Optimize bilinear interpolation foward (#39243)

* bilinear_fw init

* optimize code

* pre-compute linear_interp input index

paddle/fluid/operators/interpolate_v2_op.cu

@@ -59,6 +59,17 @@ inline platform::GpuLaunchConfig GetGpuLaunchConfig3D(
   return config;
 }
 
+template <typename T>
+__forceinline__ __device__ void PreCalculatorForLinearInterpInputIndex(
+    int* in_img_idx, int* w_id, T* w1lambda, T* w2lambda, T src_w,
+    const int in_img_w) {
+  src_w = (src_w > 0) ? src_w : 0.f;
+  *in_img_idx = static_cast<int>(src_w);
+  *w_id = (*in_img_idx < in_img_w - 1) ? 1 : 0;
+  *w1lambda = src_w - *in_img_idx;
+  *w2lambda = 1.f - *w1lambda;
+}
+
 struct FastDivModForInterpolate {
  public:
   FastDivMod channels_div;
@@ -417,96 +428,93 @@ __global__ void KeLinearInterpBw(T* in, const size_t in_img_w,
 }
 
 template <typename T>
-__global__ void KeBilinearInterpFw(
-    const T* in, const size_t in_img_h, const size_t in_img_w,
-    const size_t input_h, const size_t input_w, T* out, const size_t out_img_h,
-    const size_t out_img_w, const size_t output_h, const size_t output_w,
-    const size_t num_channels, const float ratio_h, const float ratio_w,
-    const bool align_corners, const int align_mode,
-    const DataLayout data_layout) {
-  int nthreads = output_h * output_w;
-  int tid = blockIdx.x * blockDim.x + threadIdx.x;
-  int stride = blockDim.x * gridDim.x;
-  bool align_flag = (align_mode == 0 && !align_corners);
-  for (; tid < nthreads; tid += stride) {
-    int out_id_h = tid / output_w;
-    int out_id_w = tid % output_w;
-    int in_img_size = input_w / num_channels;
-    int out_img_size = output_w / num_channels;
+__global__ void KeBilinearInterpNCHWFw(const T* in, const size_t in_img_h,
+                                       const size_t in_img_w, T* out,
+                                       const size_t out_img_h,
+                                       const size_t out_img_w, const size_t nc,
+                                       const float ratio_h, const float ratio_w,
+                                       const T align_type_value) {
+  int out_img_idx = threadIdx.x + blockIdx.x * blockDim.x;
+  int out_img_idy = threadIdx.y + blockIdx.y * blockDim.y;
+  int nc_id = threadIdx.z + blockIdx.z * blockDim.z;
+  int nc_stride = blockDim.z * gridDim.z;
 
-    int channel_id, out_img_idy, out_img_idx;
-    if (data_layout == DataLayout::kNCHW) {
-      channel_id = out_id_w / out_img_size;
-      out_img_idy = (out_id_w % out_img_size) / out_img_w;
-      out_img_idx = tid % out_img_w;
-    } else {
-      out_img_idy = out_id_w / (out_img_w * num_channels);
-      out_img_idx = out_id_w % (out_img_w * num_channels) / num_channels;
-      channel_id = tid % num_channels;
-    }
+  int in_img_idx, in_img_idy, h_id, w_id;
+  T h1lambda, w1lambda, h2lambda, w2lambda;
+  T src_w = ratio_w * (out_img_idx + align_type_value) - align_type_value;
+  T src_h = ratio_h * (out_img_idy + align_type_value) - align_type_value;
 
-    int in_img_idy = align_flag
-                         ? static_cast<int>(ratio_h * (out_img_idy + 0.5) - 0.5)
-                         : static_cast<int>(ratio_h * out_img_idy);
-    in_img_idy = (in_img_idy > 0) ? in_img_idy : 0;
-    int h_id = (in_img_idy < in_img_h - 1) ? 1 : 0;
-    T src_h = ratio_h * (out_img_idy + 0.5) - 0.5;
-    src_h = (src_h > 0) ? src_h : 0;
-    T h1lambda =
-        align_flag ? src_h - in_img_idy : ratio_h * out_img_idy - in_img_idy;
-    T h2lambda = 1.f - h1lambda;
+  PreCalculatorForLinearInterpInputIndex(&in_img_idx, &w_id, &w1lambda,
+                                         &w2lambda, src_w, in_img_w);
+  PreCalculatorForLinearInterpInputIndex(&in_img_idy, &h_id, &h1lambda,
+                                         &h2lambda, src_h, in_img_h);
 
-    int in_img_idx = align_flag
-                         ? static_cast<int>(ratio_w * (out_img_idx + 0.5) - 0.5)
-                         : static_cast<int>(ratio_w * out_img_idx);
-    in_img_idx = (in_img_idx > 0) ? in_img_idx : 0;
-    int w_id = (in_img_idx < in_img_w - 1) ? 1 : 0;
-    T src_w = ratio_w * (out_img_idx + 0.5) - 0.5;
-    src_w = (src_w > 0) ? src_w : 0;
-    T w1lambda =
-        align_flag ? src_w - in_img_idx : ratio_w * out_img_idx - in_img_idx;
-    T w2lambda = 1.f - w1lambda;
+  int in_index = (nc_id * in_img_h + in_img_idy) * in_img_w + in_img_idx;
+  int in_index_stride = nc_stride * in_img_h * in_img_w;
 
