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llama.cpp/ggml/src/ggml-openvino/ggml-openvino.cpp

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#include "ggml-openvino.h"
#include <cstdint>
#include <mutex>
#include <openvino/openvino.hpp>
#include <set>
#include <string>
#include <vector>
#include "ggml-backend-impl.h"
#include "ggml-backend.h"
#include "ggml-impl.h"
#include "ggml-openvino/utils.h"
#include "ggml.h"
#define GGML_OPENVINO_MAX_STREAMS 8
struct ggml_backend_openvino_context {
int device; // the device ID currently in use
std::string name; // context Name
std::string description; // context description
// OpenVINO core components
ov::Core core; // OpenVINO core interface
std::shared_ptr<ov::CompiledModel> model; // compiled Model
ov::InferRequest infer_request; // inference Request
// OpenVINO Multi-stream support
static const int MAX_STREAMS = 8; // define the maximum number of flows
std::vector<ov::InferRequest> streams; // used to support multi-stream reasoning
int current_stream; // the currently active stream index
// state Management
bool is_initialized; // initialize
ggml_backend_openvino_context()
: device(0), name("OpenVINO"), description("OpenVINO Backend Context"),
current_stream(0), is_initialized(false) {}
};
static void ggml_backend_openvino_free(ggml_backend_t backend) {
ggml_backend_openvino_context * ctx = (ggml_backend_openvino_context *)backend->context;
delete ctx;
delete backend;
}
static const char * ggml_backend_openvino_get_name(ggml_backend_t backend) {
return GGML_OPENVINO_NAME;
GGML_UNUSED(backend);
}
static enum ggml_status
ggml_backend_openvino_graph_compute(ggml_backend_t backend, struct ggml_cgraph *cgraph) {
openvino_frontend_compute(backend, cgraph);
return GGML_STATUS_SUCCESS;
}
static const ggml_backend_i ggml_backend_openvino_interface = {
/* .get_name = */ ggml_backend_openvino_get_name,
/* .free = */ ggml_backend_openvino_free,
/* .set_tensor_async = */ NULL,
/* .get_tensor_async = */ NULL,
/* .cpy_tensor_async = */ NULL,
/* .synchronize = */ NULL,
/* .graph_plan_create = */ NULL,
/* .graph_plan_free = */ NULL,
/* .graph_plan_update = */ NULL,
/* .graph_plan_compute = */ NULL,
/* .graph_compute = */ ggml_backend_openvino_graph_compute,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
};
int ggml_backend_openvino_get_device_count() {
return ggml_openvino_info().device_count;
}
static ggml_guid_t ggml_backend_openvino_guid(void) {
static ggml_guid guid = { 0x12, 0xa8, 0xae, 0xf4, 0xc0, 0x1e, 0x61, 0x97, 0x8f, 0xeb, 0x33, 0x04, 0xa1, 0x33, 0x51, 0x2d };
return &guid;
}
// backend API
GGML_BACKEND_API ggml_backend_t ggml_backend_openvino_init(int device) {
if (device < 0 || device >= ggml_backend_openvino_get_device_count()) {
GGML_LOG_ERROR("%s: invalid device %d\n", __func__, device);
return nullptr;
}
ggml_backend_openvino_context * ctx = new ggml_backend_openvino_context;
if (ctx == nullptr) {
GGML_LOG_ERROR("%s: failed to allocate context\n", __func__);
return nullptr;
}
ggml_backend_t openvino_backend = new ggml_backend {
/* .guid = */ ggml_backend_openvino_guid(),
/* .interface = */ ggml_backend_openvino_interface,
/* .device = */ ggml_backend_reg_dev_get(ggml_backend_openvino_reg(), device),
/* .context = */ ctx,
};
return openvino_backend;
}
GGML_BACKEND_API bool ggml_backend_is_openvino(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_openvino_guid());
}
// device buffer
GGML_BACKEND_API ggml_backend_buffer_type_t ggml_backend_openvino_buffer_type(int device) {
GGML_ASSERT(device >= 0);
return ggml_backend_cpu_buffer_type();
GGML_UNUSED(device);
