Add support for custom packed Lhs/Rhs blocks in tensor contractions

1 files changed, 163 insertions, 39 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
index 6ca881f27..6a213096d 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
@@ -105,7 +105,9 @@ struct traits<TensorContractionOp<Dimensions, LhsXprType, RhsXprType, OutputKern
   static const int NumDimensions = traits<LhsXprType>::NumDimensions + traits<RhsXprType>::NumDimensions - 2 * array_size<Dimensions>::value;
   static const int Layout = traits<LhsXprType>::Layout;
   typedef typename conditional<Pointer_type_promotion<typename LhsXprType::Scalar, Scalar>::val,
-  typename traits<LhsXprType>::PointerType, typename traits<RhsXprType>::PointerType>::type PointerType;
+                               typename traits<LhsXprType>::PointerType,
+                               typename traits<RhsXprType>::PointerType>::type
+      PointerType;
 
   enum {
     Flags = 0
@@ -136,6 +138,80 @@ struct traits<TensorEvaluator<const TensorContractionOp<Indices_, LeftArgType_,
   static const int NumDimensions = traits<LeftArgType_>::NumDimensions + traits<RightArgType_>::NumDimensions - 2 * array_size<Indices_>::value;
 };
 
+// Helper class to allocate and deallocate temporary memory for packed buffers.
+template <typename LhsScalar, typename RhsScalar>
+struct TensorContractionBlockMemAllocator {
+  typedef void* BlockMemHandle;
+
+  template <typename Device>
+  EIGEN_DEVICE_FUNC static BlockMemHandle allocate(Device& d, const Index bm,
+                                                   const Index bk,
+                                                   const Index bn,
+                                                   LhsScalar** lhs_block,
+                                                   RhsScalar** rhs_block) {
+    eigen_assert(lhs_block);
+    eigen_assert(rhs_block);
+    BlockSizes sz = ComputeLhsRhsBlockSizes(bm, bk, bn);
+    char* block_mem = static_cast<char*>(d.allocate(sz.lhs_size + sz.rhs_size));
+    eigen_assert(block_mem);
+    *lhs_block = reinterpret_cast<LhsScalar*>(block_mem);
+    *rhs_block = reinterpret_cast<RhsScalar*>(block_mem + sz.lhs_size);
+    return block_mem;
+  }
+
+  template <typename Device>
+  EIGEN_DEVICE_FUNC static BlockMemHandle allocateSlices(
+      Device& d, const Index bm, const Index bk, const Index bn,
+      const Index num_lhs, const Index num_rhs, const Index num_slices,
+      std::vector<LhsScalar*>* lhs_blocks,
+      std::vector<RhsScalar*>* rhs_blocks) {
+    eigen_assert(num_slices > 0);
+    eigen_assert(num_lhs >= 0 && num_rhs >= 0)
+    eigen_assert(num_lhs == 0 || lhs_blocks);
+    eigen_assert(num_rhs == 0 || rhs_blocks);
+    BlockSizes sz = ComputeLhsRhsBlockSizes(bm, bk, bn);
+    void* block_mem = d.allocate(
+        (num_lhs * sz.lhs_size + num_rhs * sz.rhs_size) * num_slices);
+    eigen_assert(block_mem);
+    char* mem = static_cast<char*>(block_mem);
+
+    for (Index x = 0; x < num_slices; x++) {
+      if (num_lhs > 0) lhs_blocks[x].resize(num_lhs);
+      for (Index m = 0; m < num_lhs; m++) {
+        lhs_blocks[x][m] = reinterpret_cast<LhsScalar*>(mem);
+        mem += sz.lhs_size;
+      }
+      if (num_rhs > 0) rhs_blocks[x].resize(num_rhs);
+      for (Index n = 0; n < num_rhs; n++) {
+        rhs_blocks[x][n] = reinterpret_cast<RhsScalar*>(mem);
+        mem += sz.rhs_size;
+      }
+    }
+
+    return block_mem;
+  }
+
+  template <typename Device>
+  EIGEN_DEVICE_FUNC static void deallocate(Device& d, BlockMemHandle handle) {
+    d.deallocate(handle);
+  }
+
+ private:
+  struct BlockSizes {
+    Index lhs_size;
+    Index rhs_size;
+  };
+  EIGEN_DEVICE_FUNC static BlockSizes ComputeLhsRhsBlockSizes(const Index bm,
+                                                              const Index bk,
+                                                              const Index bn) {
+    Index align = numext::maxi(EIGEN_MAX_ALIGN_BYTES, 1);
+    BlockSizes sz;
+    sz.lhs_size = divup<Index>(bm * bk * sizeof(LhsScalar), align) * align;
+    sz.rhs_size = divup<Index>(bn * bk * sizeof(RhsScalar), align) * align;
+    return sz;
+  }
+};
+
 // WARNING: In this code we assume that Lhs and Rhs tensor expressions are in
 // ColMajor storage order. This property is guaranteed by the
 // TensorContractionOp evaluator. TensorContractionKernel specifies how we pack
@@ -164,16 +240,28 @@ struct traits<TensorEvaluator<const TensorContractionOp<Indices_, LeftArgType_,
 //   TensorContractionInputMapper, or some specialization of it based on the
 //   type of tensor expression (e.g. TensorImagePatchOp has optimized input
 //   mapper).
-template<typename ResScalar, typename LhsScalar, typename RhsScalar,
+template <typename ResScalar, typename LhsScalar, typename RhsScalar,
     typename StorageIndex, typename OutputMapper, typename LhsMapper,
     typename RhsMapper>
 struct TensorContractionKernel {
+  TensorContractionKernel(StorageIndex m, StorageIndex k, StorageIndex n,
+                          StorageIndex bm, StorageIndex bk, StorageIndex bn)
+      : m(m), k(k), n(n), bm(bm), bk(bk), bn(bn) {}
+
+  // Pack blocks of Lhs and Rhs into contiguous blocks in memory.
+  typedef LhsScalar* LhsBlock;
+  typedef RhsScalar* RhsBlock;
+
+  // Packed Lhs/Rhs block memory allocator.
+  typedef TensorContractionBlockMemAllocator<LhsScalar, RhsScalar>
+      BlockMemAllocator;
+  typedef typename BlockMemAllocator::BlockMemHandle BlockMemHandle;
+
   typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
 
