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* [PATCH PR90078]Capping comp_cost computation in ivopts
@ 2019-04-17  7:00 bin.cheng
  2019-04-17  7:19 ` Jakub Jelinek
  0 siblings, 1 reply; 8+ messages in thread
From: bin.cheng @ 2019-04-17  7:00 UTC (permalink / raw)
  To: GCC Patches

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Hi,
As discussed in PR90078, this patch checks possible infinite_cost overflow in ivopts.
Also as discussed, overflow happens mostly because of cost scaling wrto bb_freq/loop_freq.
For the moment, we only implement capping in comp_cost operators, while in next
stage1, we may instead implement capping in get_scaled_computation_cost_at with
more supporting benchmark data.

BTW, I think switching costs around comparison between infinite_cost is unnecessary
since there will be no overflow in integer after capping with infinite_cost.

Bootstrap and test on x86_64, is it OK?

Thanks,
bin

2019-04-17  Bin Cheng  <bin.cheng@linux.alibaba.com>

        PR tree-optimization/92078
        * tree-ssa-loop-ivopts.c (comp_cost::operator +,-,+=,-+,/=,*=): Add
        checks for infinite_cost overflow.

2018-04-17  Bin Cheng  <bin.cheng@linux.alibaba.com>

        PR tree-optimization/92078
        * gcc/testsuite/g++.dg/tree-ssa/pr90078.C: New test.

