chsasank · February 6, 2024 13:17 · Feb 6, 2024 · Feb 6, 2024 · Feb 6, 2024
diff --git a/build.sh b/build.sh
@@ -1 +0,0 @@
-icpx -fsycl -std=c++17 joint-matrix.cpp -o joint-matrix -lsycl -lOpenCL

diff --git a/build.sh b/build.sh
@@ -0,0 +1 @@
+icpx -fsycl -std=c++17 joint-matrix.cpp -o joint-matrix -lsycl -lOpenCL
diff --git a/joint_matrix.cpp b/joint_matrix.cpp
@@ -0,0 +1,194 @@
+//==============================================================
+// Copyright © 2022 Intel Corporation
+//
+// SPDX-License-Identifier: MIT
+// =============================================================
+
+#include <iostream>
+#include <sycl/sycl.hpp>
+#include <chrono>
+
+// using joint_matrix = sycl::ext::oneapi::experimental::matrix;
+using use = sycl::ext::oneapi::experimental::matrix::use;
+using layout = sycl::ext::oneapi::experimental::matrix::layout;
+using bfloat16 = sycl::ext::oneapi::bfloat16;
+
+#define SG_SZ 8
+
+#define TM 8
+#define TN SG_SZ
+#define TK 16
+
+#define BF16_EPSILON 0.00781250
+
+template <typename T, size_t NUM_ROWS, size_t NUM_COLS> struct big_matrix {
+private:
+  T *mat;
+
+public:
+  T *get_data() { return mat; }
+  void set_data(T *data) { mat = data; }
+  big_matrix(T *data) : mat(data) {}
+};
+
+template <typename T1, typename T2, size_t M, size_t N, size_t K>
+void matrix_multiply(big_matrix<T1, M, N> &C, big_matrix<T2, M, K> &A,
+                     big_matrix<T2, K / 2, N * 2> &B) {
+  // kernel begin
+  size_t NDRangeM = M / TM;
+  size_t NDRangeN = N / TN;
+  sycl::buffer<bfloat16, 2> bufA(A.get_data(), sycl::range<2>(M, K));
+  sycl::buffer<bfloat16, 2> bufB(B.get_data(), sycl::range<2>(K, N));
+  sycl::buffer<float, 2> bufC((float *)C.get_data(), sycl::range<2>(M, N));
+
+  sycl::queue q;
+  q.submit([&](sycl::handler &cgh) {
+     sycl::accessor accC(bufC, cgh, sycl::read_write, sycl::no_init);
+     sycl::accessor accA(bufA, cgh, sycl::read_only);
+     sycl::accessor accB(bufB, cgh, sycl::read_only);
+
+     cgh.parallel_for(
+         sycl::nd_range<2>({NDRangeM, NDRangeN * SG_SZ}, {1, 1 * SG_SZ}),
+         [=](sycl::nd_item<2> spmd_item) [[intel::reqd_sub_group_size(SG_SZ)]]
+
+         {
+           // The joint matrix API has to be accessed by all the workitems in a
+           // subgroup these functions will be called once by the subgroup no
+           // code divergence between the workitems
+           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);
+
+           sycl::sub_group sg = spmd_item.get_sub_group();
+           sycl::ext::oneapi::experimental::matrix::joint_matrix<
+               sycl::sub_group, bfloat16, use::a, TM, TK, layout::row_major>
+               sub_a;
+           // For B, we assume B has been already VNNIed.
