Fix __shfl_down_sync_ of cross_entropy (#10345)

* fix __shfl_down_sync_ of cross_entropy

* use reduceSum

* "fix ci"

paddle/fluid/operators/elementwise_op_function.h

@@ -22,6 +22,7 @@ limitations under the License. */
 #ifdef __NVCC__
 #include <cuda.h>
 #include <thrust/iterator/iterator_adaptor.h>
+#include "paddle/fluid/platform/cuda_device_function.h"
 #include "paddle/fluid/platform/cuda_primitives.h"
 constexpr int ELEMWISE_MAX_BLOCK_DIM = 1024;
 #endif
@@ -336,43 +337,6 @@ static void ElemwiseGradBroadcast1CPU(const T* x, const T* y, const T* out,
 }
 
 #ifdef __NVCC__
-
-template <typename T>
-__device__ T reduceSum(T val, int tid, int len) {
-  // NOTE(zcd): The warp size should be taken from the
-  // parameters of the GPU but not specified as 32 simply.
-  // To make the reduceSum more efficiently,
-  // I use Warp-Level Parallelism and assume the Warp size
-  // is 32 which may be different for different GPU,
-  // but most card's warp size is 32.
-  const int warpSize = 32;
-  __shared__ T shm[warpSize];
-  unsigned mask = 0u;
-  CREATE_SHFL_MASK(mask, tid < len);
-
-  for (int offset = warpSize / 2; offset > 0; offset /= 2)
-    val += platform::__shfl_down_sync(mask, val, offset);
-
-  if (tid < warpSize) shm[tid] = 0;
-
-  __syncthreads();
-
-  if (tid % warpSize == 0) {
-    shm[tid / warpSize] = val;
-  }
-  __syncthreads();
-
-  CREATE_SHFL_MASK(mask, tid < warpSize);
-
-  if (tid < warpSize) {
-    val = shm[tid];
-    for (int offset = warpSize / 2; offset > 0; offset /= 2)
-      val += platform::__shfl_down_sync(mask, val, offset);
-  }
-
-  return val;
-}
-
 template <typename T, typename DX_OP, typename DY_OP>
 static __global__ void ElemwiseGradBroadcast1CUDAKernel(
     const T* x, const T* y, const T* out, const T* dout, int h, int w,
@@ -395,7 +359,7 @@ static __global__ void ElemwiseGradBroadcast1CUDAKernel(
 
   if (dy) {
     h = h > ELEMWISE_MAX_BLOCK_DIM ? ELEMWISE_MAX_BLOCK_DIM : h;
-    val = reduceSum(val, tid, h);
+    val = paddle::platform::reduceSum(val, tid, h);
     if (threadIdx.x == 0) {
       dy[j] = val;
     }
@@ -472,7 +436,7 @@ static __global__ void ElemwiseGradBroadcast2CUDAKernel(
   if (dy) {
     int h = pre * post;
     h = h > ELEMWISE_MAX_BLOCK_DIM ? ELEMWISE_MAX_BLOCK_DIM : h;
-    val = reduceSum(val, tid, h);
+    val = paddle::platform::reduceSum(val, tid, h);
     if (threadIdx.x == 0) {
       dy[j] = val;
     }

paddle/fluid/operators/math/cross_entropy.cu

@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/math/cross_entropy.h"
+#include "paddle/fluid/platform/cuda_device_function.h"
 #include "paddle/fluid/platform/cuda_primitives.h"
 
 namespace paddle {
@@ -30,66 +31,22 @@ __global__ void CrossEntropyKernel(T* Y, const T* X, const int64_t* label,
   }
 }
 
-template <typename T>
-__device__ __forceinline__ T sum_single_warp(T val) {
-  val += platform::__shfl_down_sync(0, val, 16);
-  val += platform::__shfl_down_sync(0, val, 8);
-  val += platform::__shfl_down_sync(0, val, 4);
-  val += platform::__shfl_down_sync(0, val, 2);
-  val += platform::__shfl_down_sync(0, val, 1);
-  return val;
-}
-
-// CUDA do not support dynamic arrary in template
-// https://stackoverflow.com/questions/20497209
-template <typename T>
-struct SharedMemory {
-  // Ensure that we won't compile any un-specialized types
-  __device__ T* GetPointer() { return NULL; }
-};
-
-template <>
-struct SharedMemory<float> {
-  __device__ float* GetPointer() {
-    extern __shared__ float s_float[];
-    return s_float;
-  }
-};
-
-template <>
-struct SharedMemory<double> {
-  __device__ double* GetPointer() {
-    extern __shared__ double s_double[];
-    return s_double;
-  }
-};
-
 template <typename T>
 __global__ void SoftCrossEntropyKernel(T* Y, const T* X, const T* label,
                                        const int class_num) {
   int tid = threadIdx.x;
-  SharedMemory<T> d_sum_shared;
-  T* d_sum = d_sum_shared.GetPointer();
-  d_sum[tid] = 0;
+  T val = 0;
 
