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
This commit is contained in:
Aman Gupta
2025-11-13 08:50:01 +08:00
committed by GitHub
parent 07751f8d44
commit a90eb94ca9
4 changed files with 215 additions and 61 deletions
+49
View File
@@ -2992,6 +2992,36 @@ static void update_cuda_graph_executable(ggml_backend_cuda_context * cuda_ctx) {
}
#endif
static bool ggml_cuda_should_fuse_rope_set_rows(const ggml_tensor * rope,
const ggml_tensor * view,
const ggml_tensor * set_rows) {
// ne3 not tested
if (rope->src[0]->ne[3] != 1) {
return false;
}
if (set_rows->type != GGML_TYPE_F32 && set_rows->type != GGML_TYPE_F16) {
return false;
}
if (set_rows->src[1]->type != GGML_TYPE_I64) {
return false;
}
// The view should flatten two dims of rope into one dim
if (!ggml_is_contiguous(view) || view->ne[0] != rope->ne[0] * rope->ne[1]) {
return false;
}
// Only norm/neox shaders have the fusion code
const int mode = ((const int32_t *) rope->op_params)[2];
if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) {
return false;
}
return true;
}
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) {
#ifndef NDEBUG
const size_t num_unary = std::count(ops.begin(), ops.end(), GGML_OP_UNARY);
@@ -3067,6 +3097,16 @@ static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx,
}
}
if (ops.size() == 3 && ggml_can_fuse_subgraph(cgraph, node_idx, ops, { node_idx + 2 })) {
const ggml_tensor * rope = cgraph->nodes[node_idx];
const ggml_tensor * view = cgraph->nodes[node_idx + 1];
const ggml_tensor * set_rows = cgraph->nodes[node_idx + 2];
if (ggml_cuda_should_fuse_rope_set_rows(rope, view, set_rows)) {
return true;
}
}
if (!ggml_can_fuse(cgraph, node_idx, ops)) {
return false;
}
@@ -3196,6 +3236,15 @@ static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx
continue;
}
if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, {})) {
ggml_tensor * rope = cgraph->nodes[i];
ggml_tensor * set_rows = cgraph->nodes[i + 2];
ggml_cuda_op_rope_fused(*cuda_ctx, rope, set_rows);
i += 2;
continue;
}
if (node->op == GGML_OP_ADD) {
int n_fuse = 0;
ggml_op ops[8];