}
// split tensor buffer that splits matrices by rows across multiple devices
GGML_BACKEND_API ggml_backend_buffer_type_t ggml_backend_openvino_split_buffer_type(const float * tensor_split) {
GGML_ASSERT(tensor_split != nullptr);
return nullptr;
}
// pinned host buffer for use with the CPU backend for faster copies between CPU
// and GPU
GGML_BACKEND_API ggml_backend_buffer_type_t ggml_backend_openvino_host_buffer_type(void) {
return nullptr;
}
struct ggml_backend_openvino_buffer_type_context {
int device;
std::string name;
};
static const char * ggml_backend_openvino_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
ggml_backend_openvino_buffer_type_context * ctx = (ggml_backend_openvino_buffer_type_context *)buft->context;
return ctx->name.c_str();
}
static bool ggml_backend_buft_is_openvino(ggml_backend_buffer_type_t buft) {
return buft->iface.get_name == ggml_backend_openvino_buffer_type_get_name;
}
static const char * ggml_backend_openvino_split_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
return GGML_OPENVINO_NAME "_Split";
GGML_UNUSED(buft);
}
static bool ggml_backend_buft_is_openvino_split(ggml_backend_buffer_type_t buft) {
return buft->iface.get_name == ggml_backend_openvino_split_buffer_type_get_name;
}
struct ggml_backend_openvino_device_context {
int device;
std::string name;
std::string description;
};
static const char * ggml_backend_openvino_device_get_name(ggml_backend_dev_t dev) {
ggml_backend_openvino_device_context * ctx = (ggml_backend_openvino_device_context *)dev->context;
return ctx->name.c_str();
}
static const char * ggml_backend_openvino_device_get_description(ggml_backend_dev_t dev) {
ggml_backend_openvino_device_context * ctx = (ggml_backend_openvino_device_context *)dev->context;
return ctx->description.c_str();
}
// TODO
static void ggml_backend_openvino_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) {
GGML_ASSERT(dev->context != nullptr);
GGML_ASSERT(free != nullptr);
GGML_ASSERT(total != nullptr);
ggml_backend_openvino_device_context * ctx = (ggml_backend_openvino_device_context *)dev->context;
GGML_ASSERT(ctx->device >= 0);
// ggml_openvino_set_device(ctx->device);
*total = 1;
*free = 1;
}
static enum ggml_backend_dev_type ggml_backend_openvino_device_get_type(ggml_backend_dev_t dev) {
GGML_UNUSED(dev);
return GGML_BACKEND_DEVICE_TYPE_GPU;
}
static void ggml_backend_openvino_device_get_props(ggml_backend_dev_t dev, ggml_backend_dev_props * props) {
props->name = ggml_backend_openvino_device_get_name(dev);
props->description = ggml_backend_openvino_device_get_description(dev);
props->type = ggml_backend_openvino_device_get_type(dev);
ggml_backend_openvino_device_get_memory(dev, &props->memory_free, &props->memory_total);
bool host_buffer = getenv("GGML_OPENVINO_NO_PINNED") == nullptr;
#ifdef GGML_OPENVINO_NO_PEER_COPY
bool events = false;
#else
bool events = true;
#endif
props->caps = {
/* .async = */ true,
/* .host_buffer = */ host_buffer,
/* .buffer_from_host_ptr = */ false,
/* .events = */ events,
};
}
static ggml_backend_t ggml_backend_openvino_device_init(ggml_backend_dev_t dev, const char * params) {
GGML_UNUSED(params);
ggml_backend_openvino_device_context * ctx = (ggml_backend_openvino_device_context *)dev->context;
return ggml_backend_openvino_init(ctx->device);
}
static ggml_backend_buffer_type_t ggml_backend_openvino_device_get_buffer_type(ggml_backend_dev_t dev) {
ggml_backend_openvino_device_context * ctx = (ggml_backend_openvino_device_context *)dev->context;
return ggml_backend_openvino_buffer_type(ctx->device);
}
static ggml_backend_buffer_type_t ggml_backend_openvino_device_get_host_buffer_type(ggml_backend_dev_t dev) {
GGML_UNUSED(dev);
return ggml_backend_openvino_host_buffer_type();
}
static ggml_backend_buffer_t ggml_backend_openvino_device_buffer_from_ptr(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) {
GGML_UNUSED(dev);
GGML_UNUSED(ptr);
GGML_UNUSED(size);
GGML_UNUSED(max_tensor_size);
return nullptr;
}
static ggml_backend_buffer_t ggml_backend_openvino_device_buffer_from_host_ptr(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) {
GGML_UNUSED(dev);
GGML_UNUSED(ptr);
GGML_UNUSED(size);
GGML_UNUSED(max_tensor_size);
return nullptr;
}
static bool is_op_unsupported_case(const ggml_tensor* op) {
if (op->op == GGML_OP_SOFT_MAX) {
if (op->src[2] != nullptr) {
GGML_LOG_WARN("OpenVINO backend does not support SOFT_MAX with sinks\n");
return true;
}
float scale = 1.0f;
float max_bias = 0.0f;
const auto* op_params = op->op_params;
memcpy(&scale, (const float*) op_params + 0, sizeof(float));
memcpy(&max_bias, (const float*) op_params + 1, sizeof(float));
const uint32_t h = op->src[0]->ne[2];
const uint32_t n_head = op->src[0]->ne[0];
const uint32_t n_head_log2 = 1u << (uint32_t) floor(log2(n_head));
const float m0 = powf(2.0f, -(max_bias) / n_head_log2);
const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
const float slope =
(max_bias > 0.0f) ? h < n_head_log2 ? powf(m0, h + 1) : powf(m1, 2 * (h - n_head_log2) + 1) : 1.0f;
if (slope != 1.0f) {
GGML_LOG_WARN("OpenVINO backend does not support SOFT_MAX with slope != 1.0f\n");
return true;
}
}
if (op->op == GGML_OP_PERMUTE) {
if (op->type == GGML_TYPE_BF16) {
// err msg: [GPU] Could not find a suitable kernel for transpose
GGML_LOG_WARN("OpenVINO backend does not support PERMUTE with BF16 type\n");
return true;
}
}
if (op->op == GGML_OP_CPY) {
if (op->src[1] != op) {
GGML_LOG_WARN("OpenVINO backend only supports CPY that is a cast\n");
return true;
}
}
if (op->op == GGML_OP_MUL_MAT) {
if (op->src[0]->type == GGML_TYPE_F16 && op->src[1]->type == GGML_TYPE_F16) {
// Has accuracy issue, try enabling this and see `test-backend-ops -o "MUL_MAT"`
GGML_LOG_WARN("OpenVINO backend does not support MUL_MAT with two F16 tensors\n");
return true;
}
}
if (op->op == GGML_OP_ROPE) {
const int32_t* op_params = op->op_params;
const int n_dims = op_params[1];
const int mode = op_params[2];
if (mode == GGML_ROPE_TYPE_MROPE || mode == GGML_ROPE_TYPE_VISION) {
GGML_LOG_WARN("OpenVINO backend does not support ROPE with mode %d\n", mode);
return true;
}
if (n_dims != 0.0f && n_dims != op->src[0]->ne[0]) {
GGML_LOG_WARN("OpenVINO backend does not support ROPE with n_dims %d != src[0]->ne[0] %ld\n",
n_dims,
op->src[0]->ne[0]);
return true;
}
if (op->type != GGML_TYPE_F32) {
GGML_LOG_WARN("OpenVINO backend does not support ROPE with type %s\n", ggml_type_name(op->type));
return true;
}
float freq_scale;
memcpy(&freq_scale, op_params + 6, sizeof(float));
if (freq_scale != 0.0f && freq_scale != 1.0f) {
GGML_LOG_WARN("OpenVINO backend does not support ROPE with freq_scale %f != 1.0f\n", freq_scale);
return true;
}
float ext_factor;
memcpy(&ext_factor, op_params + 7, sizeof(float));
if (ext_factor != 0.0f) {
GGML_LOG_WARN("OpenVINO backend does not support ROPE with ext_factor %f != 0.0f\n", ext_factor);
return true;
}
if (op->src[0]->op == GGML_OP_VIEW) {
if (op->src[0]->view_src->ne[1] != op->src[0]->ne[2]) {
GGML_LOG_WARN(
"OpenVINO backend does not support ROPE with src[0]->view_src->ne[1] %ld != src[0]->ne[2] %ld\n",
op->src[0]->view_src->ne[1],
op->src[0]->ne[2]);
return true;
}
}
}
return false;
}
