how to accelerate bge m3 sparse embeding module when inference？

[seetimee]

Feature request

how to accelerate bge m3 sparse embeding module when inference？

Motivation

the sparse embeding process is too slow during infer bge-m3 after accelerate the dense emb inference

Your contribution

you can give a idea，I will learn how to make it work

[greptile-apps]

To accelerate the bge-m3 sparse embedding module during inference, consider the following steps:

1. Optimize Model Loading:

   • Ensure the model is loaded efficiently in select_model.py.
   • Use optimized libraries like ONNX or TensorRT if supported.

2. Batch Processing:

   • Increase the batch size in BatchHandler initialization in engine.py.
   • Adjust batch_delay to balance between latency and throughput.

3. Caching:

   • Implement or enhance caching mechanisms in batch_handler.py to reuse embeddings.

4. Hardware Acceleration:

   • Utilize GPU or specialized hardware (e.g., AWS Neuron) for inference.
   • Check transformer/embedder/neuron.py for Neuron-specific optimizations.

5. Parallel Processing:

   • Use multi-threading or asynchronous processing in BatchHandler and ModelWorker classes.

Example Code Adjustments:

# engine.py
self._batch_handler = BatchHandler(
    max_batch_size=self._engine_args.batch_size * 2,  # Increase batch size
    model=self._model,
    batch_delay=self._min_inference_t / 4,  # Adjust batch delay
    vector_disk_cache_path=self._engine_args.vector_disk_cache_path,
    verbose=logger.level <= 10,
    lengths_via_tokenize=self._engine_args.lengths_via_tokenize,
)

# batch_handler.py
class BatchHandler:
    def __init__(self, ...):
        ...
        self._threadpool = ThreadPoolExecutor(max_workers=8)  # Increase thread pool size
        ...

These changes should help in accelerating the sparse embedding process for the bge-m3 model.

References

/libs/infinity_emb/infinity_emb/engine.py
/libs/infinity_emb/infinity_emb/inference/select_model.py
/libs/infinity_emb/infinity_emb/inference/batch_handler.py
/libs/infinity_emb/infinity_emb/inference
/libs/infinity_emb/infinity_emb/transformer/embedder

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[seetimee]

These methods are difficult to work.