Fix B matrix layout (#85)

* Use N major for B * Use N major for B coordinates * Update include/cute/atom/copy_traits_xe.hpp Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com> * Update include/cute/atom/copy_traits_xe.hpp Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com> * Update include/cute/atom/copy_traits_xe.hpp Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com> * Update include/cute/atom/copy_traits_xe.hpp Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com> * Fix A copy trait layout * Update include/cute/atom/copy_traits_xe.hpp Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com> --------- Co-authored-by: Mehdi Goli <mehdi.goli@codeplay.com>
codeplaysoftware · Jun 19, 2024 · ef0284f · ef0284f
1 parent c584a18
commit ef0284f
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Showing 4 changed files with 60 additions and 30 deletions.
diff --git a/include/cute/atom/copy_traits_xe.hpp b/include/cute/atom/copy_traits_xe.hpp
@@ -37,24 +37,55 @@
 
 namespace cute
 {
+
+template <class IntT>
+CUTE_HOST_DEVICE constexpr
+auto get_shape_WHD(cute::Stride<Int<1>, IntT, IntT> , cute::Shape<int,int,int> shape_MKL) {
+  return shape_MKL;
+}
+
+template <class IntT>
+CUTE_HOST_DEVICE constexpr
+auto get_shape_WHD(cute::Stride<IntT, Int<1>, IntT> , cute::Shape<int,int,int> shape_MKL) {
+  return Shape<int, int, int>(get<1>(shape_MKL), get<0>(shape_MKL), get<2>(shape_MKL));
+}
+
+template <class IntT, class TS, class SLayout>
+CUTE_HOST_DEVICE constexpr
+auto get_coordinates(cute::Stride<Int<1>, IntT, IntT> ,
+                     Tensor<ViewEngine<ArithmeticTupleIterator<TS>>, SLayout> const &src) {
+  auto [x, y, z] = src.data().coord_;
+  return make_coord(x, y, z);
+}
+
+template <class IntT, class TS, class SLayout>
+CUTE_HOST_DEVICE constexpr
+auto get_coordinates(cute::Stride<IntT, Int<1>, IntT> ,
+                     Tensor<ViewEngine<ArithmeticTupleIterator<TS>>, SLayout> const &src) {
+  auto [x, y, z] = src.data().coord_;
+  return make_coord(y, x, z);
+}
+
 template <class CopyOp, class GTensor>
 struct XE_2D_LD_Unpack
 {
   GTensor tensor;
 
   using Copy_Traits = Copy_Traits<CopyOp, GTensor>;
+
   template <class TS, class SLayout,
             class TD, class DLayout>
   CUTE_HOST_DEVICE friend constexpr void
   copy_unpack(Copy_Traits const &traits,
               Tensor<ViewEngine<ArithmeticTupleIterator<TS>>, SLayout> const &src,
               Tensor<TD, DLayout> &dst)
   {
-      static_assert(is_rmem<TD>::value);
-      int H = size<0>(traits.tensor);
-      int W = size<1>(traits.tensor) * sizeof(typename Copy_Traits::CopyInternalType);
-      auto [y, x, z] = src.data().coord_;
-      CopyOp::copy(traits.tensor.data() + z, W, H, W, intel::coord_t{x, y}, &*dst.data());
+    static_assert(is_rmem<TD>::value);
+    auto shape_whd = get_shape_WHD(traits.tensor.stride(), traits.tensor.shape());
+    int W = size<0>(shape_whd) * sizeof(typename Copy_Traits::CopyInternalType);
+    int H = size<1>(shape_whd);
+    auto [x, y, z] = get_coordinates(traits.tensor.stride(), src);
+    CopyOp::copy(traits.tensor.data() + z, W, H, W, intel::coord_t{x, y}, &*dst.data());
   }
 
