Transpose optimization for AlphaFold2 (#45230)

* first commit

* fix bugs according to ci

* add some changes

* change file name into function.cu.h

* remove const_cast

paddle/fluid/operators/fused/fmha_ref.h

@@ -21,7 +21,7 @@ limitations under the License. */
 #include "paddle/phi/kernels/funcs/elementwise_base.h"
 #include "paddle/phi/kernels/funcs/elementwise_functor.h"
 #include "paddle/phi/kernels/funcs/functors.h"
-#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
+#include "paddle/phi/kernels/funcs/transpose_function.cu.h"
 #include "paddle/phi/kernels/gpudnn/softmax_gpudnn.h"
 
 namespace paddle {

paddle/fluid/operators/fused/fused_gate_attention.h

@@ -18,7 +18,7 @@ limitations under the License. */
 #include "paddle/phi/kernels/funcs/elementwise_base.h"
 #include "paddle/phi/kernels/funcs/elementwise_functor.h"
 #include "paddle/phi/kernels/funcs/reduce_function.h"
-#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
+#include "paddle/phi/kernels/funcs/transpose_function.cu.h"
 #include "paddle/phi/kernels/gpudnn/softmax_gpudnn.h"
 
 namespace paddle {

paddle/phi/kernels/funcs/dims_simplifier.h

@@ -243,5 +243,106 @@ struct BroadcastDimsSimplifier {
   }
 };
 
+// Simplify the input dims and permute dims if possible.
+struct DimsSimplifier {
+ public:
+  explicit DimsSimplifier(const int rank,
+                          const int64_t numel,
+                          const std::vector<int32_t> &perm,
+                          const std::vector<int64_t> &dims)
+      : perm_(rank), src_dims_(rank), count_(numel) {
+    SimplifyPermAndDims(rank, dims, perm);
+    perm_.resize(rank_);
+    src_dims_.resize(rank_);
+    dst_dims_.resize(rank_);
+    if (!is_seq_perm_) {
+      for (auto i = 0; i < rank_; ++i) {
+        dst_dims_[i] = src_dims_[perm_[i]];
+      }
+    } else {
+      dst_dims_[0] = numel;
+      src_dims_[0] = numel;
+    }
+  }
+
+  ~DimsSimplifier() = default;
+
+  const int &GetRank() const { return rank_; }
+  const int64_t &GetCount() const { return count_; }
+  const std::vector<int> &GetPerm() const { return perm_; }
+  const std::vector<int64_t> &GetSrcDims() const { return src_dims_; }
+  const std::vector<int64_t> &GetDstDims() const { return dst_dims_; }
+
+ private:
+  int rank_{1};
+  int64_t count_{0};
+  bool is_seq_perm_{true};
+  std::vector<int> perm_;
+  std::vector<int64_t> src_dims_;
+  std::vector<int64_t> dst_dims_;
+
+  void SimplifyPermAndDims(const int rank,
+                           const std::vector<int64_t> &in_dims,
+                           const std::vector<int32_t> &perm) {
+    int start_perm_idx = 0;
+    int valid_dim_idx = 0;
+    int valid_map[phi::DDim::kMaxRank];
+    int64_t combined_dims[phi::DDim::kMaxRank];
+
+    // Merge consecutive dims to the fist one dim and
+    // leave original dim to be 1. Example below :
+    // perm: [2, 3, 0, 1], origin_dims : [4, 8, 2, 5]
+    // new_dims: [4, 8, 2, 5] -> [32, 1, 10, 1]
+    while (start_perm_idx < rank) {
+      const int start_dim_idx = perm[start_perm_idx];
+      combined_dims[start_dim_idx] = in_dims[start_dim_idx];
+      int end_perm_idx = start_perm_idx + 1;
+
+      while (end_perm_idx < rank &&
+             perm[end_perm_idx] == perm[end_perm_idx - 1] + 1) {
+        const int end_dim_idx = perm[end_perm_idx];
+        combined_dims[start_dim_idx] *= in_dims[end_dim_idx];
+        combined_dims[end_dim_idx] = 1;
+        end_perm_idx += 1;
+      }
+      start_perm_idx = end_perm_idx;
+    }
+
+    // Reorder combined dims and marked useless dim as -1.
+    // for example, if combined dims is [32, 1, 10, 1],
+    // valid_map is [0, -1, 1, -1] and generate simplified
+    // dims as [32, 10]
+    for (auto i = 0; i < rank; ++i) {
+      const int dim_val = combined_dims[i];
+      if (dim_val == 1) {
+        valid_map[i] = -1;
+      } else {
+        valid_map[i] = valid_dim_idx;
+        src_dims_[valid_dim_idx] = dim_val;
+        valid_dim_idx += 1;
+      }
+    }
+
+    if (valid_dim_idx == 0) {
+      src_dims_[0] = 1;
+      perm_[0] = 0;
+      return;
+    }
+
+    // Acquire simplified perm with help of combined dims
+    // and original perm, finally simplified perm is [1, 0]
+    int perm_idx = 0;
+    for (auto i = 0; i < rank; ++i) {
+      const int mapped = valid_map[perm[i]];
+      if (mapped >= 0) {
+        perm_[perm_idx] = mapped;
+        is_seq_perm_ &= (mapped == perm_idx);
+        perm_idx += 1;
+      }
+    }
+    rank_ = is_seq_perm_ ? 1 : valid_dim_idx;
+  }
+};
+
 }  // namespace funcs
 }  // namespace phi