-  int cur_idx = tid;
-  int next_idx = blockIdx.x * class_num + tid;
-  while (cur_idx < class_num) {
-    d_sum[tid] +=
-        math::TolerableValue<T>()(std::log(X[next_idx])) * label[next_idx];
-    next_idx += blockDim.x;
-    cur_idx += blockDim.x;
+  int idx = blockIdx.x * class_num + tid;
+  int end = blockIdx.x * class_num + class_num;
+  for (; idx < end; idx += blockDim.x) {
+    val += math::TolerableValue<T>()(std::log(X[idx])) * label[idx];
   }
-  __syncthreads();
 
-  for (unsigned int stride = blockDim.x >> 1; stride >= 32; stride >>= 1) {
-    if (tid < stride) d_sum[tid] += d_sum[tid + stride];
-    __syncthreads();
+  val = paddle::platform::reduceSum(val, tid, blockDim.x);
+  if (threadIdx.x == 0) {
+    Y[blockIdx.x] = -val;
   }
-
-  T val = d_sum[tid];
-  val = sum_single_warp<T>(val);
-  if (tid == 0) Y[blockIdx.x] = -val;
 }
 }  // namespace
 
@@ -113,9 +70,7 @@ class CrossEntropyFunctor<platform::CUDADeviceContext, T> {
                       ? 512
                       : pow(2, static_cast<int>(std::log2(class_num)));
 
-      SoftCrossEntropyKernel<T><<<
-          batch_size, block, block * sizeof(T),
-          reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream()>>>(
+      SoftCrossEntropyKernel<T><<<batch_size, block, 0, ctx.stream()>>>(
           loss_data, prob_data, label_data, class_num);
     } else {
       const int64_t* label_data = labels->data<int64_t>();

paddle/fluid/operators/row_conv_op.cu

@@ -14,7 +14,7 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/math/math_function.h"
 #include "paddle/fluid/operators/row_conv_op.h"
-#include "paddle/fluid/platform/cuda_primitives.h"
+#include "paddle/fluid/platform/cuda_device_function.h"
 
 namespace paddle {
 namespace operators {

paddle/fluid/platform/cuda_device_function.h

@@ -0,0 +1,74 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+#include <cuda.h>
+
+namespace paddle {
+namespace platform {
+
+// __shfl_down and __shfl have been deprecated as of CUDA 9.0.
+#if CUDA_VERSION < 9000
+template <typename T>
+__forceinline__ __device__ T __shfl_down_sync(unsigned, T val, int delta) {
+  return __shfl_down(val, delta);
+}
+
+template <typename T>
+__forceinline__ __device__ T __shfl_sync(unsigned, T val, int src_line,
+                                         int width) {
+  return __shfl(val, src_line, width);
+}
+#define CREATE_SHFL_MASK(mask, predicate) mask = 0u;
+#else
+#define FULL_WARP_MASK 0xFFFFFFFF
+#define CREATE_SHFL_MASK(mask, predicate) \
+  mask = __ballot_sync(FULL_WARP_MASK, (predicate))
+#endif
+
+template <typename T>
+__device__ T reduceSum(T val, int tid, int len) {
+  // NOTE(zcd): The warp size should be taken from the
+  // parameters of the GPU but not specified as 32 simply.
+  // To make the reduceSum more efficiently,
+  // I use Warp-Level Parallelism and assume the Warp size
+  // is 32 which may be different for different GPU,
+  // but most card's warp size is 32.
+  const int warpSize = 32;
+  __shared__ T shm[warpSize];
+  unsigned mask = 0u;
+  CREATE_SHFL_MASK(mask, tid < len);
+
+  for (int offset = warpSize / 2; offset > 0; offset /= 2)
+    val += platform::__shfl_down_sync(mask, val, offset);
+
+  if (tid < warpSize) shm[tid] = 0;
+
+  if (tid % warpSize == 0) {
+    shm[tid / warpSize] = val;
+  }
+  __syncthreads();
+
+  CREATE_SHFL_MASK(mask, tid < warpSize);
+
+  if (tid < warpSize) {
+    val = shm[tid];
+    for (int offset = warpSize / 2; offset > 0; offset /= 2)
+      val += platform::__shfl_down_sync(mask, val, offset);
+  }
+  return val;
+}
+
+}  // namespace platform
+}  // namespace paddle

paddle/fluid/platform/cuda_primitives.h

@@ -66,18 +66,5 @@ CUDA_ATOMIC_WRAPPER(Add, double) {
 }
 #endif
 
-// __shfl_down has been deprecated as of CUDA 9.0.
-#if CUDA_VERSION < 9000
-template <typename T>
-__forceinline__ __device__ T __shfl_down_sync(unsigned, T val, int delta) {
-  return __shfl_down(val, delta);
-}
-#define CREATE_SHFL_MASK(mask, predicate) mask = 0u;
-#else
-#define FULL_WARP_MASK 0xFFFFFFFF
-#define CREATE_SHFL_MASK(mask, predicate) \
-  mask = __ballot_sync(FULL_WARP_MASK, (predicate))
-#endif
-
 }  // namespace platform
 }  // namespace paddle