[SYCL][CUDA] Adds cuda test for joint_matrix_apply.

SYCL/Matrix/joint_matrix_apply_cuda.cpp

@@ -0,0 +1,124 @@
+//==------------ joint_matrix_apply_cuda.cpp  - DPC++ joint_matrix----------==//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+// REQUIRES: cuda
+// RUN: %clangxx -fsycl -fsycl-targets=%sycl_triple -Xsycl-target-backend --cuda-gpu-arch=sm_80 %s -o %t.out
+// RUN: %t.out
+
+#include <sycl/sycl.hpp>
+
+using namespace sycl;
+using namespace sycl::ext::oneapi::experimental::matrix;
+using sycl::ext::oneapi::bfloat16;
+
+#define SG_SZ 32
+constexpr size_t nWGperDim = 2;
+
+template <typename T1, typename T2, size_t M, size_t K, size_t N>
+class KernelName;
+
+template <typename T, size_t NUM_ROWS, size_t NUM_COLS> struct big_matrix {
+public:
+  T *mat;
+
+  T *get_data() { return mat; }
+  void set_data(T *data) { mat = data; }
+  big_matrix(T *data) : mat(data) {}
+};
+
+template <typename T, size_t M, size_t N>
+void assert_ref(T *C, const float ref) {
+  for (size_t i = 0; i < M; i++)
+    for (size_t j = 0; j < N; j++) {
+      auto diff = C[i + j * M] - ref;
+      assert(std::fabs(static_cast<float>(diff)) <
+             std::numeric_limits<float>::epsilon());
+    }
+}
+
+template <typename T, typename T2, size_t M, size_t K, size_t N, typename F>
+void matrix_verify_lambda(queue q,
+                          big_matrix<T2, M * nWGperDim, N * nWGperDim> &C,
+                          nd_range<2> &r, const float ref, F &&lambda) {
+  {
+    buffer<T2, 2> bufC(C.get_data(), range<2>(N * nWGperDim, M * nWGperDim));
+
+    q.submit([&](handler &cgh) {
+      accessor<T2, 2, access::mode::read_write, target::device> accC(bufC, cgh);
+
+      cgh.parallel_for<KernelName<T, T2, M, K, N>>(
+          r, [accC, lambda](
+                 nd_item<2> spmd_item) [[sycl::reqd_sub_group_size(SG_SZ)]] {
+            const auto global_idx = spmd_item.get_global_id(0);
+            const auto global_idy = spmd_item.get_global_id(1);
+            const auto sg_startx = global_idx - spmd_item.get_local_id(0);
+            const auto sg_starty = global_idy - spmd_item.get_local_id(1);
+
+            auto sg = spmd_item.get_sub_group();
+
+            joint_matrix<sub_group, T, use::a, M, K, layout::row_major> sub_a;
+            joint_matrix<sub_group, T, use::b, K, N, layout::row_major> sub_b;
+            joint_matrix<sub_group, T2, use::accumulator, M, N> sub_c;
+
+            joint_matrix_fill(sg, sub_a, 3);
+            joint_matrix_fill(sg, sub_b, 1);
+            joint_matrix_fill(sg, sub_c, -80);
+
+            joint_matrix_apply(sg, sub_a, lambda);
+
+            sub_c = joint_matrix_mad(sg, sub_a, sub_b, sub_c);
+
+            joint_matrix_store(sg, sub_c,
+                               accC.get_pointer() +
+                                   (sg_startx * M) * (N * nWGperDim) +
+                                   sg_starty / SG_SZ * N,
+                               (N * nWGperDim), layout::row_major);
+          }); // parallel for
+    });
+  }
+  assert_ref<T2, M * nWGperDim, N * nWGperDim>(C.get_data(), ref);
+}
+
+static constexpr size_t MATRIX_M = 16 * nWGperDim;
+static constexpr size_t MATRIX_N = 16 * nWGperDim;
+
+int main() {
+
+  float D[MATRIX_M][MATRIX_N];
+  big_matrix<float, MATRIX_M, MATRIX_N> MD_f((float *)&D);
+
+  queue q;
+  auto computeCapability =
+      std::stof(q.get_device().get_info<sycl::info::device::backend_version>());
+  nd_range<2> r({nWGperDim, nWGperDim * SG_SZ}, {1, 1 * SG_SZ});
+
+  auto apply_add = [](auto &x) { x = x + 2; };
+
+  if (computeCapability >= 7.0) {
+    matrix_verify_lambda<half, float, 16, 16, 16>(q, MD_f, r, 0.0, apply_add);
+  }
+
+  if (computeCapability >= 7.2) {
+    int32_t D_i[MATRIX_M][MATRIX_N];
+    big_matrix<int32_t, MATRIX_M, MATRIX_N> MD_i((int32_t *)&D_i);
+    matrix_verify_lambda<uint8_t, int32_t, 16, 16, 16>(q, MD_i, r, 0,
+                                                       apply_add);
+    matrix_verify_lambda<int8_t, int32_t, 16, 16, 16>(q, MD_i, r, 0, apply_add);
+  }
+
+  if (computeCapability >= 8.0) {
+    matrix_verify_lambda<bfloat16, float, 16, 16, 16>(q, MD_f, r, 0.0,
+                                                      apply_add);
+
+    double D_d[MATRIX_M / 2][MATRIX_N / 2];
+    big_matrix<double, 8 * nWGperDim, 8 * nWGperDim> MD_d((double *)&D_d);
+
+    matrix_verify_lambda<double, double, 8, 4, 8>(q, MD_d, r, -60.0, apply_add);
+  }
+
+  return 0;
+}