paddle/phi/kernels/funcs/transpose_functor.h

@@ -27,161 +27,115 @@ enum { kTransposeMKLDNNFP32 = 1, kTransposeMKLDNNINT8 = 2 };
 
 enum PermuteType {
   kCopy = 1,
-  kTranspose = 2,
-  kVecPermute = 3,
-  kGeneralPermute = 4
+  kSwapTranspose = 2,
+  kGeneralTranspose = 3,
+  kVecPermute = 4,
+  kGeneralPermute = 5
 };
 
 constexpr int kBlockRows = 16;
 constexpr int kTileSize = 32;
+constexpr int kShareCol = (kTileSize + 1);
+
+#define GETTILESIZE(LEN_, ALIGN_) \
+  ((LEN_ + (ALIGN_ - 1)) & ~(ALIGN_ - 1)) / ALIGN_
 
-// Simplify the input dims and permute dims if possible.
 template <typename T>
-class TranposeTypeClassifier {
+struct PermTypeClassifier {
  public:
-  TranposeTypeClassifier(const int sm_count,
-                         const size_t rank,
-                         const int64_t numel,
-                         const std::vector<int32_t>& perm,
-                         const std::vector<int64_t>& dims,
-                         const T* src,
-                         T* dst)
-      : perm_(rank), src_dims(rank) {
-    SimplifyPermAndDims(rank, dims, perm);
-    if (rank_ > 1) {
-      vec_size_ = GetPermVecSize(sm_count, src, dst);
-    }
-    perm_.resize(rank_);
-    src_dims.resize(rank_);
-    dst_dims.resize(rank_);
-
-    for (auto i = 0; i < rank_; ++i) {
-      dst_dims[i] = src_dims[perm_[i]];
-    }
-  }
-
-  int GetRank() const { return rank_; }
-  int GetVecSize() const { return vec_size_; }
-  PermuteType GetPermType() const { return type_; }
-
-  std::vector<int> GetPerm() const { return perm_; }
-  std::vector<int64_t> GetSrcDims() const { return src_dims; }
-  std::vector<int64_t> GetDstDims() const { return dst_dims; }
-
- private:
-  int rank_{1};
-  int vec_size_{1};
-  std::vector<int> perm_;
-  std::vector<int64_t> src_dims;
-  std::vector<int64_t> dst_dims;
-  PermuteType type_{kCopy};
-
-  void SimplifyPermAndDims(const size_t rank,
-                           const std::vector<int64_t>& in_dims,
-                           const std::vector<int32_t>& perm) {
-    int64_t combined_dims[phi::DDim::kMaxRank];
-    int valid_map[phi::DDim::kMaxRank];
-
-    // Merge consecutive dims to the fist one dim and
-    // leave original dim to be 1. Example below :
-    // perm: [2, 3, 0, 1], origin_dims : [4, 8, 2, 5]
-    // new_dims: [4, 8, 2, 5] -> [32, 1, 10, 1]
-    int start_perm_idx = 0;
-    while (start_perm_idx < rank) {
-      const int start_dim_idx = perm[start_perm_idx];
-      combined_dims[start_dim_idx] = in_dims[start_dim_idx];
-      int end_perm_idx = start_perm_idx + 1;
-
-      while (end_perm_idx < rank &&
-             perm[end_perm_idx] == perm[end_perm_idx - 1] + 1) {
-        const int end_dim_idx = perm[end_perm_idx];
-        combined_dims[start_dim_idx] *= in_dims[end_dim_idx];
-        combined_dims[end_dim_idx] = 1;
-        end_perm_idx += 1;
+  explicit PermTypeClassifier(const int sm_count,
+                              const int rank,
+                              const std::vector<int32_t>& perm,
+                              const std::vector<int64_t>& dims,
+                              const T* src,
+                              T* dst) {
+    if (rank == 1) {
+      type_ = PermuteType::kCopy;
+    } else {
+      constexpr int64_t dim_limitation = 65536;
+      const int dst_vec_size = phi::GetVectorizedSize<T>(dst);
+
+      // While the last dim is fixed, there is chance for vectorized IO.
+      const int last_idx = rank - 1;
+      if (perm[last_idx] == last_idx) {
+        type_ = PermuteType::kVecPermute;
+        vec_size_ = GetDimVecSize(dst_vec_size, dims[last_idx], src, false);
+        return;
       }
-      start_perm_idx = end_perm_idx;
-    }
 
