Data backup method, device, equipment and computer readable storage medium
A data backup, computer program technology, applied in computing, electrical digital data processing, error detection of redundant data in operations, etc., can solve the problems of stagnant training tasks, low model training efficiency, loss of results, etc.
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Embodiment 1
[0047] see figure 1 , figure 1 It is an implementation flowchart of a data backup method in an embodiment of the present invention, and the method may include the following steps:
[0048] S101: Obtain device state information of a target GPU device currently used for model training.
[0049] In the process of using the target GPU device for deep learning model training, the host computer can be used to monitor the GPU device to obtain the device status information of the target GPU device currently used for model training. The device status information may include information such as temperature, memory, power consumption, and utilization of the target GPU device.
[0050] The target GPU device is any GPU device in the process of model training.
[0051] S102: Determine whether the target GPU device meets the warning condition according to the device status information, if yes, perform step S103, if not, do not process.
[0052] The warning condition for warning the targe...
Embodiment 2
[0061] see figure 2 , figure 2 It is another implementation flowchart of the data backup method in the embodiment of the present invention, and the method may include the following steps:
[0062] S201: Obtain information about each warning parameter of a target GPU device.
[0063] In the process of using the target GPU device for model training, the early warning parameter information of the target GPU device can be obtained, such as the temperature, memory, power consumption and utilization of the target GPU device and other early warning parameter information.
[0064] S202: Calculate an early warning value according to each early warning parameter information and corresponding preset weights.
[0065] You can pre-set the calculation formula for the warning value of the target GPU device. Following the above example, when the warning parameter information includes temperature, memory, power consumption, and utilization rate, you can normalize the warning parameter info...
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