-  typedef internal::gemm_pack_lhs<LhsScalar, StorageIndex,
-                                  typename LhsMapper::SubMapper,
-                                  Traits::mr, Traits::LhsProgress,
-                                  typename Traits::LhsPacket4Packing, ColMajor>
+  typedef internal::gemm_pack_lhs<
+      LhsScalar, StorageIndex, typename LhsMapper::SubMapper, Traits::mr,
+      Traits::LhsProgress, typename Traits::LhsPacket4Packing, ColMajor>
       LhsPacker;
 
   typedef internal::gemm_pack_rhs<RhsScalar, StorageIndex,
@@ -186,29 +274,61 @@ struct TensorContractionKernel {
       /*ConjugateLhs*/ false, /*ConjugateRhs*/ false>
       GebpKernel;
 
-  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE
-  static void packLhs(LhsScalar* lhsBlock,
-                      const typename LhsMapper::SubMapper& data_mapper,
-                      const StorageIndex depth, const StorageIndex rows) {
-    LhsPacker()(lhsBlock, data_mapper, depth, rows, /*stride*/ 0, /*offset*/ 0);
+  template <typename Device>
+  EIGEN_DEVICE_FUNC BlockMemHandle allocate(Device& d, LhsBlock* lhs_block,
+                                            RhsBlock* rhs_block) {
+    return BlockMemAllocator::allocate(d, bm, bk, bn, lhs_block, rhs_block);
+  }
+
+  template <typename Device>
+  EIGEN_DEVICE_FUNC BlockMemHandle allocateSlices(
+      Device& d, const StorageIndex num_lhs, const StorageIndex num_rhs,
+      const StorageIndex num_slices, std::vector<LhsBlock>* lhs_blocks,
+      std::vector<RhsBlock>* rhs_blocks) {
+    return BlockMemAllocator::allocateSlices(
+        d, bm, bk, bn, num_lhs, num_rhs, num_slices, lhs_blocks, rhs_blocks);
+  }
+
+  template <typename Device>
+  EIGEN_DEVICE_FUNC static void deallocate(Device& d, BlockMemHandle handle) {
+    BlockMemAllocator::deallocate(d, handle);
   }
 
-  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE
-  static void packRhs(RhsScalar* rhsBlock,
-                      const typename RhsMapper::SubMapper& data_mapper,
-                      const StorageIndex depth, const StorageIndex cols) {
-    RhsPacker()(rhsBlock, data_mapper, depth, cols);
+  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void packLhs(
+      LhsBlock* lhsBlock, const typename LhsMapper::SubMapper& data_mapper,
+      const StorageIndex depth, const StorageIndex rows) {
+    LhsPacker()(*lhsBlock, data_mapper, depth, rows, /*stride*/ 0,
+        /*offset*/ 0);
   }
 
-  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE
-  static void invoke(const OutputMapper& output_mapper,
-                     const LhsScalar* lhsBlock, const RhsScalar* rhsBlock,
-                     const StorageIndex rows, const StorageIndex depth,
-                     const StorageIndex cols, const ResScalar alpha) {
+  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void packRhs(
+      RhsBlock* rhsBlock, const typename RhsMapper::SubMapper& data_mapper,
+      const StorageIndex depth, const StorageIndex cols) {
+    RhsPacker()(*rhsBlock, data_mapper, depth, cols);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void invoke(
+      const OutputMapper& output_mapper, const LhsBlock& lhsBlock,
+      const RhsBlock& rhsBlock, const StorageIndex rows,
+      const StorageIndex depth, const StorageIndex cols,
+      const ResScalar alpha) {
+    static const int kComputeStrideFromBlockDimensions = -1;
     GebpKernel()(output_mapper, lhsBlock, rhsBlock, rows, depth, cols, alpha,
-        /*strideA*/ -1, /*strideB*/ -1,
+        /*strideA*/ kComputeStrideFromBlockDimensions,
+        /*strideB*/ kComputeStrideFromBlockDimensions,
         /*offsetA*/ 0, /*offsetB*/ 0);
   }
+
+ private:
+  // These are dimensions of the original Tensors, and selected block sizes. The
+  // actual block sizes passed to all function above might be smaller because of
+  // the partial blocks at the end.
+  const StorageIndex m;
+  const StorageIndex k;
+  const StorageIndex n;
+  const StorageIndex bm;
+  const StorageIndex bk;
+  const StorageIndex bn;
 };
 
 }  // end namespace internal
@@ -257,7 +377,7 @@ class TensorContractionOp : public TensorBase<TensorContractionOp<Indices, LhsXp
   public:
   typedef typename Eigen::internal::traits<TensorContractionOp>::Scalar Scalar;
   typedef typename internal::gebp_traits<typename LhsXprType::CoeffReturnType,
-                                                   typename RhsXprType::CoeffReturnType>::ResScalar CoeffReturnType;
+                                         typename RhsXprType::CoeffReturnType>::ResScalar CoeffReturnType;
   typedef typename Eigen::internal::nested<TensorContractionOp>::type Nested;
   typedef typename Eigen::internal::traits<TensorContractionOp>::StorageKind StorageKind;
   typedef typename Eigen::internal::traits<TensorContractionOp>::Index Index;
@@ -340,10 +460,10 @@ struct TensorContractionEvaluatorBase
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   TensorContractionEvaluatorBase(const XprType& op, const Device& device)
-    : m_leftImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
+      : m_leftImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
                           op.lhsExpression(), op.rhsExpression()), device),
-    m_rightImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
-                          op.rhsExpression(), op.lhsExpression()), device),
+        m_rightImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
+                           op.rhsExpression(), op.lhsExpression()), device),
         m_device(device),
         m_output_kernel(op.outputKernel()),
         m_result(NULL) {
@@ -737,11 +857,18 @@ struct TensorContractionEvaluatorBase
     const Index kc = blocking.kc();
     const Index mc = numext::mini(m, blocking.mc());
     const Index nc = numext::mini(n, blocking.nc());
-    const Index sizeA = mc * kc;
-    const Index sizeB = kc * nc;
 
-    LhsScalar* blockA = static_cast<LhsScalar *>(this->m_device.allocate(sizeA * sizeof(LhsScalar)));
-    RhsScalar* blockB = static_cast<RhsScalar *>(this->m_device.allocate(sizeB * sizeof(RhsScalar)));
+    typedef typename TensorContractionKernel::LhsBlock LhsBlock;
+    typedef typename TensorContractionKernel::RhsBlock RhsBlock;
+
+    LhsBlock blockA;
+    RhsBlock blockB;
+
+    TensorContractionKernel kernel(m, k_slice, n, mc, kc, nc);
+
+    typedef typename TensorContractionKernel::BlockMemHandle BlockMemHandle;
+    const BlockMemHandle packed_mem =
+        kernel.allocate(this->m_device, &blockA, &blockB);
 
     for(Index i2=0; i2<m; i2+=mc)
     {
@@ -749,22 +876,20 @@ struct TensorContractionEvaluatorBase
       for (Index k2 = k_start; k2 < k_end; k2 += kc) {
         // make sure we don't overshoot right edge of left matrix, then pack vertical panel
         const Index actual_kc = numext::mini(k2 + kc, k_end) - k2;
-        TensorContractionKernel::packLhs(blockA, lhs.getSubMapper(i2, k2),
-                                         actual_kc, actual_mc);
+        kernel.packLhs(&blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
 
         // series of horizontal blocks
         for (Index j2 = 0; j2 < n; j2 += nc) {
           // make sure we don't overshoot right edge of right matrix, then pack block
           const Index actual_nc = numext::mini(j2 + nc, n) - j2;
-          TensorContractionKernel::packRhs(blockB, rhs.getSubMapper(k2, j2),
-                                           actual_kc, actual_nc);
+          kernel.packRhs(&blockB, rhs.getSubMapper(k2, j2), actual_kc,
+                         actual_nc);
 
           // call gebp (matrix kernel)
           // The parameters here are copied from Eigen's GEMM implementation
           const OutputMapper output_mapper = output.getSubMapper(i2, j2);
-          TensorContractionKernel::invoke(output_mapper, blockA, blockB,
-                                          actual_mc, actual_kc, actual_nc,
-                                          Scalar(1));
+          kernel.invoke(output_mapper, blockA, blockB, actual_mc, actual_kc,
+                        actual_nc, Scalar(1));
 
           // We are done with this [i2, j2] output block.
           if (use_output_kernel && k2 + kc >= k_end) {
@@ -775,8 +900,7 @@ struct TensorContractionEvaluatorBase
       }
     }
 
-    this->m_device.deallocate(blockA);
-    this->m_device.deallocate(blockB);
+    kernel.deallocate(this->m_device, packed_mem);
   }
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {