The DGPT model implements the construction of an arithmetic platform that transforms idle arithmetic into valuable computing resources and enables arithmetic providers to gain economic benefits through task execution and realisation mechanisms. This model enables users to more flexibly use idle arithmetic to participate in AI and data processing tasks, maximising the use of resources and economic benefits.
① Arithmetic Access:
Users can provide idle arithmetic by providing their own hardware access platform, and by installing the corresponding client software, they can automatically measure the level of hardware arithmetic and evaluate the revenue interval, so that these devices become the arithmetic provider of DGPT. Such as personal computers, mobile devices, etc., to provide arithmetic to help train the model, reduce the model centralised operating costs, the user in the process, will be based on the arithmetic contribution to gain revenue.
② Model training:
The arithmetic centre on the DGPT platform deploys various types of arithmetic tasks that require a large amount of computing resources, and the user only needs to provide the platform with idle hardware arithmetic and purchase a suitable platform accelerator to complete the training tasks based on the accelerated arithmetic level. Examples include machine learning model training, data analysis, etc.
③ Results Submission:
After completing the task, the idle arithmetic device automatically submits the computational results to the DGPT platform. These results can be trained models, processed data, etc., depending on the task arithmetic requirements.
④ Settlement and realisation:
The DGPT platform settles the arithmetic provider based on the remuneration set for the task and the completion of the task, and releases the corresponding remuneration to the arithmetic provider in the form of revenue. Idle arithmetic power is realised, and the arithmetic power providers also receive financial gains from it.