added a specialization for cuda copy op when tensor is transposed

Author: bssrdf

ggml/src/ggml-cuda/cpy.cu

@@ -37,6 +37,48 @@ static __global__ void cpy_flt(const char * cx, char * cdst_direct, const int ne
     cpy_1(cx + x_offset, cdst + dst_offset);
 }
 
+
+template <typename T>
+static __global__ void cpy_flt_transpose(char * cx, char * cdst_direct,, const int ne,
+                               const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
+                               const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
+                               const int nb12, const int nb13, char ** cdst_indirect, int graph_cpynode_index) {
+
+    char * cdst = (cdst_indirect != nullptr) ? cdst_indirect[graph_cpynode_index]: cdst_direct;
+
+    const T* src = reinterpret_cast<const T*>(cx);
+    T* dst = reinterpret_cast<T*>(cdst);
+
+    const int64_t nmat = ne /(ne00 * ne01);
+    const int64_t n = ne00 * ne01;
+    // const int64_t n = ne01 * ne02;
+    int width = gridDim.x * TILE_DIM;
+    int x = blockIdx.x * TILE_DIM + threadIdx.x;
+    int y = blockIdx.y * TILE_DIM + threadIdx.y;
+    int tx = blockIdx.y * TILE_DIM + threadIdx.x;  // transpose block offset
+    int ty = blockIdx.x * TILE_DIM + threadIdx.y;
+
+    __shared__ T tile[TILE_DIM * TILE_DIM];
+
+    for(int i = 0; i < BLOCK_NM; ++i){
+        const unsigned int imat = blockIdx.z * BLOCK_NM + i;
+        if(imat < nmat){
+            for (int j = 0; j < TILE_DIM; j += BLOCK_ROWS){
+                const unsigned int idx = (y+j)*width + x;
+                if(idx < n)
+                    tile[threadIdx.y+j][threadIdx.x] = src[imat*n + idx];
+            }
+            __syncthreads();
+
+            for (int j = 0; j < TILE_DIM; j += BLOCK_ROWS){
+                const unsigned int idx = (ty+j)*width + tx;
+                if(idx < n)
+                    dst[imat*n + idx] = tile[threadIdx.x][threadIdx.y + j];
+            }
+        }
+    }
+}
+
 static __device__ void cpy_blck_q8_0_f32(const char * cxi, char * cdsti) {
     float * cdstf = (float *)(cdsti);
 
@@ -143,10 +185,25 @@ static void ggml_cpy_flt_cuda(
     const char * cx, char * cdst, const int ne,
     const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
     const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
-
     const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
-    cpy_flt<cpy_1_flt<src_t, dst_t>><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
-        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
+    if constexpr (std::is_same_v<src_t, half> && std::is_same_v<dst_t, half> ||
+                  std::is_same_v<src_t, float> && std::is_same_v<dst_t, float>
+                ){
+        if (ne00 == ne11 && ne01 = ne10 && nb00 == nb11 && nb10 == nb01){ //transpose
+            dim3 dimGrid( (ne00 + TILE_DIM - 1) / TILE_DIM,
+                          (ne01 + TILE_DIM - 1) / TILE_DIM,
+                          (ne/(ne00*ne01) + BLOCK_NM - 1) / BLOCK_NM );
+            dim3 dimBlock(TILE_DIM, BLOCK_ROWS, 1);
+            cpy_flt_transpose<cpy_1_flt<dst_t><<<dimGrid, dimBlock, 0, stream>>>
+                (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
+        } else{ // other
+            cpy_flt<cpy_1_flt<src_t, dst_t>><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
+                (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
+        }
+    } else{
+        cpy_flt<cpy_1_flt<src_t, dst_t>><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
+            (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
+    }
 }
 
 static void ggml_cpy_f32_q8_0_cuda(

ggml/src/ggml-cuda/cpy.cuh

@@ -2,6 +2,11 @@
 
 #define CUDA_CPY_BLOCK_SIZE 64
 
+const int TILE_DIM = 32;
+const int BLOCK_ROWS = 8;
+const int BLOCK_NM = 8;
+
+
 void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1,  bool disable_indirection = false);
 
 void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst);