:
     stmt = tvm.make.For(
         i, n, 2, 0, 0,
-        tvm.make.For(j, 0, n, 0, 0,
+        tvm.make.For(j, 0, 8, 3, 0,
                      tvm.make.Store(Ab.data,
                                     tvm.make.Load(dtype, Ab.data, i) + 1,
                                     j + 1)))
-    stmt = tvm.ir_pass.UnrollLoop(stmt, 8)
+    assert isinstance(stmt, tvm.stmt.For)
+    stmt = tvm.ir_pass.UnrollLoop(stmt, 4)
+    assert not isinstance(stmt, tvm.stmt.For)
     print(stmt)
 
 if __name__ == "__main__":

tests/python/unittest/test_pass_vectorize.py

+import tvm
+
+def test_vectorize_loop():
+    dtype = 'int64'
+    n = tvm.Var('n')
+    Ab = tvm.Buffer((n, ), dtype)
+    i = tvm.Var('i')
+    j = tvm.Var('j')
+    VECTORIZE = 2
+    # for i in 0 to n-1:
+    stmt = tvm.make.For(
+        i, n, 2, 0, 0,
+        tvm.make.For(j, 0, 4, VECTORIZE, 0,
+                     tvm.make.Store(Ab.data,
+                                    tvm.make.Load(dtype, Ab.data, i) + 1,
+                                    j + 1)))
+    assert isinstance(stmt.body, tvm.stmt.For)
+    stmt = tvm.ir_pass.VectorizeLoop(stmt)
+    assert isinstance(stmt, tvm.stmt.For)
+    assert not isinstance(stmt.body, tvm.stmt.For)
+    print(stmt)
+
+if __name__ == "__main__":
+    test_vectorize_loop()