-    // Reorder combined dims and marked useless dim as -1.
-    // for example, if combined dims is [32, 1, 10, 1],
-    // valid_map is [0, -1, 1, -1] and generate simplified
-    // dims as [32, 10]
-    int valid_dim_idx = 0;
-    bool sequential_flag = false;
-    for (auto i = 0; i < rank; ++i) {
-      const int src_dim = combined_dims[i];
-      if (src_dim == 1) {
-        valid_map[i] = -1;
-      } else {
-        sequential_flag = true;
-        valid_map[i] = valid_dim_idx;
-        src_dims[valid_dim_idx] = src_dim;
-        valid_dim_idx += 1;
+      // Permute at last 2 dims, namely transpose.
+      if ((rank == 2 && perm[1] == 0 && perm[0] == 1) ||
+          (rank == 3 && perm[2] == 1 && perm[1] == 2)) {
+        int64_t channel = rank == 2 ? 1 : dims[0];
+        // Currently, transpose kernel cannot cover the case that channel
+        // dimension is more than 65536 which is the limitation of dim3 setting.
+        // This special case will be covered by extended transpose kernel later.
+        if (channel < dim_limitation) {
+          type_ = PermuteType::kGeneralTranspose;
+          num_rows_tile_ = GETTILESIZE(dims[rank - 2], kTileSize);
+          int dim_vec_size = GetDimVecSize(dst_vec_size, dims[last_idx], src);
+          int tile_size =
+              channel * num_rows_tile_ * GETTILESIZE(dims[last_idx], kTileSize);
+          vec_size_ = tile_size < sm_count ? 1 : dim_vec_size;
+        } else {
+          type_ = PermuteType::kGeneralPermute;
+        }
+        return;
       }
-    }
 