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diff --git a/gcc/testsuite/g++.dg/tree-ssa/pr90078.C b/gcc/testsuite/g++.dg/tree-ssa/pr90078.C
new file mode 100644
index 00000000000..e36f50e9d8a
--- /dev/null
+++ b/gcc/testsuite/g++.dg/tree-ssa/pr90078.C
@@ -0,0 +1,199 @@
+// { dg-do compile }
+// { dg-options "-std=c++14 -O2 -ftemplate-depth=1000000" }
+
+template <class T, int Dim0, int Dim1, int Dim2> struct Tensor3;
+template <class A, class T, int Dim0, int Dim1, int Dim2, char i, char j,
+          char k>
+struct Tensor3_Expr;
+
+template <class T, int Dim0, int Dim1, int Dim2, int Dim3> struct Tensor4;
+template <class A, class T, int Dim0, int Dim1, int Dim2, int Dim3, char i,
+          char j, char k, char l>
+struct Tensor4_Expr;
+
+template <char i, int Dim> struct Index
+{};
+template <const int N> struct Number
+{
+  Number(){};
+  operator int() const { return N; }
+};
+
+template <class T, int Tensor_Dim0, int Tensor_Dim1, int Tensor_Dim2>
+struct Tensor3
+{
+  T data[Tensor_Dim0][Tensor_Dim1][Tensor_Dim2];
+
+  T operator()(const int N1, const int N2, const int N3) const
+  {
+    return data[N1][N2][N3];
+  }
+
+  template <char i, char j, char k, int Dim0, int Dim1, int Dim2>
+  Tensor3_Expr<const Tensor3<T, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2>, T,
+               Dim0, Dim1, Dim2, i, j, k>
+  operator()(const Index<i, Dim0>, const Index<j, Dim1>,
+             const Index<k, Dim2>) const
+  {
+    return Tensor3_Expr<const Tensor3<T, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2>,
+                        T, Dim0, Dim1, Dim2, i, j, k>(*this);
+  }
+};
+
+template <class A, class T, int Dim0, int Dim1, int Dim2, char i, char j,
+          char k>
+struct Tensor3_Expr
+{
+  A iter;
+
+  Tensor3_Expr(const A &a) : iter(a) {}
+  T operator()(const int N1, const int N2, const int N3) const
+  {
+    return iter(N1, N2, N3);
+  }
+};
+
+template <class A, class T, int Tensor_Dim0, int Tensor_Dim1, int Tensor_Dim2,
+          int Dim0, int Dim1, int Dim2, char i, char j, char k>
+struct Tensor3_Expr<Tensor3<A, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2>, T, Dim0,
+                   Dim1, Dim2, i, j, k>
+{
+  Tensor3<A, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2> &iter;
+
+  Tensor3_Expr(Tensor3<A, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2> &a) : iter(a)
+  {}
+  T operator()(const int N1, const int N2, const int N3) const
+  {
+    return iter(N1, N2, N3);
+  }
+};
+
+template <class A, class B, class T, class U, int Dim0, int Dim1, int Dim23,
+          int Dim4, int Dim5, char i, char j, char k, char l, char m>
+struct Tensor3_times_Tensor3_21
+{
+  Tensor3_Expr<A, T, Dim0, Dim1, Dim23, i, j, k> iterA;
+  Tensor3_Expr<B, U, Dim23, Dim4, Dim5, k, l, m> iterB;
+
+  template <int CurrentDim>
+  T eval(const int N1, const int N2, const int N3, const int N4,
+         const Number<CurrentDim> &) const
+  {
+    return iterA(N1, N2, CurrentDim - 1) * iterB(CurrentDim - 1, N3, N4)
+           + eval(N1, N2, N3, N4, Number<CurrentDim - 1>());
+  }
+  T eval(const int N1, const int N2, const int N3, const int N4,
+         const Number<1> &) const
+  {
+    return iterA(N1, N2, 0) * iterB(0, N3, N4);
+  }
+
+  Tensor3_times_Tensor3_21(
+    const Tensor3_Expr<A, T, Dim0, Dim1, Dim23, i, j, k> &a,
+    const Tensor3_Expr<B, U, Dim23, Dim4, Dim5, k, l, m> &b)
+      : iterA(a), iterB(b)
+  {}
+  T operator()(const int &N1, const int &N2, const int &N3,
+               const int &N4) const
+  {
+    return eval(N1, N2, N3, N4, Number<Dim23>());
+  }
+};
+
+template <class A, class B, class T, class U, int Dim0, int Dim1, int Dim23,
+          int Dim4, int Dim5, char i, char j, char k, char l, char m>
+Tensor4_Expr<Tensor3_times_Tensor3_21<A, B, T, U, Dim0, Dim1, Dim23, Dim4,
+                                      Dim5, i, j, k, l, m>,
+             T, Dim0, Dim1, Dim4, Dim5, i, j, l, m>
+operator*(const Tensor3_Expr<A, T, Dim0, Dim1, Dim23, i, j, k> &a,
+          const Tensor3_Expr<B, U, Dim23, Dim4, Dim5, k, l, m> &b)
+{
+  using TensorExpr = Tensor3_times_Tensor3_21<A, B, T, U, Dim0, Dim1, Dim23,
+                                              Dim4, Dim5, i, j, k, l, m>;
+  return Tensor4_Expr<TensorExpr, T, Dim0, Dim1, Dim4, Dim5, i, j, l, m>(
+    TensorExpr(a, b));
+};
+
+template <class T, int Tensor_Dim0, int Tensor_Dim1, int Tensor_Dim2,
+          int Tensor_Dim3>
+struct Tensor4
+{
+  T data[Tensor_Dim0][Tensor_Dim1][Tensor_Dim2][Tensor_Dim3];
+
+  Tensor4() {}
+  T &operator()(const int N1, const int N2, const int N3, const int N4)
+  {
+    return data[N1][N2][N3][N4];
+  }
+
+  template <char i, char j, char k, char l, int Dim0, int Dim1, int Dim2,
+            int Dim3>
+  Tensor4_Expr<Tensor4<T, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2, Tensor_Dim3>,
+               T, Dim0, Dim1, Dim2, Dim3, i, j, k, l>
+  operator()(const Index<i, Dim0>, const Index<j, Dim1>, const Index<k, Dim2>,
+             const Index<l, Dim3>)
+  {
+    return Tensor4_Expr<
+      Tensor4<T, Tensor_Dim0, Tensor_Dim1, Tensor_Dim2, Tensor_Dim3>, T, Dim0,
+      Dim1, Dim2, Dim3, i, j, k, l>(*this);
+  };
+};
+
+template <class A, class T, int Dim0, int Dim1, int Dim2, int Dim3, char i,
+          char j, char k, char l>
+struct Tensor4_Expr
+{
+  A iter;
+
+  Tensor4_Expr(const A &a) : iter(a) {}
+  T operator()(const int N1, const int N2, const int N3, const int N4) const
+  {
+    return iter(N1, N2, N3, N4);
+  }
+};
+
+template <class A, class T, int Dim0, int Dim1, int Dim2, int Dim3, char i,
+          char j, char k, char l>
+struct Tensor4_Expr<Tensor4<A, Dim0, Dim1, Dim2, Dim3>, T, Dim0, Dim1, Dim2,
+                   Dim3, i, j, k, l>
+{
+  Tensor4<A, Dim0, Dim1, Dim2, Dim3> &iter;
+
+  Tensor4_Expr(Tensor4<A, Dim0, Dim1, Dim2, Dim3> &a) : iter(a) {}
+  T operator()(const int N1, const int N2, const int N3, const int N4) const
+  {
+    return iter(N1, N2, N3, N4);
+  }
+
+  template <class B, class U, int Dim1_0, int Dim1_1, int Dim1_2, int Dim1_3,
+            char i_1, char j_1, char k_1, char l_1>
+  auto &operator=(const Tensor4_Expr<B, U, Dim1_0, Dim1_1, Dim1_2, Dim1_3, i_1,
+                                     j_1, k_1, l_1> &rhs)
+  {
+    for(int ii = 0; ii < Dim0; ++ii)
+      for(int jj = 0; jj < Dim1; ++jj)
+        for(int kk = 0; kk < Dim2; ++kk)
+          for(int ll = 0; ll < Dim3; ++ll)
+            {
+              iter(ii, jj, kk, ll) = rhs(ii, jj, kk, ll);
+            }
+    return *this;
+  }
+};
+
+int main()
+{
+  Tensor3<float, 100, 100, 1000> t1;
+  Tensor3<float, 1000, 100, 100> t2;
+
+  Index<'l', 100> l;
+  Index<'m', 100> m;
+  Index<'k', 1000> k;
+  Index<'n', 100> n;
+  Index<'o', 100> o;
+
+  Tensor4<float, 100, 100, 100, 100> res;
+  res(l, m, n, o) = t1(l, m, k) * t2(k, n, o);
+  return 0;
+}
+
diff --git a/gcc/tree-ssa-loop-ivopts.c b/gcc/tree-ssa-loop-ivopts.c
index a2b6b2b2312..4ca1f0e9686 100644
--- a/gcc/tree-ssa-loop-ivopts.c
+++ b/gcc/tree-ssa-loop-ivopts.c
@@ -243,6 +243,9 @@ operator+ (comp_cost cost1, comp_cost cost2)
   if (cost1.infinite_cost_p () || cost2.infinite_cost_p ())
     return infinite_cost;
 
