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With mechanism to fall back if graph capture fails

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This commit is contained in:
Alan Gray 2024-04-30 06:19:51 -07:00
parent d44e0fb22c
commit eb9f15fb6f
2 changed files with 30 additions and 6 deletions
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35
ggml-cuda.cu
View File

@ -48,11 +48,20 @@
static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size");
[[noreturn]]
static bool disable_cuda_graphs_due_to_failed_capture = false;
void ggml_cuda_error(const char * stmt, const char * func, const char * file, int line, const char * msg) {
int id = -1; // in case cudaGetDevice fails
cudaGetDevice(&id);
if(strcmp(msg,"operation not permitted when stream is capturing")==0 ||
strcmp(msg,"operation failed due to a previous error during capture")==0) {
// CUDA graph capture has failed, but we can fall back to regular stream-based CUDA
// so mark as failed, clear the error and return.
disable_cuda_graphs_due_to_failed_capture = true;
cudaGetLastError();
return;
}
fprintf(stderr, "CUDA error: %s\n", msg);
fprintf(stderr, " current device: %d, in function %s at %s:%d\n", id, func, file, line);
fprintf(stderr, " %s\n", stmt);
@ -2428,6 +2437,7 @@ struct ggml_cuda_graph {
cudaKernelNodeParams params[MAX_NODES_IN_CUDA_GRAPH];
bool disable_due_to_gpu_arch = false;
bool disable_due_to_too_many_updates = false;
bool disable_due_to_failed_graph_capture = false;
int number_consecutive_updates = 0;
ggml_graph_node_properties ggml_graph_properties[MAX_NODES_IN_CUDA_GRAPH];
};
@ -2481,9 +2491,11 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
}
}
// Disable CUDA graphs in presence of env var, old GPU or use-case which is changing too rapidly.
// Disable CUDA graphs in presence of env var, old GPU, use-case which is changing too rapidly,
// or previous graph capture failure.
// Also disable for multi-gpu for now. TO DO investigate
if(disable_cuda_graphs || cuda_graph.disable_due_to_gpu_arch || cuda_graph.disable_due_to_too_many_updates ||
if(disable_cuda_graphs || cuda_graph.disable_due_to_gpu_arch ||
cuda_graph.disable_due_to_too_many_updates || cuda_graph.disable_due_to_failed_graph_capture ||
ggml_backend_cuda_get_device_count() > 1){
use_cuda_graph = false;
}
@ -2540,11 +2552,16 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
bool use_cuda_graph = false;
bool cuda_graph_update_required = false;
#endif // USE_CUDA_GRAPH
bool graph_evaluated_or_captured = false;
while(!graph_evaluated_or_captured) {
// Temporarily avoid indenting here (and below the following if) to make code review easier
// Only perform the graph execution if CUDA graphs are not enabled, or we are capturing the graph.
// With the use of CUDA graphs, the execution will be performed by the graph launch.
if(!use_cuda_graph || cuda_graph_update_required) {
//temporarily avoid indenting here to make code review easier
for (int i = 0; i < cgraph->n_nodes; i++) {
ggml_tensor * node = cgraph->nodes[i];
@ -2572,6 +2589,14 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
#ifdef USE_CUDA_GRAPH
if(use_cuda_graph && (cuda_graph_update_required)) { // End CUDA graph capture
CUDA_CHECK(cudaStreamEndCapture(cuda_ctx->stream(), &cuda_graph.graph));
if(disable_cuda_graphs_due_to_failed_capture) {
use_cuda_graph = false;
cuda_graph.disable_due_to_failed_graph_capture = true;
}
}
else {
graph_evaluated_or_captured = true;
}
}
if(use_cuda_graph){

1
ggml-cuda/common.cuh
View File

@ -172,7 +172,6 @@
#define GGML_CUDA_MAX_STREAMS 8
[[noreturn]]
void ggml_cuda_error(const char * stmt, const char * func, const char * file, int line, const char * msg);
#define CUDA_CHECK_GEN(err, success, error_fn) \