Skip to content

Remove unused static remote context and parallelize model build #291

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
zhaixuejun1993 wants to merge 2 commits into
base: dev_backend_openvino
Choose a base branch
from
+48 −29
Open

Remove unused static remote context and parallelize model build #291

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a9acc80
openvino: remove unused static remote context branch
zhaixuejun1993 Aug 17, 2026
3f2ffef
openvino: parallelize static model build
zhaixuejun1993 Aug 17, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
77 changes: 48 additions & 29 deletions ggml/src/ggml-openvino/utils.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,8 @@
#include <cstdlib>
#include <cstring>
#include <fstream>
#include <functional>
#include <future>
#include <iomanip>
#include <iostream>
#include <memory>
Expand Down Expand Up @@ -700,38 +702,55 @@ enum ggml_status ov_graph_compute_static(ggml_cgraph * cgraph, std::shared_ptr<o
stateful, false, false, prefill_chunk_size);
decoder_end_time = ggml_time_us();

auto input_model_prefill = std::make_shared<ov::frontend::ggml::InputModel>(ggml_decoder_prefill);
auto input_model_decode = std::make_shared<ov::frontend::ggml::InputModel>(ggml_decoder_decode);

auto model_prefill = ov::frontend::ggml::FrontEnd::convert(input_model_prefill);
ggml_decoder_prefill->clear_model_weights();
auto model_decode = ov::frontend::ggml::FrontEnd::convert(input_model_decode);
ggml_decoder_decode->clear_model_weights();
conversion_end_time = ggml_time_us();

if (ggml_openvino_getenv_int("GGML_OPENVINO_DUMP_IR")) {
char timestamped_filename[64];
auto timestamp = (long long) ggml_time_us();
snprintf(timestamped_filename, sizeof(timestamped_filename), "model_prefill_%lld.xml", timestamp);
ov::serialize(model_prefill, timestamped_filename);
snprintf(timestamped_filename, sizeof(timestamped_filename), "model_decode_%lld.xml", timestamp);
ov::serialize(model_decode, timestamped_filename);
}
const bool dump_ir = ggml_openvino_getenv_int("GGML_OPENVINO_DUMP_IR");
const auto dump_ir_timestamp = static_cast<long long>(ggml_time_us());

auto build_static_model = [&core, &config, dump_ir, dump_ir_timestamp](
std::shared_ptr<GgmlOvDecoder> decoder,
const char * tag,
std::shared_ptr<ov::Model> & model,
ov::CompiledModel & compiled_model,
std::shared_ptr<ov::InferRequest> & infer_request,
int64_t & local_conversion_end_time,
int64_t & local_compile_end_time) {
auto input_model = std::make_shared<ov::frontend::ggml::InputModel>(decoder);
model = ov::frontend::ggml::FrontEnd::convert(input_model);
decoder->clear_model_weights();
local_conversion_end_time = ggml_time_us();

if (dump_ir) {
char timestamped_filename[64];
snprintf(timestamped_filename, sizeof(timestamped_filename), "model_%s_%lld.xml", tag,
dump_ir_timestamp);
ov::serialize(model, timestamped_filename);
}

compiled_model = core.compile_model(model, device, config);
infer_request = std::make_shared<ov::InferRequest>(compiled_model.create_infer_request());
local_compile_end_time = ggml_time_us();
};
std::shared_ptr<ov::Model> model_prefill;
std::shared_ptr<ov::Model> model_decode;
ov::CompiledModel compiled_model_prefill;
ov::CompiledModel compiled_model_decode;
auto remote_context = ggml_openvino_get_remote_context();
if (remote_context.has_value()) {
compiled_model_prefill = core.compile_model(model_prefill, remote_context.value(), config);
compiled_model_decode = core.compile_model(model_decode, remote_context.value(), config);
} else {
compiled_model_prefill = core.compile_model(model_prefill, device, config);
compiled_model_decode = core.compile_model(model_decode, device, config);
}

auto infer_request_prefill = std::make_shared<ov::InferRequest>(compiled_model_prefill.create_infer_request());
auto infer_request_decode = std::make_shared<ov::InferRequest>(compiled_model_decode.create_infer_request());
compile_end_time = ggml_time_us();
std::shared_ptr<ov::InferRequest> infer_request_prefill;
std::shared_ptr<ov::InferRequest> infer_request_decode;
int64_t prefill_conversion_end_time;
int64_t decode_conversion_end_time;
int64_t prefill_compile_end_time;
int64_t decode_compile_end_time;
auto prefill_future = std::async(std::launch::async, build_static_model, ggml_decoder_prefill, "prefill",
std::ref(model_prefill), std::ref(compiled_model_prefill),
std::ref(infer_request_prefill), std::ref(prefill_conversion_end_time),
std::ref(prefill_compile_end_time));
auto decode_future = std::async(std::launch::async, build_static_model, ggml_decoder_decode, "decode",
std::ref(model_decode), std::ref(compiled_model_decode),
std::ref(infer_request_decode), std::ref(decode_conversion_end_time),
std::ref(decode_compile_end_time));
prefill_future.get();
decode_future.get();
conversion_end_time = std::max(prefill_conversion_end_time, decode_conversion_end_time);
compile_end_time = std::max(prefill_compile_end_time, decode_compile_end_time);

model = is_prefill ? model_prefill : model_decode;
ggml_decoder = is_prefill ? ggml_decoder_prefill : ggml_decoder_decode;
Expand Down