Modified distribution kernel with Kernel Primitive API

paddle/fluid/operators/distribution_helper.h

@@ -28,6 +28,10 @@ limitations under the License. */
 #include "paddle/fluid/platform/for_range.h"
 #include "paddle/pten/core/hostdevice.h"
 
+#if defined(__NVCC__) || defined(__HIPCC__)
+#include "paddle/pten/kernels/primitive/kernel_primitives.h"
+#endif
+
 #if !defined(_WIN32)
 #define UNLIKELY(condition) __builtin_expect(static_cast<bool>(condition), 0)
 #else
@@ -91,6 +95,8 @@ struct normal_transform {
 
 #if defined(__NVCC__) || defined(__HIPCC__)
 
+namespace kps = pten::kps;
+
 /*********************** Distribution Function *************************/
 template <typename T>
 struct uniform_distribution;
@@ -176,25 +182,26 @@ template <typename T, typename DistOp, typename TransformOp>
 __global__ void DistributionKernel(size_t size, uint64_t seed, uint64_t offset,
                                    DistOp dist, TransformOp trans,
                                    T *out_data) {
-  size_t idx = static_cast<size_t>(blockIdx.x * blockDim.x + threadIdx.x);
-  int32_t returns_count = DistOp::kReturnsCount;
+  size_t idx = static_cast<size_t>(BLOCK_ID_X * BLOCK_NUM_X);
+  static constexpr int kCount = DistOp::kReturnsCount;
 #if defined(__NVCC__)
   curandStatePhilox4_32_10_t state;
-  curand_init(seed, idx, offset, &state);
+  curand_init(seed, idx + THREAD_ID_X, offset, &state);
+  using SType = curandStatePhilox4_32_10_t;
 #else
   hiprandStatePhilox4_32_10_t state;
-  hiprand_init(seed, idx, offset, &state);
+  hiprand_init(seed, idx + THREAD_ID_X, offset, &state);
+  using SType = hiprandStatePhilox4_32_10_t;
 #endif
-  size_t total_thread = gridDim.x * blockDim.x;
-  for (size_t i = idx; i < size; i += total_thread * returns_count) {
-    auto random_tuple = dist(&state);
-    for (size_t j = 0; j < returns_count; j++) {
-      size_t index = i + j * total_thread;
-      if (index < size) {
-        auto random = (&random_tuple.x)[j];
-        out_data[index] = static_cast<T>(trans(random));
-      }
-    }
+  size_t total_thread = GRID_NUM_X * BLOCK_NUM_X;
+  T args[kCount];
+  T result[kCount];
+  for (size_t i = idx; i < size; i += total_thread * kCount) {
+    kps::ElementwiseRandom<SType, T, kCount, 1, DistOp>(&args[0], dist, &state);
+    kps::ElementwiseUnary<T, T, kCount, 1, 1, TransformOp>(&result[0], &args[0],
+                                                           trans);
+    kps::WriteData<T, T, kCount, 1, 1, true>(out_data + i, &result[0], size - i,
+                                             1, total_thread, 1);
   }
 }
 

paddle/pten/kernels/primitive/compute_primitives.h

@@ -428,5 +428,58 @@ __device__ __forceinline__ void ElementwiseConstant(OutT* out, OpFunc compute) {
   }
 }
 
+template <typename StateType,
+          typename OutT,
+          int ReturnsCount,
+          int BlockSize,
+          class OpFunc>
+__device__ __forceinline__ void ElementwiseRandom(OutT* out,
+                                                  OpFunc compute,
+                                                  StateType* state) {
+  auto random_tuple = compute(state);
+#pragma unroll
+  for (int i = 0; i < ReturnsCount; i++) {
+    out[i] = static_cast<OutT>((&random_tuple.x)[i]);
+  }
+}
+
+// attention please set share_size = blockDim.x;
+// data and b are the register pointer
+#define shared_size 64
+template <typename InT,
+          typename OutT,
+          int NX,
+          int NY,
+          int BlockSize,
+          class OpFunc>
+__device__ __forceinline__ void Cumsum(OutT* out,
+                                       const InT* in,
+                                       OpFunc compute) {
+  __shared__ InT temp[shared_size * 2 + (shared_size * 2) / 32];
+  int tidx = threadIdx.x;
+  temp[tidx + tidx / 32] = in[0];
+  temp[shared_size + tidx + (shared_size + tidx) / 32] = in[1];
+  for (int stride = 1; stride <= blockDim.x; stride *= 2) {
+    __syncthreads();
+    int index = (tidx + 1) * 2 * stride - 1;
+    if (index < (blockDim.x * 2)) {
+      temp[index + index / 32] += temp[index - stride + (index - stride) / 32];
+    }
+  }
+  for (int stride = (blockDim.x * 2) / 4; stride > 0; stride /= 2) {
+    __syncthreads();
+    int index = (tidx + 1) * 2 * stride - 1;
+    if ((index + stride) < (blockDim.x * 2)) {
+      temp[index + stride + (stride + index) / 32] +=
+          temp[index + (index) / 32];
+    }
+  }
+
+  __syncthreads();
+  out[0] = static_cast<OutT>(temp[tidx + tidx / 32]);
+  out[1] =
+      static_cast<OutT>(temp[tidx + shared_size + (tidx + shared_size) / 32]);
+}
+
 }  // namespace kps
 }  // namespace pten