-    if (data_layout == DataLayout::kNCHW) {
-      const T* in_pos = &in[out_id_h * input_w + channel_id * in_img_size +
-                            in_img_idy * in_img_w + in_img_idx];
+  int out_index = (nc_id * out_img_h + out_img_idy) * out_img_w + out_img_idx;
+  int out_index_stride = nc_stride * out_img_h * out_img_w;
 
-      // bilinear interpolation
-      out[out_id_h * output_w + out_id_w] =
+  // prevent from multiple threads writing
+  if (out_img_idx < out_img_w && out_img_idy < out_img_h) {
+    while (nc_id < nc) {
+      const T* in_pos = &in[in_index];
+      out[out_index] =
           h2lambda * (w2lambda * in_pos[0] + w1lambda * in_pos[w_id]) +
           h1lambda * (w2lambda * in_pos[h_id * in_img_w] +
                       w1lambda * in_pos[h_id * in_img_w + w_id]);
-    } else {
-      const T* in_pos =
-          &in[out_id_h * input_w + in_img_idy * in_img_w * num_channels +
-              in_img_idx * num_channels + channel_id];
 
-      // bilinear interpolation
-      out[out_id_h * output_w + out_id_w] =
-          h2lambda *
-              (w2lambda * in_pos[0] + w1lambda * in_pos[w_id * num_channels]) +
-          h1lambda * (w2lambda * in_pos[h_id * in_img_w * num_channels] +
-                      w1lambda * in_pos[h_id * in_img_w * num_channels +
-                                        w_id * num_channels]);
+      in_index += in_index_stride;
+      out_index += out_index_stride;
+      nc_id += nc_stride;
     }
   }
 }
 
 template <typename T>
-__forceinline__ __device__ void PreCalculatorForInputIndex(
-    int* in_img_idx, int* in_img_idy, int* w_id, int* h_id, T* w1lambda,
-    T* h1lambda, T* w2lambda, T* h2lambda, T src_w, T src_h, const int in_img_w,
-    const int in_img_h) {
-  src_w = (src_w > 0) ? src_w : 0.f;
-  src_h = (src_h > 0) ? src_h : 0.f;
-  *in_img_idx = static_cast<int>(src_w);
-  *in_img_idy = static_cast<int>(src_h);
-  *w_id = (*in_img_idx < in_img_w - 1) ? 1 : 0;
-  *h_id = (*in_img_idy < in_img_h - 1) ? 1 : 0;
-  *w1lambda = src_w - *in_img_idx;
-  *h1lambda = src_h - *in_img_idy;
-  *w2lambda = 1.f - *w1lambda;
-  *h2lambda = 1.f - *h1lambda;
+__global__ void KeBilinearInterpFw(
+    const T* in, const size_t in_img_h, const size_t in_img_w,
+    const size_t input_h, const size_t input_w, T* out, const size_t out_img_h,
+    const size_t out_img_w, const size_t output_h, const size_t output_w,
+    const size_t num_channels, const float ratio_h, const float ratio_w,
+    const T align_type_value, FastDivModForInterpolate divmods) {
+  int nthreads = output_h * output_w;
+  int tid = blockIdx.x * blockDim.x + threadIdx.x;
+  int stride = blockDim.x * gridDim.x;
+
+  for (; tid < nthreads; tid += stride) {
+    auto out_id_divmod = divmods.output_w_div.Divmod(tid);
+    int out_id_h = out_id_divmod.val[0];
+    int out_id_w = out_id_divmod.val[1];
+
+    int channel_id = divmods.channels_div.Divmod(tid).val[1];
+    auto outimg_id_divmod = divmods.output_wc_div.Divmod(out_id_w);
+    int out_img_idy = outimg_id_divmod.val[0];
+    int out_img_idx =
+        divmods.channels_div.Divmod(outimg_id_divmod.val[1]).val[0];
+
+    int in_img_idx, in_img_idy, h_id, w_id;
+    T h1lambda, w1lambda, h2lambda, w2lambda;
+    T src_w = ratio_w * (out_img_idx + align_type_value) - align_type_value;
+    T src_h = ratio_h * (out_img_idy + align_type_value) - align_type_value;
+
+    PreCalculatorForLinearInterpInputIndex(&in_img_idx, &w_id, &w1lambda,
+                                           &w2lambda, src_w, in_img_w);
+    PreCalculatorForLinearInterpInputIndex(&in_img_idy, &h_id, &h1lambda,
+                                           &h2lambda, src_h, in_img_h);
+
+    // bilinear interpolation
+    const T* in_pos =
+        &in[out_id_h * input_w + in_img_idy * in_img_w * num_channels +
+            in_img_idx * num_channels + channel_id];
+    out[tid] =
+        h2lambda *
+            (w2lambda * in_pos[0] + w1lambda * in_pos[w_id * num_channels]) +
+        h1lambda *
+            (w2lambda * in_pos[h_id * in_img_w * num_channels] +
+             w1lambda *
+                 in_pos[h_id * in_img_w * num_channels + w_id * num_channels]);
+  }
 }
 