+           sycl::ext::oneapi::experimental::matrix::joint_matrix<
+               sycl::sub_group, bfloat16, use::b, TK, TN,
+               sycl::ext::intel::experimental::matrix::layout::packed>
+               sub_b;
+           sycl::ext::oneapi::experimental::matrix::joint_matrix<
+               sycl::sub_group, float, use::accumulator, TM, TN>
+               sub_c;
+
+           joint_matrix_load(sg, sub_c,
+                             accC.get_pointer() + (sg_startx * TM) * N +
+                                 sg_starty / SG_SZ * TN,
+                             N, layout::row_major);
+           for (int k = 0; k < K / TK; k += 1) { //
+             joint_matrix_load(
+                 sg, sub_a, accA.get_pointer() + (sg_startx * TM) * K + k * TK,
+                 K);
+             joint_matrix_load(sg, sub_b,
+                               accB.get_pointer() + (k * TK / 2) * (N * 2) +
+                                   sg_starty / SG_SZ * TN * 2,
+                               N * 2);
+             sub_c = joint_matrix_mad(sg, sub_a, sub_b, sub_c);
+           }
+           joint_matrix_store(sg, sub_c,
+                              accC.get_pointer() + (sg_startx * TM) * N +
+                                  sg_starty / SG_SZ * TN,
+                              N, layout::row_major);
+         }); // parallel for
+   }).wait();
+  // kernel end
+}
+
+static constexpr size_t MATRIX_M = TM * 128 * 1;
+static constexpr size_t MATRIX_N = TN * 128 * 1;
+static constexpr size_t MATRIX_K = TK * 64 * 1;
+bfloat16 A[MATRIX_M][MATRIX_K];
+bfloat16 B[MATRIX_K / 2][MATRIX_N * 2];
+unsigned short Aref[MATRIX_M][MATRIX_K];
+unsigned short Bref[MATRIX_K / 2][MATRIX_N * 2];
+float C[MATRIX_M][MATRIX_N];
+float D[MATRIX_M][MATRIX_N];
+
+float make_fp32(short x) {
+  unsigned int y = x;
+  y = y << 16;
+  float *res = reinterpret_cast<float *>(&y);
+  return *res;
+}
+
+unsigned short make_bf16(float x) {
+  int *res = reinterpret_cast<int *>(&x);
+  *res = *res >> 16;
+  return (unsigned short)*res;
+}
+
+void matrix_multiply_ref(int *A_mem, int *B_mem, int *C_mem, int M, int N,
+                         int K) {
+  for (int m = 0; m < M; m++)
+    for (int n = 0; n < N; n++) {
+      for (int k = 0; k < K; k++) {
+        short *va = (short *)(A_mem + m * K + k);
+        short *vb = (short *)(B_mem + k * N + n);
+        float acc = *((float *)(C_mem + m * N + n));
+        for (int i = 0; i < 2; i++) {
+          acc += (make_fp32(va[i]) * make_fp32(vb[i]));
+        }
+        *((float *)(C_mem + m * N + n)) = acc;
+      }
+    }
+}
+
+int main() {
+  for (int i = 0; i < MATRIX_M; i++) {
+    for (int j = 0; j < MATRIX_K; j++) {
+      // bfloat16 is created using unsigned short since conversion from float to
+      // bfloat16 is not supported on the host side yet
+      A[i][j] = bfloat16(1.0f * (i + j));
+      Aref[i][j] = make_bf16(1.0f * (i + j));
+    }
+  }
+  for (int i = 0; i < MATRIX_K / 2; i++) {
+    for (int j = 0; j < MATRIX_N * 2; j++) {
+      B[i][j] = bfloat16(2.0f * i + 3.0f * j);
+      Bref[i][j] = make_bf16(2.0f * i + 3.0f * j);
+    }
+  }
+  for (int i = 0; i < MATRIX_M; i++) {
+    for (int j = 0; j < MATRIX_N; j++) {
+      C[i][j] = 1.0;
+      D[i][j] = 1.0;
+    }
+  }
+
+  big_matrix<float, MATRIX_M, MATRIX_N> MC((float *)&C);
+  big_matrix<float, MATRIX_M, MATRIX_N> MD((float *)&D);
+  big_matrix<bfloat16, MATRIX_M, MATRIX_K> MA((bfloat16 *)&A);
+  big_matrix<bfloat16, MATRIX_K / 2, MATRIX_N * 2> MB((bfloat16 *)&B);
+
+  int num_trails = 20;
+  auto start = std::chrono::steady_clock::now();
+  for (int i = 0; i < num_trails; i++){
+    matrix_multiply(MC, MA, MB);
+  }
+  auto end = std::chrono::steady_clock::now();
+  auto total_time = std::chrono::duration<double>(end - start).count();
+  std::cout << "time for gpu gemm " << MATRIX_M << " " << MATRIX_N << " " << MATRIX_K <<
+     " for " << num_trails << " trails: " << total_time << std::endl;
+  auto avg = total_time / num_trails;
+  auto op_count = double(MATRIX_M) * double(MATRIX_N) * double(MATRIX_K) * 2;
+  auto flops = op_count / avg;
+  std::cout << "estimated flops: " << flops << std::endl;
+
+  matrix_multiply_ref((int32_t *)Aref, (int32_t *)Bref, (int32_t *)D, MATRIX_M,
+                      MATRIX_N, MATRIX_K / 2);
+
+  bool res = true;
+  for (int i = 0; i < MATRIX_M; i++) {
+    for (int j = 0; j < MATRIX_N; j++) {
+      C[i][j] = C[i][j] / num_trails;
+      auto diff_r = 2 * fabs(C[i][j] - D[i][j]) / (fabs(C[i][j]) + fabs(D[i][j]));
+      if (diff_r > 1e-2){
+        res = false;
+      }
+    }
+  }
+  std::cout << (res ? "passed" : "failed") << std::endl;
+  return !res;
+}
Original file line number	Diff line number	Diff line change
		@@ -1 +0,0 @@
		icpx -fsycl -std=c++17 joint-matrix.cpp -o joint-matrix -lsycl -lOpenCL
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		icpx -fsycl -std=c++17 joint-matrix.cpp -o joint-matrix -lsycl -lOpenCL