Add basic Kokkos support for the original tests of vgvassilev#783

This commit adds a test from the original Kokkos PR vgvassilev#783
and provides the implementation of the simplest Kokkos
features in the form of custom pushforwards. This commit
only addresses the forward mode.

include/clad/Differentiator/KokkosBuiltins.h

@@ -0,0 +1,55 @@
+// This header file contains the implementation of the Kokkos framework
+// differentiation support in Clad in the form of custom pushforwards and
+// pullbacks. Please include it manually to use Clad on Kokkos code.
+
+#ifndef CLAD_DIFFERENTIATOR_KOKKOSBUILTINS_H
+#define CLAD_DIFFERENTIATOR_KOKKOSBUILTINS_H
+
+#include <Kokkos_Core.hpp>
+#include "clad/Differentiator/Differentiator.h"
+
+namespace clad::custom_derivatives {
+namespace class_functions {
+/// Kokkos arrays
+template <class DataType, class... ViewParams>
+clad::ValueAndPushforward<Kokkos::View<DataType, ViewParams...>,
+                          Kokkos::View<DataType, ViewParams...>>
+constructor_pushforward(
+    clad::ConstructorPushforwardTag<Kokkos::View<DataType, ViewParams...>>,
+    const ::std::string& name, const size_t& idx0, const size_t& idx1,
+    const size_t& idx2, const size_t& idx3, const size_t& idx4,
+    const size_t& idx5, const size_t& idx6, const size_t& idx7,
+    const ::std::string& _d_name, const size_t& _d_idx0, const size_t& _d_idx1,
+    const size_t& _d_idx2, const size_t& _d_idx3, const size_t& _d_idx4,
+    const size_t& _d_idx5, const size_t& _d_idx6, const size_t& _d_idx7) {
+  return {Kokkos::View<DataType, ViewParams...>(name, idx0, idx1, idx2, idx3,
+                                                idx4, idx5, idx6, idx7),
+          Kokkos::View<DataType, ViewParams...>(
+              "_diff_" + name, idx0, idx1, idx2, idx3, idx4, idx5, idx6, idx7)};
+}
+} // namespace class_functions
+
+/// Kokkos functions
+namespace Kokkos {
+template <typename View1, typename View2, typename T>
+inline void deep_copy_pushforward(const View1& dst, const View2& src, T param,
+                                  const View1& _d_dst, const View2& _d_src,
+                                  T _d_param) {
+  deep_copy(dst, src);
+  deep_copy(_d_dst, _d_src);
+}
+
+template <class ExecPolicy, class FunctorType>
+inline void parallel_for_pushforward(const ::std::string& str,
+                                     const ExecPolicy& policy,
+                                     const FunctorType& functor,
+                                     const ::std::string& _d_str,
+                                     const ExecPolicy& _d_policy,
+                                     const FunctorType& _d_functor) {
+  // TODO: implement parallel_for_pushforward
+  return;
+}
+} // namespace Kokkos
+} // namespace clad::custom_derivatives
+
+#endif // CLAD_DIFFERENTIATOR_KOKKOSBUILTINS_H

unittests/Kokkos/CMakeLists.txt

@@ -1,5 +1,6 @@
 add_clad_unittest(KokkosTests
   main.cpp
+  ViewAccess.cpp
   ViewBasics.cpp
   ParallelReduce.cpp
   ParallelFor.cpp

unittests/Kokkos/TestUtils.h

@@ -3,11 +3,10 @@
 #ifndef KOKKOS_UNITTEST_UTILS
 #define KOKKOS_UNITTEST_UTILS
 
-template <typename T> // comparison with the finite difference approx. has been
-                      // tested in the initial PR for Kokkos-aware Clad by Kim
-                      // Liegeois
-T finite_difference_tangent(std::function<T(T)> func, const T& x,
-                            const T& epsilon) {
+template <typename F, typename T> // comparison with the finite difference
+                                  // approx. has been tested in the initial PR
+                                  // for Kokkos-aware Clad by Kim Liegeois
+T finite_difference_tangent(F func, const T& x, const T& epsilon) {
   return (func(x + epsilon) - func(x - epsilon)) / (2 * epsilon);
 }
 

