feat(cambricon): add AddOp in Cambricon

src/native/cambricon/ops/add/add.h

@@ -0,0 +1,66 @@
+#ifndef INFINI_OPS_CAMBRICON_ADD_H_
+#define INFINI_OPS_CAMBRICON_ADD_H_
+
+#include "base/add.h"
+#include "native/cambricon/common.h"
+#include "native/cambricon/data_type_.h"
+
+namespace infini::ops {
+
+template <typename T>
+void AddUnion(void* workspace, int core_per_cluster, int cluster_count,
+              cnrtQueue_t queue, void* out, const void* input,
+              const void* other, const size_t* out_shape,
+              const ptrdiff_t* out_strides, const size_t* input_shape,
+              const ptrdiff_t* input_strides, const size_t* other_shape,
+              const ptrdiff_t* other_strides, size_t output_size, int ndim,
+              bool fast_path, bool out_contiguous);
+
+template <>
+class Operator<Add, Device::Type::kCambricon> : public Add {
+ public:
+  Operator(const Tensor input, const Tensor other, Tensor out)
+      : Add{input, other, out} {
+    cnrt_utils::GetLaunchConfig(input.device(), &core_per_cluster,
+                                &cluster_count);
+    cnrtMalloc(&default_workspace_, workspace_size_in_bytes());
+  }
+
+  void operator()(const Tensor input, const Tensor other,
+                  Tensor out) const override {
+    auto queue = static_cast<cnrtQueue_t>(stream_ ? stream_ : 0);
+    auto workspace{workspace_ ? workspace_ : default_workspace_};
+
+    bool fast_path = is_input_contiguous_ && is_other_contiguous_ &&
+                     is_out_contiguous_ && input_shape_ == out_shape_ &&
+                     other_shape_ == out_shape_;
+
+    DispatchFunc<List<DataType::kFloat16, DataType::kBFloat16,
+                      DataType::kFloat32, DataType::kInt32, DataType::kInt64>>(
+        {static_cast<int64_t>(out_type_)},
+        [&](auto tag) {
+          using T = TypeMapType<Device::Type::kCambricon, ListGet<0>(tag)>;
+          AddUnion<T>(workspace, core_per_cluster, cluster_count, queue,
+                      out.data(), input.data(), other.data(), out_shape_.data(),
+                      out_strides_.data(), input_shape_.data(),
+                      input_strides_.data(), other_shape_.data(),
+                      other_strides_.data(), output_size_, ndim_, fast_path,
+                      is_out_contiguous_);
+        },
+        "CambriconAdd::operator() - output dispatch");
+  }
+
+  ~Operator() { cnrtFree(default_workspace_); }
+
+  std::size_t workspace_size_in_bytes() const override {
+    return ndim_ * (3 * sizeof(size_t) + 3 * sizeof(ptrdiff_t));
+  }
+
+  void* default_workspace_{nullptr};
+  int core_per_cluster = 0;
+  int cluster_count = 0;
+};
+
+}  // namespace infini::ops
+
+#endif