   template <class GCoord, class GShape, class GStride>
@@ -105,15 +136,13 @@ struct Copy_Traits<XE_2D_U16x8x16x4x2_LD_N, GTensor>
      : XE_2D_LD_Unpack<XE_2D_U16x8x16x4x2_LD_N, GTensor>
 {
   // Logical thread id to thread idx
-  using ThrID = Layout<_16>;
+  using ThrID = Layout<_1>;
   // Map from (src-thr,src-val) to bit
-  using SrcLayout = Layout<Shape<_16, _64>, Stride<_0, _1>>;
+  using SrcLayout = Layout<Shape<_1, Shape<_1, _1>>>; // one coordinate
   // Map from (dst-thr,dst-val) to bit
-  using DstLayout =
-      Layout<Shape<_16, Shape<Shape<_8, _4>, Shape<_16, _2>>>,
-             Stride<_16, Stride<Stride<_512, _4096>, Stride<_1, _256>>>>;
+  using DstLayout = Layout<Shape<_1, Shape<_64, _1>>>;
   // Reference map from (thr,val) to bit
-  using RefLayout = DstLayout;
+  using RefLayout = SrcLayout;
   using CopyInternalType = ushort;
 };
 
@@ -188,14 +217,13 @@ struct Copy_Traits<XE_2D_U16x16x16x2x1_LD_N, GTensor>
      : XE_2D_LD_Unpack<XE_2D_U16x16x16x2x1_LD_N, GTensor>
 {
   // Logical thread id to thread idx
-  using ThrID = Layout<_16>;
+  using ThrID = Layout<_1>;
   // Map from (src-thr,src-val) to bit
-  using SrcLayout = Layout<Shape<_16, _64>, Stride<_0, _1>>;
+  using SrcLayout = Layout<Shape<_1, Shape<_1, _4>>>;   // expected 4 coordinates
   // Map from (dst-thr,dst-val) to bit
-  using DstLayout =
-      Layout<Shape<_16, Shape<_16, _32>>, Stride<_32, Stride<_512, _1>>>;
+  using DstLayout = Layout<Shape<_1, Shape<_32, _4>>>;
   // Reference map from (thr,val) to bit
-  using RefLayout = DstLayout;
+  using RefLayout = SrcLayout;
   // 32 bits register file
   using CopyInternalType = uint;
 };

diff --git a/include/cute/util/debug.hpp b/include/cute/util/debug.hpp
@@ -129,7 +129,9 @@ bool
 block(int bid)
 {
 #if defined(CUTLASS_ENABLE_SYCL)
-    return (syclcompat::get_nd_item<3>().get_group_linear_id()==bid);
+  using namespace syclcompat;
+  return (work_group_id::x() + work_group_id::y() * work_group_range::x() +
+          work_group_id::z() * work_group_range::y() * work_group_range::x() == bid);
 #elif defined(__CUDA_ARCH__)
   return blockIdx.x + blockIdx.y*gridDim.x + blockIdx.z*gridDim.x*gridDim.y == bid;
 #else
@@ -142,7 +144,9 @@ bool
 thread(int tid, int bid)
 {
 #if defined(CUTLASS_ENABLE_SYCL)
-    return (syclcompat::get_nd_item<3>().get_global_linear_id()==bid);
+  using namespace syclcompat;
+  return (local_id::x() + local_id::y() * local_range::x() +
+          local_id::z() * local_range::x() * local_range::y() == tid) && block(bid);
 #elif defined(__CUDA_ARCH__)
   return (threadIdx.x + threadIdx.y*blockDim.x + threadIdx.z*blockDim.x*blockDim.y == tid) && block(bid);
 #else

diff --git a/include/cutlass/gemm/collective/intel_pvc_mma.hpp b/include/cutlass/gemm/collective/intel_pvc_mma.hpp
@@ -149,7 +149,7 @@ struct CollectiveMma<
     auto [M,N,K,L] = problem_shape_MNKL;
 
     Tensor tensorA = make_tensor(args.ptr_A, make_layout(make_shape(M,K,L), args.dA));
-    Tensor tensorB = make_tensor(args.ptr_B, make_layout(make_shape(K,N,L), args.dB));
+    Tensor tensorB = make_tensor(args.ptr_B, make_layout(make_shape(N,K,L), args.dB));
 
     typename Params::XE_Copy_A copyA = make_xe_2d_copy<GmemTiledCopyA>(tensorA);
     typename Params::XE_Copy_B copyB = make_xe_2d_copy<GmemTiledCopyB>(tensorB);
@@ -187,14 +187,14 @@ struct CollectiveMma<
     static_assert(is_rmem<FrgTensorC>::value, "C tensor must be rmem resident.");
 
     // Tensor to hold input data
-    Tensor tAr = make_tensor<typename TiledMma::ValTypeA>(Shape<Int<get<0>(SubgroupTileShape{}) * FragsK>, Int<1>>{});
-    Tensor tBr = make_tensor<typename TiledMma::ValTypeB>(
-            Shape<Int<FragsK * get<1>(SubgroupTileShape{}) / FragsN>, Int<FragsN>>{});
+    Tensor tAr = make_tensor<typename TiledMma::ValTypeA>(Shape<Int<get<0>(SubgroupTileShape{}) * FragsK>, _1>{});
+    Tensor tBr = make_tensor<typename TiledMma::ValTypeB>(Shape<Int<get<1>(SubgroupTileShape{}) / 2>, Int<FragsN>>{});
 
     Tensor tAr_view = make_tensor(static_cast<decltype(tAr) &&>(tAr).data(),
                             Shape<Int<VecA>, Int<FragsM>, Int<FragsK>>{});
     Tensor tBr_view = make_tensor(static_cast<decltype(tBr) &&>(tBr).data(),
-                            Shape<Int<VecB>, Int<FragsK>, Int<FragsN>>{});
+                            Shape<Int<VecB>, Int<FragsN>, Int<FragsK>>{},
+                            Stride<_1, Int<get<1>(SubgroupTileShape{}) / 2>, Int<VecB>>{});
 
     // Instantiate the M MA object
     TiledMma tiled_mma;
@@ -206,11 +206,9 @@ struct CollectiveMma<
    {
      // Copy gmem to rmem for the first k_tile
      copy(mainloop.gmem_tiled_copy_a, gA(_,_,k), tAr);
-     copy(mainloop.gmem_tiled_copy_b, gB(_,k/2,_), tBr);
+     copy(mainloop.gmem_tiled_copy_b, gB(_,_,k/2), tBr);
 
-     for (int kl = 0; kl < FragsK; kl++) {
-       cute::gemm(tiled_mma, accum, tAr_view(_, _, kl), tBr_view(_, kl, _), src_accum);
-     }
+     cute::gemm(tiled_mma, accum, tAr_view, tBr_view, src_accum);
    }
   }
 };

diff --git a/include/cutlass/gemm/kernel/intel_pvc_gemm.hpp b/include/cutlass/gemm/kernel/intel_pvc_gemm.hpp
@@ -221,9 +221,9 @@ class GemmUniversal<
             make_stride(Int<FragsM>{} * get<0>(MmaAtomShape()),_1{}));
 
     Tensor tBi = params.mainloop.gmem_tiled_copy_b.get_pvc_tensor(
-            make_coord(0, n_coord, 0),
-            make_shape(K, Int<FragsN>{}, L),
-            make_stride(_1{}, get<1>(MmaAtomShape())));
+            make_coord(n_coord, 0, 0),
+            make_shape(Int<FragsN>{}, K / 2, L),
+            make_stride(get<1>(MmaAtomShape()), _1{}));
 
     // Compute tile residues for predication
     auto m_max_coord = M - get<0>(subgroup_shape) * m_coord;                             // M - SUB_M * m_coord