Computational Measurement Model for Large Language Models
In the face of the rapidly increasing demand for computing power in large language models,traditional Moore's Law is no longer sufficient to meet the demand,while the expansion rules of large language models indicate that more parameters,more data,and more computing power can lead to better model intelligence.Research is conducted on the measurement of computing power for large language models in order to evaluate the computing power requirements of large language models.It proposes a computational power measurement model for training large language models and a computational power measurement model for inference of large language models,and the corresponding calculation methods is put forward through theoretical analysis.
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