src/native/cambricon/ops/add/kernel.mlu

@@ -0,0 +1,205 @@
+#include "add.h"
+
+__nram__ char nram_buffer[NRAM_MAX_SIZE];
+
+namespace infini::ops {
+
+template <typename T>
+__mlu_device__ void BangAdd(const T* src1, const T* src2, T* dst, size_t n) {
+  if constexpr (std::is_same_v<T, __half>) {
+    __bang_add(reinterpret_cast<half*>(dst),
+               reinterpret_cast<const half*>(src1),
+               reinterpret_cast<const half*>(src2), n);
+  } else {
+    __bang_add(dst, src1, src2, n);
+  }
+}
+
+template <typename T>
+__mlu_global__ void AddKernel(
+    const T* input, const T* other, T* output, const size_t* out_shape,
+    const ptrdiff_t* out_strides, const size_t* input_shape,
+    const ptrdiff_t* input_strides, const size_t* other_shape,
+    const ptrdiff_t* other_strides, size_t output_size, int ndim,
+    bool fast_path, bool out_contiguous) {
+  size_t elements_per_task = (output_size + taskDim - 1) / taskDim;
+  size_t start = taskId * elements_per_task;
+  size_t end = start + elements_per_task;
+  if (end > output_size) end = output_size;
+  size_t num_elements = end > start ? end - start : 0;
+  if (num_elements == 0) return;
+
+  size_t nram_usable = NRAM_MAX_SIZE - 256;
+  size_t block_size = nram_usable / (3 * sizeof(T));
+  block_size = (block_size / 64) * 64;  // Align to 64 elements
+  if (block_size == 0) block_size = 64;
+
+  T* input_buf = reinterpret_cast<T*>(nram_buffer);
+  T* other_buf = input_buf + block_size;
+  T* output_buf = other_buf + block_size;
+
+  size_t processed = 0;
+
+  if (fast_path) {
+    // Fast path: all tensors contiguous with matching shapes (no broadcast).
+    while (processed < num_elements) {
+      size_t curr = block_size;
+      if (curr > num_elements - processed) curr = num_elements - processed;
+
+      __memcpy(input_buf, input + start + processed, curr * sizeof(T),
+               GDRAM2NRAM);
+      __memcpy(other_buf, other + start + processed, curr * sizeof(T),
+               GDRAM2NRAM);
+      BangAdd(input_buf, other_buf, output_buf, curr);
+      __memcpy(output + start + processed, output_buf, curr * sizeof(T),
+               NRAM2GDRAM);
+
+      processed += curr;
+    }
+    return;
+  }
+
+  // General path: handle non-contiguous tensors and broadcasting.
+  while (processed < num_elements) {
+    size_t curr = block_size;
+    if (curr > num_elements - processed) curr = num_elements - processed;
+
+    for (size_t i = 0; i < curr; ++i) {
+      size_t flat_idx = start + processed + i;
+
+      // Compute `input` offset.
+      {
+        size_t tmp = flat_idx;
+        ptrdiff_t offset = 0;
+        for (int d = ndim - 1; d >= 0; --d) {
+          size_t coord = tmp % out_shape[d];
+          tmp /= out_shape[d];
+          size_t c = coord < input_shape[d] ? coord : 0;
+          offset += static_cast<ptrdiff_t>(c) * input_strides[d];
+        }
+        input_buf[i] = input[offset];
+      }
+
+      // Compute `other` offset.
+      {
+        size_t tmp = flat_idx;
+        ptrdiff_t offset = 0;
+        for (int d = ndim - 1; d >= 0; --d) {
+          size_t coord = tmp % out_shape[d];
+          tmp /= out_shape[d];
+          size_t c = coord < other_shape[d] ? coord : 0;
+          offset += static_cast<ptrdiff_t>(c) * other_strides[d];
+        }
+        other_buf[i] = other[offset];
+      }
+    }
+
+    BangAdd(input_buf, other_buf, output_buf, curr);
+
+    if (out_contiguous) {
+      __memcpy(output + start + processed, output_buf, curr * sizeof(T),
+               NRAM2GDRAM);
+    } else {
+      for (size_t i = 0; i < curr; ++i) {
+        size_t flat_idx = start + processed + i;
+        size_t tmp = flat_idx;
+        ptrdiff_t offset = 0;
+        for (int d = ndim - 1; d >= 0; --d) {
+          size_t coord = tmp % out_shape[d];
+          offset += static_cast<ptrdiff_t>(coord) * out_strides[d];
+          tmp /= out_shape[d];
+        }
+        output[offset] = output_buf[i];
+      }
+    }
+
+    processed += curr;
+  }
+}
+
+template <typename T>
+void AddUnion(void* workspace, int core_per_cluster, int cluster_count,
+              cnrtQueue_t queue, void* out, const void* input,
+              const void* other, const size_t* out_shape,
+              const ptrdiff_t* out_strides, const size_t* input_shape,
+              const ptrdiff_t* input_strides, const size_t* other_shape,
+              const ptrdiff_t* other_strides, size_t output_size, int ndim,
+              bool fast_path, bool out_contiguous) {