+  if (cost1.cost + cost2.cost >= infinite_cost.cost)
+    return infinite_cost;
+
   cost1.cost += cost2.cost;
   cost1.complexity += cost2.complexity;
 
@@ -256,6 +259,8 @@ operator- (comp_cost cost1, comp_cost cost2)
     return infinite_cost;
 
   gcc_assert (!cost2.infinite_cost_p ());
+  if (cost1.cost - cost2.cost >= infinite_cost.cost)
+    return infinite_cost;
 
   cost1.cost -= cost2.cost;
   cost1.complexity -= cost2.complexity;
@@ -276,6 +281,8 @@ comp_cost::operator+= (HOST_WIDE_INT c)
   if (infinite_cost_p ())
     return *this;
 
+  if (this->cost + c >= infinite_cost.cost)
+    return infinite_cost;
   this->cost += c;
 
   return *this;
@@ -287,6 +294,8 @@ comp_cost::operator-= (HOST_WIDE_INT c)
   if (infinite_cost_p ())
     return *this;
 
+  if (this->cost - c >= infinite_cost.cost)
+    return infinite_cost;
   this->cost -= c;
 
   return *this;
@@ -295,6 +304,7 @@ comp_cost::operator-= (HOST_WIDE_INT c)
 comp_cost
 comp_cost::operator/= (HOST_WIDE_INT c)
 {
+  gcc_assert (c != 0);
   if (infinite_cost_p ())
     return *this;
 
@@ -309,6 +319,9 @@ comp_cost::operator*= (HOST_WIDE_INT c)
   if (infinite_cost_p ())
     return *this;
 
+  if (this->cost * c >= infinite_cost.cost)
+    return infinite_cost;
+
   this->cost *= c;
 
   return *this;

^ permalink raw reply	[flat|nested] 8+ messages in thread
end of thread, other threads:[~2019-05-06 10:27 UTC | newest]

Thread overview: 8+ messages (download: mbox.gz / follow: Atom feed)
-- links below jump to the message on this page --
2019-04-17  7:00 [PATCH PR90078]Capping comp_cost computation in ivopts bin.cheng
2019-04-17  7:19 ` Jakub Jelinek
2019-04-17 11:14   ` Bin.Cheng
2019-04-17 11:35     ` Jakub Jelinek
2019-05-05  6:02       ` bin.cheng
2019-05-06 10:11         ` Richard Biener
2019-05-06 10:24           ` Bin.Cheng
2019-05-06 10:27             ` Richard Biener

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