CUDA: fuse rope + set_rows (#16884)
* CUDA: add fused rope * move k forward_expand up * create helper function instead of re-using params * make assert statement more in line with comment * rope_norm: coalesced writes to global mem
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@@ -2992,6 +2992,36 @@ static void update_cuda_graph_executable(ggml_backend_cuda_context * cuda_ctx) {
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}
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#endif
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static bool ggml_cuda_should_fuse_rope_set_rows(const ggml_tensor * rope,
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const ggml_tensor * view,
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const ggml_tensor * set_rows) {
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// ne3 not tested
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if (rope->src[0]->ne[3] != 1) {
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return false;
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}
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if (set_rows->type != GGML_TYPE_F32 && set_rows->type != GGML_TYPE_F16) {
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return false;
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}
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if (set_rows->src[1]->type != GGML_TYPE_I64) {
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return false;
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}
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// The view should flatten two dims of rope into one dim
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if (!ggml_is_contiguous(view) || view->ne[0] != rope->ne[0] * rope->ne[1]) {
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return false;
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}
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// Only norm/neox shaders have the fusion code
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const int mode = ((const int32_t *) rope->op_params)[2];
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if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) {
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return false;
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}
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return true;
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}
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static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx, std::initializer_list<enum ggml_op> ops, std::initializer_list<enum ggml_unary_op> unary_ops) {
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#ifndef NDEBUG
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const size_t num_unary = std::count(ops.begin(), ops.end(), GGML_OP_UNARY);
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@@ -3067,6 +3097,16 @@ static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx,
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}
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}
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if (ops.size() == 3 && ggml_can_fuse_subgraph(cgraph, node_idx, ops, { node_idx + 2 })) {
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const ggml_tensor * rope = cgraph->nodes[node_idx];
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const ggml_tensor * view = cgraph->nodes[node_idx + 1];
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const ggml_tensor * set_rows = cgraph->nodes[node_idx + 2];
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if (ggml_cuda_should_fuse_rope_set_rows(rope, view, set_rows)) {
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return true;
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}
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}
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if (!ggml_can_fuse(cgraph, node_idx, ops)) {
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return false;
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}
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@@ -3196,6 +3236,15 @@ static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx
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continue;
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}
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if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, {})) {
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ggml_tensor * rope = cgraph->nodes[i];
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ggml_tensor * set_rows = cgraph->nodes[i + 2];
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ggml_cuda_op_rope_fused(*cuda_ctx, rope, set_rows);
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i += 2;
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continue;
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}
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if (node->op == GGML_OP_ADD) {
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int n_fuse = 0;
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ggml_op ops[8];
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