-    if (valid_dim_idx == 0) {
-      src_dims[0] = 1;
-      perm_[0] = 0;
-      return;
-    } else if (valid_dim_idx == 1) {
-      type_ = PermuteType::kCopy;
-    }
-
-    // Acquire simplified perm with help of combined dims
-    // and original perm, finally simplified perm is [1, 0]
-    int perm_idx = 0;
-    for (auto i = 0; i < rank; ++i) {
-      const int mapped = valid_map[perm[i]];
-      if (mapped >= 0) {
-        perm_[perm_idx] = mapped;
-        perm_idx += 1;
+      // Permute at first dim and third dim.
+      if (rank == 3 && perm[2] == 0 && perm[1] == 1) {
+        // Currently, transpose kernel cannot cover the case that channel
+        // dimension is more than 65536 which is the limitation of dim3 setting.
+        // This special case will be covered by extended transpose kernel later.
+        if (dims[1] < dim_limitation) {
+          type_ = PermuteType::kSwapTranspose;
+          num_rows_tile_ = GETTILESIZE(dims[0], kTileSize);
+
+          int dim_vec_size = GetDimVecSize(dst_vec_size, dims[last_idx], src);
+          int tile_size =
+              dims[1] * num_rows_tile_ * GETTILESIZE(dims[2], kTileSize);
+          vec_size_ = tile_size < sm_count ? 1 : dim_vec_size;
+        } else {
+          type_ = PermuteType::kGeneralPermute;
+        }
+        return;
       }
+      vec_size_ = dst_vec_size;
     }
-    rank_ = valid_dim_idx;
   }
 
-  int GetPermVecSize(const int sm_count, const T* src, T* dst) {
-    // For gerneal_permute kernel, there is good chance for
-    // vectorized write.
-    type_ = PermuteType::kGeneralPermute;
-    int vec_size = phi::GetVectorizedSize<T>(dst);
-
-    // While the last dim is fixed, there is good chance for
-    // both vectorized read and write.
-    if (perm_[rank_ - 1] == rank_ - 1) {
-      int tmp_size = std::min(vec_size, phi::GetVectorizedSize<T>(src));
-      tmp_size = GetDimVesSize(tmp_size, src_dims[rank_ - 1]);
-      if (tmp_size > 1) {
-        type_ = kVecPermute;
-        vec_size = tmp_size;
-      }
-    }
+  ~PermTypeClassifier() = default;
 
-    // Once only transpose at the last 2 dims, there is good
-    // chance for vectorized read.
-    if ((rank_ == 2 && perm_[1] == 0 && perm_[0] == 1) ||
-        (rank_ == 3 && perm_[2] == 1 && perm_[1] == 2)) {
-      type_ = PermuteType::kTranspose;
-      int tmp_vec = std::min(vec_size, phi::GetVectorizedSize<T>(src));
-      // With bytes limitation of shared_memory, the VecSize shall be
-      // restricted for the type whose byte-size is less than 8 (double).
-      vec_size =
-          sizeof(T) > 8 ? 1 : GetDimVesSize(tmp_vec, src_dims[rank_ - 1]);
-    }
-    return vec_size;
-  }
+  int GetVecSize() const { return vec_size_; }
+  int GetRowsTile() const { return num_rows_tile_; }
+  PermuteType GetPermType() const { return type_; }
+
+ private:
+  int vec_size_{1};
+  int64_t num_rows_tile_{0};
+  PermuteType type_{kGeneralPermute};
 
   // To find if highest common divisor and make it as vec_size.
-  int GetDimVesSize(const int vec_size, const size_t target_dim) {
+  int GetDimVecSize(const int dst_vec_size,
+                    const int64_t target_dim,
+                    const T* src,
+                    bool use_share_mem = true) {
+    const int vec_size = std::min(dst_vec_size, phi::GetVectorizedSize<T>(src));
     int dim_vec_size = 1;
-    for (auto size = vec_size; size > 0; size /= 2) {
+    for (int size = vec_size; size > 0; size /= 2) {
       if (target_dim % size == 0) {
         dim_vec_size = size;
         break;
       }
     }
-    return dim_vec_size;
+
+    if (use_share_mem) {
+      // By bytes limitation of shared_memory.
+      return (sizeof(T) > sizeof(float) ? 1 : dim_vec_size);
+    } else {
+      return dim_vec_size;
+    }
   }
 };
 

paddle/phi/kernels/gpu/transpose_kernel.cu

@@ -21,7 +21,7 @@
 #include "paddle/phi/backends/gpu/gpu_primitives.h"
 #include "paddle/phi/common/bfloat16.h"
 #include "paddle/phi/core/kernel_registry.h"
-#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
+#include "paddle/phi/kernels/funcs/transpose_function.cu.h"
 #include "paddle/phi/kernels/impl/transpose_grad_kernel_impl.h"
 
 namespace phi {