sched : reintroduce less synchronizations during split compute (#20793)
* CUDA: Improve performance via less synchronizations between token (#17795) * Adds CPU-to-CUDA copy capability to ggml_backend_cuda_cpy_tensor_async() * Adds function to relax sync requirements between input copies on supported backends (CUDA for now) * Exchanges synchronous copy with async copy function. * Adds macro guards to allow compilation in non-CUDA builds * Reworked backend detection in ggml-backend.cpp to avoid linking conflicts * Relax requirement of checks in async CUDA copies from backend and buffer type to just buffer type, to avoid linking issues * Minor cleanup * Makes opt-in to relax use of explicit syncs more general. Backends like vulkan which require a synchronization between HtoD copies and graph execution could also adopt this change now. * Reintroduces stricter check for CPU->CUDA backend async copy via GGML_DEVICE_TYPE_CPU. * Corrects initialization of ggml_backend_sync_mode in ggml_backend_sched_split initialization * Simplifies synchronizations to adhere to `saaasg` pattern. * Apply suggestion from @ggerganov (src->buffer to buf_src) Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Apply suggestion from @ggerganov (src->buffer to buf_src) v2 Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Apply suggestions from @johannesgaessler code review Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * Adds single-GPU synchronizations to multi-GPU settings to fix hip backend pipeline parallel bugs. * Scheduler Hardening: Exclude hip/MUSA from copy_from_host CPU split -> GPU split optimization * Scheduler Hardening: Re-adding original additional synchronizations for non-async backends * Adds disclaimer to hip/musa exclusion of copy_from_host. Highlights that it is out of precaution, but that no perf-impact is visible, and that it can be revisited separately anytime. --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
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co-authored by
Georgi Gerganov
Johannes Gäßler
parent
5d8ccdf9d1
commit
3fc4e10527
@@ -1551,6 +1551,8 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
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int split_backend_id = split->backend_id;
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ggml_backend_t split_backend = sched->backends[split_backend_id];
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ggml_backend_synchronize(split_backend);
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// copy the input tensors to the split backend
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for (int input_id = 0; input_id < split->n_inputs; input_id++) {
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ggml_backend_t input_backend = ggml_backend_sched_get_tensor_backend(sched, split->inputs[input_id]);
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@@ -1561,15 +1563,15 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
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// inputs from the user must be copied immediately to prevent the user overwriting the data before the copy is done
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if (sched->events[split_backend_id][sched->cur_copy] != NULL) {
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ggml_backend_event_synchronize(sched->events[split_backend_id][sched->cur_copy]);
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} else {
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} else if (!split_backend->iface.cpy_tensor_async) {
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ggml_backend_synchronize(split_backend);
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}
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ggml_backend_tensor_copy(input, input_cpy);
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ggml_backend_tensor_copy_async(input_backend, split_backend, input, input_cpy);
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} else {
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// wait for the split backend to finish using the input before overwriting it
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if (sched->events[split_backend_id][sched->cur_copy] != NULL) {
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ggml_backend_event_wait(split_backend, sched->events[split_backend_id][sched->cur_copy]);
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} else {
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} else if (!split_backend->iface.cpy_tensor_async) {
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ggml_backend_synchronize(split_backend);
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}
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@@ -1674,6 +1676,8 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
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}
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}
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ggml_backend_synchronize(split_backend);
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if (!sched->callback_eval) {
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enum ggml_status ec = ggml_backend_graph_compute_async(split_backend, &split->graph);
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if (ec != GGML_STATUS_SUCCESS) {
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