unittests/Kokkos/ViewAccess.cpp

@@ -0,0 +1,73 @@
+// Tests originally created by Kim Liegeois
+
+#include "TestUtils.h"
+#include <Kokkos_Core.hpp>
+#include "clad/Differentiator/Differentiator.h"
+#include "clad/Differentiator/KokkosBuiltins.h"
+#include "gtest/gtest.h"
+
+double f(double x, double y) {
+
+  const int N1 = 4;
+
+  Kokkos::View<double* [4], Kokkos::LayoutLeft, Kokkos::HostSpace> a("a", N1);
+  Kokkos::View<double* [4], Kokkos::LayoutLeft, Kokkos::HostSpace> b("b", N1);
+
+  a(0, 0) = x;
+  b(0, 0) = y;
+
+  b(0, 0) += a(0, 0) * b(0, 0);
+
+  return a(0, 0) * a(0, 0) * b(0, 0) + b(0, 0);
+}
+
+double f_2(double x, double y) {
+
+  const int N1 = 4;
+
+  Kokkos::View<double* [4], Kokkos::LayoutLeft, Kokkos::HostSpace> a("a", N1);
+  Kokkos::View<double* [4], Kokkos::LayoutLeft, Kokkos::HostSpace> b("b", N1);
+
+  Kokkos::deep_copy(a, 3 * x + y);
+  b(0, 0) = x;
+  Kokkos::deep_copy(b, a);
+
+  b(0, 0) += a(0, 0) * b(0, 0);
+
+  return a(0, 0);
+}
+
+TEST(ViewAccess, Test1) {
+  EXPECT_NEAR(f(0, 1), 1, 1e-8);
+  EXPECT_NEAR(f(0, 2), 2, 1e-8);
+}
+
+TEST(ViewAccess, Test2) {
+
+  double tolerance = 1e-8;
+  double epsilon = 1e-6;
+
+  auto f_x = clad::differentiate(f, "x");
+
+  std::function<double(double)> f_tmp = [](double x) { return f(x, 4.); };
+  double dx_f_FD = finite_difference_tangent(f_tmp, 3., epsilon);
+
+  EXPECT_NEAR(f_x.execute(3, 4), dx_f_FD, tolerance * dx_f_FD);
+
+  auto f_2_x = clad::differentiate(f_2, "x");
+
+  std::function<double(double)> f_2_tmp = [](double x) { return f_2(x, 4.); };
+  double dx_f_2_FD = finite_difference_tangent(f_2_tmp, 3., epsilon);
+  EXPECT_NEAR(f_2_x.execute(3, 4), dx_f_2_FD, tolerance * dx_f_2_FD);
+
+  //   TODO: uncomment this once it has been implemented
+  //   auto f_grad_exe = clad::gradient(f);
+  //   double dx, dy;
+  //   f_grad_exe.execute(3., 4., &dx, &dy);
+  //   EXPECT_NEAR(f_x.execute(3, 4),dx,tolerance*dx);
+
+  //   double dx_2, dy_2;
+  //   auto f_2_grad_exe = clad::gradient(f_2);
+  //   f_2_grad_exe.execute(3., 4., &dx_2, &dy_2);
+  //   EXPECT_NEAR(f_2_x.execute(3, 4),dx_2,tolerance*dx_2);
+}

unittests/Kokkos/ViewBasics.cpp

@@ -4,12 +4,11 @@
 // it has been modified to match gtest guidelines and improve readability
 
 #include "ParallelAdd.h"
-#include "TestUtils.h"
 #include <Kokkos_Core.hpp>
 #include "clad/Differentiator/Differentiator.h"
 #include "gtest/gtest.h"
 
-double f(double x, double y) {
+double f_basics(double x, double y) {
   const int N = 2;
 
   Kokkos::View<double* [N], Kokkos::HostSpace> a("a", N);
@@ -27,10 +26,10 @@ TEST(ViewBasics, TestAccessForward) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_x = clad::differentiate(f, "x");
+  // auto f_x = clad::differentiate(f_basics, "x");
   // for (double y = 3; y <= 5; y += 1) {
-  //   std::function<double(double)> f_tmp = [y](double t){ return f(t, y); };
-  //   for (double x = 3; x <= 5; x += 1) {
+  //   std::function<double(double)> f_tmp = [y](double t){ return f_basics(t,
+  //   y); }; for (double x = 3; x <= 5; x += 1) {
   //     double f_x_ex = f_x.execute(x, y);
   //     double dx_f_FD = finite_difference_tangent(f_tmp, x, eps);
   //     EXPECT_NEAR(f_x_ex, dx_f_FD, abs(tau*dx_f_FD));
@@ -44,10 +43,10 @@ TEST(ViewBasics, TestAccessReverse) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_grad_exe = clad::gradient(f);
+  // auto f_grad_exe = clad::gradient(f_basics);
   // for (double y = 3; y <= 5; y += 1) {
-  //   std::function<double(double)> f_tmp = [y](double t){ return f(t, y); };
-  //   for (double x = 3; x <= 5; x += 1) {
+  //   std::function<double(double)> f_tmp = [y](double t){ return f_basics(t,
+  //   y); }; for (double x = 3; x <= 5; x += 1) {
   //     double dx_f_FD = finite_difference_tangent(f_tmp, x, eps);
   //     double dx, dy;
   //     f_grad_exe.execute(x, y, &dx, &dy);
@@ -56,7 +55,7 @@ TEST(ViewBasics, TestAccessReverse) {
   // }
 }
 