static bool ggml_backend_openvino_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor* op) {
GGML_ASSERT(dev->reg != nullptr);
static std::set<ggml_type> supported_types{GGML_TYPE_F32,
GGML_TYPE_F16,
GGML_TYPE_BF16,
GGML_TYPE_I64,
GGML_TYPE_I32,
GGML_TYPE_Q4_0,
GGML_TYPE_Q4_1,
GGML_TYPE_Q4_K,
GGML_TYPE_Q8_0,
GGML_TYPE_Q6_K};
std::string device = std::string(getenv("GGML_OPENVINO_DEVICE"));
bool is_npu = device == "NPU";
if (is_npu) {
// NPU has poor support for asymmetric quantization
supported_types.erase(GGML_TYPE_Q4_1);
supported_types.erase(GGML_TYPE_Q4_K);
}
static const std::set<ggml_op> supported_ops{GGML_OP_NONE,
GGML_OP_ADD,
GGML_OP_MUL,
GGML_OP_MUL_MAT,
GGML_OP_VIEW,
GGML_OP_CONT,
GGML_OP_RESHAPE,
GGML_OP_PERMUTE,
GGML_OP_TRANSPOSE,
GGML_OP_GET_ROWS,
GGML_OP_ROPE,
GGML_OP_RMS_NORM,
GGML_OP_SCALE,
GGML_OP_SOFT_MAX,
GGML_OP_SET_ROWS,
GGML_OP_FLASH_ATTN_EXT,
GGML_OP_CPY};
static const std::set<ggml_unary_op> supported_unary_ops{
GGML_UNARY_OP_SILU,
};
static const std::set<ggml_glu_op> supported_glu_ops{
GGML_GLU_OP_SWIGLU,
};
switch (op->op) {
case GGML_OP_UNARY: {
auto supported = supported_unary_ops.find(ggml_get_unary_op(op)) != supported_unary_ops.end();
if (!supported) {
GGML_LOG_WARN("OpenVINO backend does not support unary op %s\n", ggml_unary_op_name(ggml_get_unary_op(op)));
return false;
}
break;
}
case GGML_OP_GLU: {
auto supported = supported_glu_ops.find(ggml_get_glu_op(op)) != supported_glu_ops.end();
if (!supported) {
GGML_LOG_WARN("OpenVINO backend does not support GLU op %s\n", ggml_glu_op_name(ggml_get_glu_op(op)));
return false;
}
break;
}
default: {
auto supported = supported_ops.find(op->op) != supported_ops.end();
if (!supported) {
GGML_LOG_WARN("OpenVINO backend does not support op %s\n", ggml_op_name(op->op));
return false;
}
}
}
if (supported_types.find(op->type) == supported_types.end()) {
GGML_LOG_WARN("OpenVINO backend does not support tensor type %s\n", ggml_type_name(op->type));
return false;
}
if (op->ne[3] != 1) {
GGML_LOG_WARN("OpenVINO backend does not support tensors with ne[3] != 1\n");
return false;
}
for (int i = 0; i < GGML_MAX_SRC; i++) {
auto* src = op->src[i];
if (src == nullptr) {
break;
}
if (supported_types.find(src->type) == supported_types.end()) {
GGML_LOG_WARN("OpenVINO backend does not support tensor type %s\n", ggml_type_name(src->type));
return false;
}
if (src->ne[3] != 1) {
GGML_LOG_WARN("OpenVINO backend does not support tensors with ne[3] != 1\n");
return false;
}
if (ggml_is_quantized(src->type) && src->ne[2] != 1) {
GGML_LOG_WARN("OpenVINO backend does not support 3D quantized tensors\n");
return false;
}
}
if (is_op_unsupported_case(op)) {
return false;
}
return true;
}
static bool ggml_backend_openvino_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) {
return ggml_backend_buft_is_host(buft);
GGML_UNUSED(dev);
}
static const struct ggml_backend_device_i ggml_backend_openvino_device_interface = {
/* .get_name = */ ggml_backend_openvino_device_get_name,
/* .get_description = */ ggml_backend_openvino_device_get_description,
/* .get_memory = */ ggml_backend_openvino_device_get_memory,
/* .get_type = */ ggml_backend_openvino_device_get_type,
/* .get_props = */ ggml_backend_openvino_device_get_props,
/* .init_backend = */ ggml_backend_openvino_device_init,
/* .get_buffer_type = */ ggml_backend_openvino_device_get_buffer_type,
/* .get_host_buffer_type = */ NULL,
/* .buffer_from_host_ptr = */ ggml_backend_openvino_device_buffer_from_ptr,
/* .supports_op = */ ggml_backend_openvino_device_supports_op,
/* .supports_buft = */ ggml_backend_openvino_device_supports_buft,
