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tamaas/tests/test_loop.cpp
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test_loop.cpp
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/**
*
* @author Lucas Frérot <lucas.frerot@epfl.ch>
*
* @section LICENSE
*
* Copyright (©) 2017 EPFL (Ecole Polytechnique Fédérale de
* Lausanne) Laboratory (LSMS - Laboratoire de Simulation en Mécanique des
* Solides)
*
* Tamaas is free software: you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation, either version 3 of the License, or (at your option) any
* later version.
*
* Tamaas is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Tamaas. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include "test.hh"
#include "grid.hh"
#include "static_types.hh"
#include "loop.hh"
/* -------------------------------------------------------------------------- */
/* WARNING: here we cannot use lambdas for tests because GoogleTest declares */
/* test functions as private members of classes which is incompatible with */
/* cuda's extended lambdas. I know... it's f*cking stupid */
/* -------------------------------------------------------------------------- */
using namespace tamaas;
template <typename T>
struct AddOneInplace {
CUDA_LAMBDA void operator()(T& x) { x += 1; }
};
// Testing loops on one grid
TEST(TestLoops, OneArgument) {
Grid<Real, 1> grid({20}, 1);
Grid<Real, 1> solution({20}, 1);
auto add_one = [] (Real & x) { return x + 1; };
std::iota(grid.begin(), grid.end(), 1);
// Makeing solution
std::transform(grid.begin(), grid.end(), solution.begin(), add_one);
auto add_one_inplace = AddOneInplace<Real>();
Loop::loop(add_one_inplace, grid);
ASSERT_TRUE(compare(grid, solution, AreFloatEqual())) << "One argument loop failed";
}
struct PrimalTest {
CUDA_LAMBDA void operator()(Int& primal, Int& val) {
val = (primal > 0)? -1:1;
}
};
// Testing loops on two grids
TEST(TestLoops, TwoArguments) {
// Why no ints?
Grid<Int, 2> grid({20, 20}, 1);
Grid<Int, 2> primal({20, 20}, 1);
Grid<Int, 2> solution({20, 20}, 1);
primal(0, 0) = 1; primal(0, 1) = 1;
primal(1, 0) = 1; primal(1, 1) = 1;
std::transform(primal.begin(), primal.end(), solution.begin(),
[] (Int & primal) {
return (primal > 0)? -1:1;
});
auto primal_test = PrimalTest();
Loop::loop(primal_test, primal, grid);
ASSERT_TRUE(compare(solution, grid)) << "Two argument loop failed";
}
struct AssignUInt {
CUDA_LAMBDA void operator()(UInt& x, UInt i) {
x = i;
}
};
// Testing an enumeration
TEST(TestLoops, Enumeration) {
Grid<UInt, 1> grid({100}, 1);
Grid<UInt, 1> solution({100}, 1);
std::iota(solution.begin(), solution.end(), 0);
auto assign_uint = AssignUInt();
Loop::loop(assign_uint, grid, Loop::range(100));
ASSERT_TRUE(compare(solution, grid)) << "Enumeration loop failed";
}
/* -------------------------------------------------------------------------- */
struct Identity {
CUDA_LAMBDA UInt operator()(UInt& x) const { return x; }
};
// Testing one grid reductions
TEST(TestReductions, OneArgument) {
Grid<UInt, 1> grid({6}, 1);
std::iota(grid.begin(), grid.end(), 1);
const auto id = Identity();
// Sum reduction
UInt sol = std::accumulate(grid.begin(), grid.end(), 0, std::plus<UInt>());
UInt red = Loop::reduce<operation::plus>(id, grid);
ASSERT_TRUE(sol == red) << "Addition reduction failed on one argument";
// Product reduction
sol = std::accumulate(grid.begin(), grid.end(), 1, std::multiplies<UInt>());
red = Loop::reduce<operation::times>(id, grid);
ASSERT_TRUE(sol == red) << "Multiplication reduction failed on one argument";
// Min reduction
sol = *std::min_element(grid.begin(), grid.end());
red = Loop::reduce<operation::min>(id, grid);
ASSERT_TRUE(sol == red) << "Min reduction failed on one argument";
// Max reduction
sol = *std::max_element(grid.begin(), grid.end());
red = Loop::reduce<operation::max>(id, grid);
ASSERT_TRUE(sol == red) << "Max reduction failed on one argument";
}
struct PrimalReduce {
CUDA_LAMBDA UInt operator()(UInt& p, UInt& val) {
return (p > 0)? val:0;
}
};
TEST(TestReductions, TwoArguments) {
Grid<UInt, 1> grid({20}, 1);
Grid<UInt, 1> primal({20}, 1);
grid = 1;
primal(0) = 1;
primal(1) = 1;
auto primal_reduce = PrimalReduce();
// Reduce on values where primal > 0
UInt red = Loop::reduce<operation::plus>(primal_reduce, primal, grid);
ASSERT_TRUE(red == 2) << "Two args reduction failed";
}
/* -------------------------------------------------------------------------- */
template <typename T> using WrapVector = VectorProxy<T, 2>;
struct AddOneVector {
CUDA_LAMBDA void operator()(WrapVector<UInt> x) {
x(0) += 1;
}
};
TEST(TestStridedLoops, VectorStride) {
Grid<UInt, 2> grid({10, 10}, 2);
std::iota(grid.begin(), grid.end(), 1);
Grid<UInt, 2> solution({10, 10}, 2);
solution = grid;
std::for_each(solution.begin(), solution.end(), [] (UInt & x) {
if (x % 2 == 1)
x += 1;
});
auto add_one_inplace = AddOneVector();
Loop::loop(add_one_inplace, range<WrapVector<UInt>>(grid));
ASSERT_TRUE(compare(solution, grid)) << "Static vector strided loop failed";
}
template <typename T> using WrapMatrix = MatrixProxy<T, 2, 2>;
struct SetOneMatrix {
CUDA_LAMBDA void operator()(WrapMatrix<UInt> x) {
x(0, 0) = 1;
x(1, 1) = 1;
}
};
TEST(TestStridedLoops, MatrixStride) {
Grid<UInt, 2> grid({10, 10}, 4);
Grid<UInt, 2> solution({10, 10}, 4);
std::iota(solution.begin(), solution.end(), 0);
std::for_each(solution.begin(), solution.end(), [] (UInt & x) {
if (x % 4 == 0 || x % 4 == 3)
x = 1;
else
x = 0;
});
auto set_one = SetOneMatrix();
Loop::loop(set_one, range<WrapMatrix<UInt>>(grid));
ASSERT_TRUE(compare(solution, grid)) << "Static matrix strided loop failed";
}
struct VectorReduction {
CUDA_LAMBDA Vector<UInt, 3> operator()(VectorProxy<UInt, 3> v) const {
return v;
}
};
struct BroadcastSet123 {
CUDA_LAMBDA inline void operator()(VectorProxy<UInt, 3> v) const {
v(0) = 1;
v(1) = 2;
v(2) = 3;
}
};
TEST(TestStridedReduction, VectorReduce) {
Grid<UInt, 2> grid({10, 10}, 3);
Loop::loop(BroadcastSet123(), range<VectorProxy<UInt, 3>>(grid));
auto res = Loop::reduce<operation::plus>(
VectorReduction(), range<VectorProxy<UInt, 3>>(grid));
ASSERT_EQ(res(0), 100);
ASSERT_EQ(res(1), 200);
ASSERT_EQ(res(2), 300);
}
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