 /* Calculate the minimum of partial elements in a block */
@@ -574,9 +582,11 @@ __global__ void KeBilinearInterpBwShareMemory(
     T w1lambda, h1lambda, w2lambda, h2lambda;
     T src_w = ratio_w * (out_img_idx + align_type_value) - align_type_value;
     T src_h = ratio_h * (out_img_idy + align_type_value) - align_type_value;
-    PreCalculatorForInputIndex(&in_img_idx, &in_img_idy, &w_id, &h_id,
-                               &w1lambda, &h1lambda, &w2lambda, &h2lambda,
-                               src_w, src_h, in_w, in_h);
+
+    PreCalculatorForLinearInterpInputIndex(&in_img_idx, &w_id, &w1lambda,
+                                           &w2lambda, src_w, in_w);
+    PreCalculatorForLinearInterpInputIndex(&in_img_idy, &h_id, &h1lambda,
+                                           &h2lambda, src_h, in_h);
 
     // top_left_index is just input_index.
     int input_index = out_id_h * in_chw + channel_id * in_img_size +
@@ -661,9 +671,11 @@ __global__ void KeBilinearInterpBw(T* in, const int in_h, const int in_w,
 
       T src_w = ratio_w * (out_img_idx + align_type_value) - align_type_value;
       T src_h = ratio_h * (out_img_idy + align_type_value) - align_type_value;
-      PreCalculatorForInputIndex(&in_img_idx, &in_img_idy, &w_id, &h_id,
-                                 &w1lambda, &h1lambda, &w2lambda, &h2lambda,
-                                 src_w, src_h, in_w, in_h);
+
+      PreCalculatorForLinearInterpInputIndex(&in_img_idx, &w_id, &w1lambda,
+                                             &w2lambda, src_w, in_w);
+      PreCalculatorForLinearInterpInputIndex(&in_img_idy, &h_id, &h1lambda,
+                                             &h2lambda, src_h, in_h);
 
       T* in_pos = &in[out_id_h * in_chw + channel_id * in_img_size +
                       in_img_idy * in_w + in_img_idx];
@@ -690,9 +702,11 @@ __global__ void KeBilinearInterpBw(T* in, const int in_h, const int in_w,
       T w1lambda, h1lambda, w2lambda, h2lambda;
       T src_w = ratio_w * (out_img_idx + align_type_value) - align_type_value;
       T src_h = ratio_h * (out_img_idy + align_type_value) - align_type_value;
-      PreCalculatorForInputIndex(&in_img_idx, &in_img_idy, &w_id, &h_id,
-                                 &w1lambda, &h1lambda, &w2lambda, &h2lambda,
-                                 src_w, src_h, in_w, in_h);
+
+      PreCalculatorForLinearInterpInputIndex(&in_img_idx, &w_id, &w1lambda,
+                                             &w2lambda, src_w, in_w);
+      PreCalculatorForLinearInterpInputIndex(&in_img_idy, &h_id, &h1lambda,
+                                             &h2lambda, src_h, in_h);
 
       T* in_pos = &in[out_id_h * in_chw + in_img_idy * in_w * num_channels +
                       in_img_idx * num_channels + channel_id];
@@ -1398,11 +1412,25 @@ static void Interpolate2DCUDAFwd(const framework::ExecutionContext& ctx,
       thread_num = 512;
     }
 #endif
-
-    KeBilinearInterpFw<T><<<config.block_per_grid, thread_num, 0,
-                            ctx.cuda_device_context().stream()>>>(
-        input_data, in_h, in_w, n, in_chw, output_data, out_h, out_w, n,
-        out_chw, c, ratio_h, ratio_w, align_corners, align_mode, data_layout);
+    const T align_type_value = (align_mode == 0 && !align_corners) ? 0.5f : 0;
+    if (data_layout == DataLayout::kNCHW) {
+      // get launch 3D config
+      int nc = n * c;
+      platform::GpuLaunchConfig config_3d =
+          GetGpuLaunchConfig3D(ctx.cuda_device_context(), nc, out_h, out_w);
+      KeBilinearInterpNCHWFw<
+          T><<<config_3d.block_per_grid, config_3d.thread_per_block, 0,
+               ctx.cuda_device_context().stream()>>>(
+          input_data, in_h, in_w, output_data, out_h, out_w, nc, ratio_h,
+          ratio_w, align_type_value);
+    } else {
+      int64_t cw = c * out_w;
+      auto interp_divmods = FastDivModForInterpolate(c, out_chw, cw);
+      KeBilinearInterpFw<T><<<config.block_per_grid, thread_num, 0,
+                              ctx.cuda_device_context().stream()>>>(
+          input_data, in_h, in_w, n, in_chw, output_data, out_h, out_w, n,
+          out_chw, c, ratio_h, ratio_w, align_type_value, interp_divmods);
+    }
   } else if ("bicubic" == interp_method) {
 #ifdef __HIPCC__
     constexpr int thread_per_block = 256;