libgomp/
* testsuite/libgomp.c++/target-std__valarray-1.C: New.
* testsuite/libgomp.c++/target-std__valarray-1.output: Likewise.
---
.../libgomp.c++/target-std__valarray-1.C | 179 ++++++++++++++++++
.../libgomp.c++/target-std__valarray-1.output | 22 +++
2 files changed, 201 insertions(+)
create mode 100644 libgomp/testsuite/libgomp.c++/target-std__valarray-1.C
create mode 100644 libgomp/testsuite/libgomp.c++/target-std__valarray-1.output
diff --git a/libgomp/testsuite/libgomp.c++/target-std__valarray-1.C
b/libgomp/testsuite/libgomp.c++/target-std__valarray-1.C
new file mode 100644
index 00000000000..865cde2e66b
--- /dev/null
+++ b/libgomp/testsuite/libgomp.c++/target-std__valarray-1.C
@@ -0,0 +1,179 @@
+// { dg-additional-options -std=c++20 }
+// { dg-output-file target-std__valarray-1.output }
+
+#include <valarray>
+#include <ostream>
+#include <sstream>
+
+
+/*TODO Work around PR118484 "ICE during IPA pass: cp, segfault in
determine_versionability ipa-cp.cc:467".
+
+We can't:
+
+ #pragma omp declare target(std::basic_streambuf<char,
std::char_traits<char>>::basic_streambuf)
+
+... because:
+
+ error: overloaded function name ‘std::basic_streambuf<char>::__ct ’ in
clause ‘enter’
+
+Therefore, use dummy classes in '#pragma omp declare target':
+*/
+
+#pragma omp declare target
+
+// For 'std::basic_streambuf<char, std::char_traits<char> >::basic_streambuf':
+
+class dummy_basic_streambuf__char
+ : public std::basic_streambuf<char>
+{
+public:
+ dummy_basic_streambuf__char() {}
+};
+
+// For 'std::basic_ios<char, std::char_traits<char> >::basic_ios()':
+
+class dummy_basic_ios__char
+ : public std::basic_ios<char>
+{
+public:
+ dummy_basic_ios__char() {}
+};
+
+#pragma omp end declare target
+
+
+int main()
+{
+ // Due to PR120021 "Offloading vs. C++ 'std::initializer_list'", we can't
construct these on the device.
+ std::initializer_list<int> v1_i = {10, 20, 30, 40, 50};
+ const int *v1_i_data = std::data(v1_i);
+ size_t v1_i_size = v1_i.size();
+ std::initializer_list<int> v2_i = {5, 4, 3, 2, 1};
+ const int *v2_i_data = std::data(v2_i);
+ size_t v2_i_size = v2_i.size();
+ std::initializer_list<int> shiftData_i = {1, 2, 3, 4, 5};
+ const int *shiftData_i_data = std::data(shiftData_i);
+ size_t shiftData_i_size = shiftData_i.size();
+#pragma omp target \
+ defaultmap(none) \
+ map(to: v1_i_data[:v1_i_size], v1_i_size, \
+ v2_i_data[:v2_i_size], v2_i_size, \
+ shiftData_i_data[:shiftData_i_size], shiftData_i_size)
+ {
+ /* Manually set up a buffer we can stream into, similar to 'cout <<
[...]', and print it at the end of region. */
+ std::stringbuf out_b;
+ std::ostream out(&out_b);
+
+ std::valarray<int> v1(v1_i_data, v1_i_size);
+ out << "\nv1:";
+ for (auto val : v1)
+ out << " " << val;
+
+ std::valarray<int> v2(v2_i_data, v2_i_size);
+ out << "\nv2:";
+ for (auto val : v2)
+ out << " " << val;
+
+ std::valarray<int> sum = v1 + v2;
+ out << "\nv1 + v2:";
+ for (auto val : sum)
+ out << " " << val;
+
+ std::valarray<int> diff = v1 - v2;
+ out << "\nv1 - v2:";
+ for (auto val : diff)
+ out << " " << val;
+
+ std::valarray<int> product = v1 * v2;
