The present disclosure relates to a method, a device, and related products for processing data. In an embodiment of the present disclosure, when processing data related to a neural network, an optimal truncation threshold value for a plurality of pieces of data is determined. The data is truncated through the truncation data threshold, and the plurality of pieces of data is quantized from a high-precision format to a low-precision format. The method in the present disclosure can ensure the precision of data processing as high as possible while reducing the amount of data processing. In addition, the method also helps to significantly reduce the amount of data transmission, thereby greatly accelerating the data exchange among a plurality of computing devices.

A power supply system includes a power supply unit, a voltage converting unit, a comparison unit, and a switching unit. The power supply unit is configured to provide working voltage for a motherboard via a first resistor. The voltage converting unit includes a voltage converting chip. The voltage converting chip is configured to detect a first direct current (DC) voltage on the first resistor, and convert the first DC voltage to a second DC voltage. The comparison unit is configured to receive the second DC voltage, compare the second DC voltage with the working voltage, and output a switch signal. The switching unit is configured to receive the switch signal, and output a control signal to a central processing unit (CPU) on the motherboard according to the switch signal. The CPU is configured to adjust its frequency according to the control signal.