DarthAffe/stable-diffusion.cpp
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feat: support for cross-device row split (#1735)

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Piotr Wilkin (ilintar) authored and GitHub committed 2026-07-04 16:31:18 +08:00
1 parent 7bcd189639
commit 68f3d6df9f
12 files changed
+322 -21
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src/model_manager.h
+9 -1
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@@ -36,6 +36,7 @@ private:
ResidencyMode residency_mode = ResidencyMode::ParamBackend;
ggml_backend_t compute_backend = nullptr;
ggml_backend_t params_backend = nullptr;
bool allow_split_buffer = false;
bool metadata_validated = false;
int active_prepare_count = 0;
@@ -63,6 +64,8 @@ private:
std::map<std::string, TensorState*> tensor_states_by_name_;
std::vector<std::unique_ptr<ParamsStorageBlock>> params_storage_blocks_;
std::vector<std::unique_ptr<ComputeStagingBlock>> compute_staging_blocks_;
std::map<ggml_backend_t, ggml_backend_buffer_type_t> split_buffer_types_;
bool warned_split_lora_skip_ = false;
std::set<std::string> common_ignore_tensors_;
std::vector<LoraSpec> loras_;
SDVersion lora_version_ = VERSION_COUNT;
@@ -91,6 +94,7 @@ private:
bool stage_tensors_to_compute_backend(const std::vector<TensorState*>& states);
ggml_backend_buffer_type_t params_buffer_type_for(const TensorState& state) const;
ggml_backend_buffer_type_t split_buffer_type_for(const TensorState& state) const;
void release_compute_staging_blocks(bool force = false,
const std::unordered_set<TensorState*>* target_states = nullptr);
void release_params_storage_blocks(bool force = false,
@@ -114,6 +118,9 @@ public:
void set_writable_mmap(bool writable_mmap) { writable_mmap_ = writable_mmap; }
void set_common_ignore_tensors(std::set<std::string> ignore_tensors);
void set_loras(std::vector<LoraSpec> loras, SDVersion version);
void set_split_buffer_type(ggml_backend_t compute_backend, ggml_backend_buffer_type_t split_buft);
static bool tensor_shape_supports_split_buffer(const ggml_tensor* tensor);
std::set<std::string> tensor_names() const;
@@ -122,7 +129,8 @@ public:
ResidencyMode residency_mode,
ggml_backend_t compute_backend,
ggml_backend_t params_backend,
size_t* registered_tensor_size = nullptr);
size_t* registered_tensor_size = nullptr,
bool allow_split_buffer = false);
template <typename Runner>
bool register_runner_params(const std::string& desc,