+ out << "\nv1 * v2:";
+ for (auto val : product)
+ out << " " << val;
+
+ std::valarray<int> quotient = v1 / v2;
+ out << "\nv1 / v2:";
+ for (auto val : quotient)
+ out << " " << val;
+
+ std::valarray<int> squares = pow(v1, 2);
+ out << "\npow(v1, 2):";
+ for (auto val : squares)
+ out << " " << val;
+
+ std::valarray<int> sinhs = sinh(v2);
+ out << "\nsinh(v2):";
+ for (auto val : sinhs)
+ out << " " << val;
+
+ std::valarray<int> logs = log(v1 * v2);
+ out << "\nlog(v1 * v2):";
+ for (auto val : logs)
+ out << " " << val;
+
+ std::valarray<int> data(12);
+ for (size_t i = 0; i < data.size(); ++i)
+ data[i] = i;
+ out << "\nOriginal array:";
+ for (auto val : data)
+ out << " " << val;
+
+ std::slice slice1(2, 5, 1);
+ std::valarray<int> sliced1 = data[slice1];
+ out << "\nSlice(2, 5, 1):";
+ for (auto val : sliced1)
+ out << " " << val;
+
+ std::slice slice2(1, 4, 3);
+ std::valarray<int> sliced2 = data[slice2];
+ out << "\nSlice(1, 4, 3):";
+ for (auto val : sliced2)
+ out << " " << val;
+
+ data[slice1] = 99;
+ out << "\nArray after slice modification:";
+ for (auto val : data)
+ out << " " << val;
+
+ std::valarray<bool> mask = (v1 > 20);
+ out << "\nElements of v1 > 20:";
+ for (size_t i = 0; i < v1.size(); ++i)
+ {
+ if (mask[i])
+ out << " " << v1[i];
+ }
+
+ std::valarray<int> masked = v1[mask];
+ out << "\nMasked array:";
+ for (auto val : masked)
+ out << " " << val;
+
+ std::valarray<int> shiftData(shiftData_i_data, shiftData_i_size);
+ out << "\nOriginal shiftData:";
+ for (auto val : shiftData)
+ out << " " << val;
+
+ std::valarray<int> shifted = shiftData.shift(2);
+ out << "\nshift(2):";
+ for (auto val : shifted)
+ out << " " << val;
+
+ std::valarray<int> cshifted = shiftData.cshift(-1);
+ out << "\ncshift(-1):";
+ for (auto val : cshifted)
+ out << " " << val;
+
+ out << "\nSum(v1): " << v1.sum();
+ out << "\nMin(v1): " << v1.min();
+ out << "\nMax(v1): " << v1.max();
+
+ out << "\n";
+
+ /* Terminate with a NUL. Otherwise, we'd have to use:
+ __builtin_printf("%.*s", (int) out_b_sv.size(), out_b_sv.data());
+ ... which nvptx 'printf', as implemented via PTX 'vprintf', doesn't
support (TODO). */
+ out << '\0';
+ std::string_view out_b_sv = out_b.view();
+ __builtin_printf("%s", out_b_sv.data());
+ }
+
+ return 0;
+}
diff --git a/libgomp/testsuite/libgomp.c++/target-std__valarray-1.output
b/libgomp/testsuite/libgomp.c++/target-std__valarray-1.output
new file mode 100644
index 00000000000..c441e066683
--- /dev/null
+++ b/libgomp/testsuite/libgomp.c++/target-std__valarray-1.output
@@ -0,0 +1,22 @@
+
+v1: 10 20 30 40 50
+v2: 5 4 3 2 1
+v1 + v2: 15 24 33 42 51
+v1 - v2: 5 16 27 38 49
+v1 * v2: 50 80 90 80 50
+v1 / v2: 2 5 10 20 50
+pow(v1, 2): 100 400 900 1600 2500
+sinh(v2): 74 27 10 3 1
+log(v1 * v2): 3 4 4 4 3
+Original array: 0 1 2 3 4 5 6 7 8 9 10 11
+Slice(2, 5, 1): 2 3 4 5 6
+Slice(1, 4, 3): 1 4 7 10
+Array after slice modification: 0 1 99 99 99 99 99 7 8 9 10 11
+Elements of v1 > 20: 30 40 50
+Masked array: 30 40 50
+Original shiftData: 1 2 3 4 5
+shift(2): 3 4 5 0 0
+cshift(-1): 5 1 2 3 4
+Sum(v1): 150
+Min(v1): 10
+Max(v1): 50
--
2.34.1
