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ggml-backend : fix async copy from CPU (#8897)
* ggml-backend : fix async copy from CPU * cuda : more reliable async copy, fix stream used when the devices are the same
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@ -351,15 +351,10 @@ void ggml_backend_tensor_copy_async(ggml_backend_t backend_src, ggml_backend_t b
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}
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}
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// an async copy would normally happen after all the queued operations on both backends are completed
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// an async copy would normally happen after all the queued operations on both backends are completed
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// sync src, set_async dst
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// to simulate the same behavior, we need to synchronize both backends first, and do a blocking copy
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if (ggml_backend_buffer_is_host(src->buffer)) {
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ggml_backend_synchronize(backend_src);
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ggml_backend_synchronize(backend_src);
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ggml_backend_tensor_set_async(backend_dst, dst, src->data, 0, ggml_nbytes(src));
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} else {
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ggml_backend_synchronize(backend_src);
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ggml_backend_tensor_copy(src, dst);
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ggml_backend_synchronize(backend_dst);
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ggml_backend_synchronize(backend_dst);
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}
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ggml_backend_tensor_copy(src, dst);
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}
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}
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// events
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// events
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@ -1782,7 +1777,17 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
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} else {
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} else {
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ggml_backend_synchronize(split_backend);
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ggml_backend_synchronize(split_backend);
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}
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}
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ggml_backend_tensor_copy_async(input_backend, split_backend, input, input_cpy);
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// try async copy, but if not possible, we can still use a sync copy without synchronizing the dst backend, since we handle the synchronization here with multiple copies and events
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// TODO: add public function to facilitate this, since applications do not have direct access to the backend interface
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if (!split_backend->iface.cpy_tensor_async || !split_backend->iface.cpy_tensor_async(input_backend, split_backend, input, input_cpy)) {
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ggml_backend_synchronize(input_backend);
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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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ggml_backend_synchronize(split_backend);
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}
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ggml_backend_tensor_copy(input, input_cpy);
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}
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}
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}
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}
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}
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@ -2358,33 +2358,35 @@ GGML_CALL static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend,
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}
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}
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GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const ggml_tensor * src, ggml_tensor * dst) {
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GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const ggml_tensor * src, ggml_tensor * dst) {
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GGML_ASSERT(ggml_backend_is_cuda(backend_src) || ggml_backend_is_cuda(backend_dst));
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ggml_backend_buffer_t buf_src = src->view_src ? src->view_src->buffer : src->buffer;
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ggml_backend_buffer_t buf_src = src->view_src ? src->view_src->buffer : src->buffer;
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ggml_backend_buffer_t buf_dst = dst->view_src ? dst->view_src->buffer : dst->buffer;
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ggml_backend_buffer_t buf_dst = dst->view_src ? dst->view_src->buffer : dst->buffer;
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if (!ggml_backend_buffer_is_cuda(src->buffer)) {
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if (!ggml_backend_is_cuda(backend_src) || !ggml_backend_is_cuda(backend_dst)) {
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return false;
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return false;
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}
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}
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if (!ggml_backend_buffer_is_cuda(dst->buffer)) {
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if (!ggml_backend_buffer_is_cuda(src->buffer) || !ggml_backend_buffer_is_cuda(dst->buffer)) {
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return false;
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return false;
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}
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}
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// device -> device
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// device -> device copy
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ggml_backend_cuda_context * cuda_ctx_src = (ggml_backend_cuda_context *)backend_src->context;
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ggml_backend_cuda_context * cuda_ctx_src = (ggml_backend_cuda_context *)backend_src->context;
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ggml_backend_cuda_context * cuda_ctx_dst = (ggml_backend_cuda_context *)backend_dst->context;
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ggml_backend_cuda_context * cuda_ctx_dst = (ggml_backend_cuda_context *)backend_dst->context;
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if (backend_src != backend_dst) {
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ggml_backend_cuda_buffer_context * buf_ctx_src = (ggml_backend_cuda_buffer_context *)buf_src->context;
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ggml_backend_cuda_buffer_context * buf_ctx_src = (ggml_backend_cuda_buffer_context *)buf_src->context;
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ggml_backend_cuda_buffer_context * buf_ctx_dst = (ggml_backend_cuda_buffer_context *)buf_dst->context;
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ggml_backend_cuda_buffer_context * buf_ctx_dst = (ggml_backend_cuda_buffer_context *)buf_dst->context;
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GGML_ASSERT(cuda_ctx_src->device == buf_ctx_src->device);
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if (cuda_ctx_src->device != buf_ctx_src->device || cuda_ctx_dst->device != buf_ctx_dst->device) {
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GGML_ASSERT(cuda_ctx_dst->device == buf_ctx_dst->device);
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#ifndef NDEBUG
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GGML_CUDA_LOG_WARN("%s: backend and buffer devices do not match\n", __func__);
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#endif
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return false;
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}
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if (backend_src != backend_dst) {
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// copy on src stream
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// copy on src stream
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if (cuda_ctx_src->device == cuda_ctx_dst->device) {
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if (cuda_ctx_src->device == cuda_ctx_dst->device) {
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CUDA_CHECK(cudaMemcpyAsync(dst->data, src->data, ggml_nbytes(dst), cudaMemcpyDeviceToDevice, cuda_ctx_dst->stream()));
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CUDA_CHECK(cudaMemcpyAsync(dst->data, src->data, ggml_nbytes(dst), cudaMemcpyDeviceToDevice, cuda_ctx_src->stream()));
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} else {
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} else {
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#ifdef GGML_CUDA_NO_PEER_COPY
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#ifdef GGML_CUDA_NO_PEER_COPY
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return false;
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return false;
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@ -2393,7 +2395,7 @@ GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_
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#endif
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#endif
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}
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}
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// record event on src stream
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// record event on src stream after the copy
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if (!cuda_ctx_src->copy_event) {
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if (!cuda_ctx_src->copy_event) {
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ggml_cuda_set_device(cuda_ctx_src->device);
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ggml_cuda_set_device(cuda_ctx_src->device);
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CUDA_CHECK(cudaEventCreateWithFlags(&cuda_ctx_src->copy_event, cudaEventDisableTiming));
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CUDA_CHECK(cudaEventCreateWithFlags(&cuda_ctx_src->copy_event, cudaEventDisableTiming));
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@ -2405,7 +2407,7 @@ GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_
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CUDA_CHECK(cudaStreamWaitEvent(cuda_ctx_dst->stream(), cuda_ctx_src->copy_event, 0));
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CUDA_CHECK(cudaStreamWaitEvent(cuda_ctx_dst->stream(), cuda_ctx_src->copy_event, 0));
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} else {
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} else {
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// src and dst are on the same backend
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// src and dst are on the same backend
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CUDA_CHECK(cudaMemcpyAsync(dst->data, src->data, ggml_nbytes(dst), cudaMemcpyDeviceToDevice, cuda_ctx_dst->stream()));
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CUDA_CHECK(cudaMemcpyAsync(dst->data, src->data, ggml_nbytes(dst), cudaMemcpyDeviceToDevice, cuda_ctx_src->stream()));
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}
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}
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return true;
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return true;
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}
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}
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