+  cnrtDim3_t kernel_dim;
+  cnrtFunctionType_t kernel_type;
+
+  kernel_dim.x = core_per_cluster;
+  kernel_dim.y = cluster_count;
+  kernel_dim.z = 1;
+  kernel_type = cnrtFuncTypeUnion1;
+
+  auto out_ = reinterpret_cast<T*>(out);
+  auto input_ = reinterpret_cast<const T*>(input);
+  auto other_ = reinterpret_cast<const T*>(other);
+
+  char* tmp = reinterpret_cast<char*>(workspace);
+  size_t* mlu_out_shape = reinterpret_cast<size_t*>(tmp);
+  size_t* mlu_input_shape = mlu_out_shape + ndim;
+  size_t* mlu_other_shape = mlu_input_shape + ndim;
+  ptrdiff_t* mlu_out_strides =
+      reinterpret_cast<ptrdiff_t*>(mlu_other_shape + ndim);
+  ptrdiff_t* mlu_input_strides = mlu_out_strides + ndim;
+  ptrdiff_t* mlu_other_strides = mlu_input_strides + ndim;
+
+  CNRT_CHECK(cnrtMemcpyAsync(mlu_out_shape, const_cast<size_t*>(out_shape),
+                             ndim * sizeof(size_t), queue,
+                             cnrtMemcpyHostToDev));
+  CNRT_CHECK(cnrtMemcpyAsync(mlu_input_shape, const_cast<size_t*>(input_shape),
+                             ndim * sizeof(size_t), queue,
+                             cnrtMemcpyHostToDev));
+  CNRT_CHECK(cnrtMemcpyAsync(mlu_other_shape, const_cast<size_t*>(other_shape),
+                             ndim * sizeof(size_t), queue,
+                             cnrtMemcpyHostToDev));
+  CNRT_CHECK(
+      cnrtMemcpyAsync(mlu_out_strides, const_cast<ptrdiff_t*>(out_strides),
+                      ndim * sizeof(ptrdiff_t), queue, cnrtMemcpyHostToDev));
+  CNRT_CHECK(
+      cnrtMemcpyAsync(mlu_input_strides, const_cast<ptrdiff_t*>(input_strides),
+                      ndim * sizeof(ptrdiff_t), queue, cnrtMemcpyHostToDev));
+  CNRT_CHECK(
+      cnrtMemcpyAsync(mlu_other_strides, const_cast<ptrdiff_t*>(other_strides),
+                      ndim * sizeof(ptrdiff_t), queue, cnrtMemcpyHostToDev));
+
+  AddKernel<T><<<kernel_dim, kernel_type, queue>>>(
+      input_, other_, out_, mlu_out_shape, mlu_out_strides, mlu_input_shape,
+      mlu_input_strides, mlu_other_shape, mlu_other_strides, output_size, ndim,
+      fast_path, out_contiguous);
+
+  cnrtQueueSync(queue);
+}
+
+template void AddUnion<__half>(void*, int, int, cnrtQueue_t, void*, const void*,
+                               const void*, const size_t*, const ptrdiff_t*,
+                               const size_t*, const ptrdiff_t*, const size_t*,
+                               const ptrdiff_t*, size_t, int, bool, bool);
+
+template void AddUnion<__bang_bfloat16>(void*, int, int, cnrtQueue_t, void*,
+                                        const void*, const void*, const size_t*,
+                                        const ptrdiff_t*, const size_t*,
+                                        const ptrdiff_t*, const size_t*,
+                                        const ptrdiff_t*, size_t, int, bool,
+                                        bool);
+
+template void AddUnion<float>(void*, int, int, cnrtQueue_t, void*, const void*,
+                              const void*, const size_t*, const ptrdiff_t*,
+                              const size_t*, const ptrdiff_t*, const size_t*,
+                              const ptrdiff_t*, size_t, int, bool, bool);
+
+template void AddUnion<int32_t>(void*, int, int, cnrtQueue_t, void*,
+                                const void*, const void*, const size_t*,
+                                const ptrdiff_t*, const size_t*,
+                                const ptrdiff_t*, const size_t*,
+                                const ptrdiff_t*, size_t, int, bool, bool);
+
+template void AddUnion<int64_t>(void*, int, int, cnrtQueue_t, void*,
+                                const void*, const void*, const size_t*,
+                                const ptrdiff_t*, const size_t*,
+                                const ptrdiff_t*, const size_t*,
+                                const ptrdiff_t*, size_t, int, bool, bool);
+
+}  // namespace infini::ops

tests/test_add.py

@@ -60,6 +60,11 @@ def test_add(
             "The `torch.musa` test cloning path does not support `uint16`, `uint32`, or `uint64`."
         )
 
+    if device == "mlu" and (dtype in _UINT_DTYPES or dtype == torch.int16):
+        pytest.skip(
+            "The `torch.mlu` test cloning path does not support `int16`, `uint16`, `uint32`, or `uint64`."
+        )
+
     if implementation_index == 1 and dtype in _UINT_DTYPES:
         pytest.skip("ATen `add` does not support unsigned integer types")