-double f_2(double x, double y) {
+double f_basics_deep_copy(double x, double y) {
   const int N = 2;
 
   Kokkos::View<double* [4], Kokkos::LayoutLeft, Kokkos::HostSpace> a("a", N);
@@ -77,10 +76,11 @@ TEST(ViewBasics, TestDeepCopyForward) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_x = clad::differentiate(f_2, "x");
+  // auto f_x = clad::differentiate(f_basics_deep_copy, "x");
   // for (double y = 3; y <= 5; y += 1) {
-  //   std::function<double(double)> f_tmp = [y](double t){ return f_2(t, y); };
-  //   for (double x = 3; x <= 5; x += 1) {
+  //   std::function<double(double)> f_tmp = [y](double t){ return
+  //   f_basics_deep_copy(t, y);
+  //   }; for (double x = 3; x <= 5; x += 1) {
   //     double f_x_ex = f_x.execute(x, y);
   //     double dx_f_FD = finite_difference_tangent(f_tmp, x, eps);
   //     EXPECT_NEAR(f_x_ex, dx_f_FD, abs(tau*dx_f_FD));
@@ -94,10 +94,11 @@ TEST(ViewBasics, TestDeepCopyReverse) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_grad_exe = clad::gradient(f_2);
+  // auto f_grad_exe = clad::gradient(f_basics_deep_copy);
   // for (double y = 3; y <= 5; y += 1) {
-  //   std::function<double(double)> f_tmp = [y](double t){ return f_2(t, y); };
-  //   for (double x = 3; x <= 5; x += 1) {
+  //   std::function<double(double)> f_tmp = [y](double t){ return
+  //   f_basics_deep_copy(t, y);
+  //   }; for (double x = 3; x <= 5; x += 1) {
   //     double dx_f_FD = finite_difference_tangent(f_tmp, x, eps);
   //     double dx, dy;
   //     f_grad_exe.execute(x, y, &dx, &dy);
@@ -106,7 +107,7 @@ TEST(ViewBasics, TestDeepCopyReverse) {
   // }
 }
 
-double f_3(double x, double y) {
+double f_basics_deep_copy_2(double x, double y) {
   const int N = 2;
 
   Kokkos::View<double*, Kokkos::LayoutLeft, Kokkos::HostSpace> a("a", N);
@@ -130,10 +131,11 @@ TEST(ViewBasics, TestDeepCopy2Forward) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_y = clad::differentiate(f_3, "y");
+  // auto f_y = clad::differentiate(f_basics_deep_copy_2, "y");
   // for (double x = 3; x <= 5; x += 1) {
-  //   std::function<double(double)> f_tmp = [x](double t){ return f_3(x, t); };
-  //   for (double y = 3; y <= 5; y += 1) {
+  //   std::function<double(double)> f_tmp = [x](double t){ return
+  //   f_basics_deep_copy_2(x, t);
+  //   }; for (double y = 3; y <= 5; y += 1) {
   //     double f_y_ex = f_y.execute(x, y);
   //     double dy_f_FD = finite_difference_tangent(f_tmp, y, eps);
   //     EXPECT_NEAR(f_y_ex, dy_f_FD, abs(tau*dy_f_FD));
@@ -147,10 +149,11 @@ TEST(ViewBasics, TestDeepCopy2Reverse) {
   // const double tau = 1e-6; // tolerance
 
   // // TODO: uncomment this once it has been implemented
-  // auto f_grad_exe = clad::gradient(f_3);
+  // auto f_grad_exe = clad::gradient(f_basics_deep_copy_2);
   // for (double x = 3; x <= 5; x += 1) {
-  //   std::function<double(double)> f_tmp = [x](double t){ return f_3(x, t); };
-  //   for (double y = 3; y <= 5; y += 1) {
+  //   std::function<double(double)> f_tmp = [x](double t){ return
+  //   f_basics_deep_copy_2(x, t);
+  //   }; for (double y = 3; y <= 5; y += 1) {
   //     double dy_f_FD = finite_difference_tangent(f_tmp, y, eps);
   //     double dx, dy;
   //     f_grad_exe.execute(x, y, &dx, &dy);