CANN: add operator fusion support for ADD + RMS_NORM (#17512)

This commit implements operator fusion for ADD + RMS_NORM operations
in the CANN backend to reduce memory access overhead and improve
performance. The fusion is controlled by the GGML_CANN_OPERATOR_FUSION
environment variable (default: false).

Changes:
- Implement ggml_cann_op_add_rms_norm_fused() using ACLNN AddRmsNorm
- Add ggml_cann_can_fuse() to check fusion eligibility
- Integrate fusion logic into computation graph evaluation
- Add test cases for ADD + RMS_NORM fusion
- Update documentation with new environment variable

The fusion combines ADD and RMS_NORM into a single kernel call,
which is more efficient than executing them separately.
This commit is contained in:
Chenguang Li
2026-01-05 15:38:18 +08:00
committed by GitHub
parent 92ac1e016b
commit 67e3f6f601
5 changed files with 179 additions and 0 deletions
+44
View File
@@ -1888,6 +1888,7 @@ static bool ggml_cann_compute_forward(ggml_backend_cann_context & ctx, struct gg
break;
case GGML_OP_OUT_PROD:
ggml_cann_out_prod(ctx, dst);
break;
case GGML_OP_SSM_CONV:
ggml_cann_ssm_conv(ctx, dst);
break;
@@ -2077,6 +2078,40 @@ static void ggml_backend_cann_synchronize(ggml_backend_t backend) {
ACL_CHECK(aclrtSynchronizeStream(cann_ctx->stream()));
}
/**
* @brief Check if CANN backend can fuse the specified operation sequence
*
* This function determines whether an operation sequence starting from the specified node
* can be fused into an optimized operation in the CANN backend. Operation fusion can reduce
* memory access overhead and improve computational efficiency.
*
* @param cgraph Pointer to the computation graph
* @param node_idx Index of the starting node in the computation graph
* @param ops Sequence of operation types to check for fusion
* @return true if the operations can be fused
* @return false if the operations cannot be fused
*/
static bool ggml_cann_can_fuse(const struct ggml_cgraph * cgraph,
int node_idx,
std::initializer_list<enum ggml_op> ops) {
if (!ggml_can_fuse(cgraph, node_idx, ops)) {
return false;
}
// CANN backend supports fusing ADD + RMS_NORM operations
if ((ops.size() == 2) && ops.begin()[0] == GGML_OP_ADD && ops.begin()[1] == GGML_OP_RMS_NORM) {
ggml_tensor * add_node = cgraph->nodes[node_idx];
// TODO: support broadcast for ADD + RMS_NORM
if (add_node->src[0]->ne[0] != add_node->src[1]->ne[0] || add_node->src[0]->ne[1] != add_node->src[1]->ne[1] ||
add_node->src[0]->ne[2] != add_node->src[1]->ne[2] || add_node->src[0]->ne[3] != add_node->src[1]->ne[3]) {
return false;
}
return true;
}
return false;
}
/**
* @brief Evaluate the computation graph and optionally capture or execute it using CANN graph API.
*
@@ -2101,9 +2136,18 @@ static void evaluate_and_capture_cann_graph(ggml_backend_cann_context * cann_ctx
#endif // USE_ACL_GRAPH
// Only perform the graph execution if CANN graphs are not enabled, or we are capturing the graph.
// With the use of CANN graphs, the execution will be performed by the graph launch.
static bool opt_fusion = parse_bool(get_env("GGML_CANN_OPERATOR_FUSION").value_or(""));
if (!use_cann_graph || cann_graph_capture_required) {
for (int i = 0; i < cgraph->n_nodes; i++) {
ggml_tensor * node = cgraph->nodes[i];
if (opt_fusion) {
if (ggml_cann_can_fuse(cgraph, i, { GGML_OP_ADD, GGML_OP_RMS_NORM })) {
ggml_cann_op_add_rms_norm_fused(*cann_ctx, node, cgraph->nodes[i + 1]);
i++;
continue;
}
}
if (ggml_is_empty(node) || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE ||
node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE || node->op == GGML_OP_NONE) {