/* .offload_op = */ NULL,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_synchronize = */ NULL,
};
struct ggml_backend_openvino_reg_context {
std::vector<ggml_backend_dev_t> devices;
};
static const char * ggml_backend_openvino_reg_get_name(ggml_backend_reg_t reg) {
return GGML_OPENVINO_NAME;
GGML_UNUSED(reg);
}
static size_t ggml_backend_openvino_reg_get_device_count(ggml_backend_reg_t reg) {
return ggml_openvino_info().device_count;
GGML_UNUSED(reg);
// TODO
ggml_backend_openvino_reg_context * ctx = (ggml_backend_openvino_reg_context *)reg->context;
return ctx->devices.size();
}
static ggml_backend_dev_t ggml_backend_openvino_reg_get_device(ggml_backend_reg_t reg, size_t index) {
ggml_backend_openvino_reg_context * ctx = (ggml_backend_openvino_reg_context *)reg->context;
GGML_ASSERT(index < ctx->devices.size());
return ctx->devices[index];
// GGML_ASSERT(index == 0);
// static ggml_backend_device ggml_backend_openvino_device = {
// /* .iface = */ ggml_backend_openvino_device_interface,
// /* .reg = */ reg,
// /* .context = */ nullptr,
// };
// return &ggml_backend_openvino_device;
// GGML_UNUSED(reg);
// GGML_UNUSED(index);
}
static void * ggml_backend_openvino_get_proc_address(ggml_backend_reg_t reg, const char * name) {
GGML_UNUSED(reg);
if (strcmp(name, "ggml_backend_split_buffer_type") == 0) {
return (void *)ggml_backend_openvino_split_buffer_type;
}
// if (strcmp(name, "ggml_backend_register_host_buffer") == 0) {
// return (void *)ggml_backend_openvino_register_host_buffer;
// }
// if (strcmp(name, "ggml_backend_unregister_host_buffer") == 0) {
// return (void *)ggml_backend_openvino_unregister_host_buffer;
// }
return nullptr;
}
static const struct ggml_backend_reg_i ggml_backend_openvino_reg_interface = {
/* .get_name = */ ggml_backend_openvino_reg_get_name,
/* .get_device_count = */ ggml_backend_openvino_reg_get_device_count,
/* .get_device = */ ggml_backend_openvino_reg_get_device,
/* .get_proc_address = */ ggml_backend_openvino_get_proc_address,
};
static int get_openvino_device_count() {
ov::Core core;
auto devices = core.get_available_devices();
// return devices.size();
return 1;
}
static ggml_openvino_device_info ggml_openvino_init() {
ggml_openvino_device_info info = {};
// TODO
info.device_count = get_openvino_device_count();
return info;
}
const ggml_openvino_device_info & ggml_openvino_info() {
static ggml_openvino_device_info info = ggml_openvino_init();
return info;
}
GGML_BACKEND_API ggml_backend_reg_t ggml_backend_openvino_reg(void) {
static ggml_backend_reg reg;
static bool initialized = false;
{
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
if (!initialized) {
ggml_backend_openvino_reg_context * ctx = new ggml_backend_openvino_reg_context;
// GGML_LOG_DEBUG("ggml_openvino_info().device_count = %d \n", ggml_openvino_info().device_count);
for (int i = 0; i < ggml_openvino_info().device_count; i++) {
ggml_backend_openvino_device_context * dev_ctx = new ggml_backend_openvino_device_context;
dev_ctx->device = i;
dev_ctx->name = GGML_OPENVINO_NAME + std::to_string(i);
// ggml_openvino_set_device(i);
dev_ctx->description = ov::get_openvino_version().description;
ggml_backend_dev_t dev = new ggml_backend_device {
/* .interface = */ ggml_backend_openvino_device_interface,
/* .reg = */ &reg,
/* .context = */ dev_ctx
};
ctx->devices.push_back(dev);
}
reg = ggml_backend_reg{ /* .api_version = */ GGML_BACKEND_API_VERSION,
/* .iface = */ ggml_backend_openvino_reg_interface,
/* .context = */ ctx };
}
initialized = true;
}
return &reg;
}
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