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Added more comprehensive graph node checking

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This commit is contained in:
Alan Gray 2024-04-30 03:29:35 -07:00
parent 9c5786161d
commit d44e0fb22c
1 changed files with 59 additions and 9 deletions
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68
ggml-cuda.cu
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@ -2409,6 +2409,14 @@ GGML_CALL static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
#define USE_CUDA_GRAPH
#endif
struct ggml_graph_node_properties {
void * node_address;
int node_op;
int64_t ne[GGML_MAX_DIMS];
size_t nb[GGML_MAX_DIMS];
void * src_address[GGML_MAX_SRC];
};
#ifdef USE_CUDA_GRAPH
#define MAX_NODES_IN_CUDA_GRAPH 10000
struct ggml_cuda_graph {
@ -2416,15 +2424,42 @@ struct ggml_cuda_graph {
cudaGraph_t graph = nullptr;
cudaGraphExec_t instance = nullptr;
size_t num_nodes = 0;
int softmax_ne0 = 0;
cudaGraphNode_t nodes[MAX_NODES_IN_CUDA_GRAPH];
cudaKernelNodeParams params[MAX_NODES_IN_CUDA_GRAPH];
bool disable_due_to_gpu_arch = false;
bool disable_due_to_too_many_updates = false;
int number_consecutive_updates = 0;
ggml_graph_node_properties ggml_graph_properties[MAX_NODES_IN_CUDA_GRAPH];
};
#endif
const bool disable_cuda_graphs = (getenv("LLAMACPP_DISABLE_CUDA_GRAPHS") != nullptr);
GGML_CALL static void set_ggml_graph_node_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) {
graph_node_properties->node_address = node;
graph_node_properties->node_op = node->op;
for(int i=0; i<GGML_MAX_DIMS; i++) {
graph_node_properties->ne[i] = node->ne[i];
graph_node_properties->nb[i] = node->nb[i];
}
for(int i=0; i<GGML_MAX_SRC; i++) {
graph_node_properties->src_address[i] = node->src[i];
}
}
GGML_CALL static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) {
if(node != graph_node_properties->node_address) return false;
if(node->op != graph_node_properties->node_op) return false;
for(int i=0; i<GGML_MAX_DIMS; i++) {
if(node->ne[i] != graph_node_properties->ne[i]) return false;
if(node->nb[i] != graph_node_properties->nb[i]) return false;
}
for(int i=0; i<GGML_MAX_SRC; i++) {
if(node->src[i] != graph_node_properties->src_address[i]) return false;
}
return true;
}
GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
@ -2446,9 +2481,10 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
}
}
// Disable CUDA graphs in presence of env var or old GPU.
// Disable CUDA graphs in presence of env var, old GPU or use-case which is changing too rapidly.
// Also disable for multi-gpu for now. TO DO investigate
if(disable_cuda_graphs || cuda_graph.disable_due_to_gpu_arch || ggml_backend_cuda_get_device_count() > 1){
if(disable_cuda_graphs || cuda_graph.disable_due_to_gpu_arch || cuda_graph.disable_due_to_too_many_updates ||
ggml_backend_cuda_get_device_count() > 1){
use_cuda_graph = false;
}
@ -2456,20 +2492,25 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
if(cuda_graph.instance == nullptr) cuda_graph_update_required=true;
// Loop over nodes in GGML graph to determine if CUDA graph update is required
// and store properties to allow this comparison for the next token
for (int i = 0; i < cgraph->n_nodes; i++) {
bool has_matching_properties = true;
if(!cuda_graph_update_required) {
has_matching_properties = ggml_graph_node_has_matching_properties(cgraph->nodes[i], &cuda_graph.ggml_graph_properties[i]);
}
if(!has_matching_properties) cuda_graph_update_required = true;
set_ggml_graph_node_properties(cgraph->nodes[i], &cuda_graph.ggml_graph_properties[i]);
}
// Loop over nodes in GGML graph to obtain info needed for CUDA graph
int k=0;
for (int i = 0; i < cgraph->n_nodes; i++) {
ggml_tensor * node = cgraph->nodes[i];
// Identify if the graph needs to be updated for this token due to the number of elements changing
// (identified by inspecting soft max op parameters)
if(node->op == GGML_OP_SOFT_MAX) {
if(node->src[1]->ne[1] > 1){
use_cuda_graph = false; // disable CUDA graphs for batch size > 1 for now. TO DO investigate
}
if(node->src[0]->ne[0] != cuda_graph.softmax_ne0) {
cuda_graph_update_required = true;
cuda_graph.softmax_ne0 = node->src[0]->ne[0];
}
}
if(node->op == GGML_OP_CPY) {
// store the copy op parameter which changes with each token.
@ -2480,6 +2521,15 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
}
}
}
// Disable CUDA graphs (from the next token) if the use-case is demanding too many consecutive graph updates.
if(cuda_graph_update_required) {
cuda_graph.number_consecutive_updates++;
}
else {
cuda_graph.number_consecutive_updates = 0;
}
if (cuda_graph.number_consecutive_updates >= 4) cuda_graph.disable_due_to_too_many_updates = true;
}
if(use_cuda_graph && cuda_graph_update_required) { // Start CUDA graph capture