Abstract: A neural network operation module, which comprises a storage unit that stores output neurons, weight precision and output neuron gradient precision of a multi-layer neural network; a controller unit that obtains an average value Y1 of the absolute value of the output neuron before fixed-point and an average value Y2 of the absolute value of the output neuron after fixed-point; if Y1/Y2 is greater than a preset threshold K, obtaining the output neuron gradient precision of adjacent two layers of the multi-layer neural network, and obtaining an estimation value An of error transfer precision; when An is greater than a preset precision Ar, the output neuron gradient precision and weight precision of the adjacent two layers are increased; and an operation unit that represents the output neuron gradient and weight of the adjacent two layers according to the increased precision.

Abstract: Embodiments of the present disclosure relate to a method and an apparatus for processing data, and related products. The embodiments of the present disclosure relate to a board card including a storage component, an interface apparatus, a control component, and an artificial intelligence chip, where the artificial intelligence chip is connected to the storage component, the control component and the interface apparatus respectively. The storage component is used to store data; the interface apparatus is used to realize data transmission between the artificial intelligence chip and the external device. The control component is used to monitor a state of the artificial intelligence chip. The board card may be used to perform artificial intelligence computations.

Abstract: Embodiments of the present disclosure relate to a method and an apparatus for processing data, and related products. The embodiments of the present disclosure provide a board card including a storage component, an interface device, a control component, and an artificial intelligence chip. The artificial intelligence chip is connected to the storage component, the control component, and the interface device, respectively; the storage component is configured to store data; the interface device is configured to implement data transfer between the artificial intelligence chip and external equipment; and the control component is configured to monitor a state of the artificial intelligence chip. The board card is configured to perform artificial intelligence operations.

Abstract: 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.

Abstract: The present disclosure provides a data processing method, a board card device, a computer equipment, and a storage medium for data quantization. The board card provided in the present disclosure includes a storage component, an interface device, a control component, and an artificial intelligence chip of a data processing device, where the artificial intelligence chip is connected to the storage device, the control device, and the interface apparatus, respectively. According to the data processing method, the device, the computer equipment, and the storage medium provided in the embodiments of the present disclosure, data to be quantized is quantized according to a corresponding quantization parameter, which may reduce the storage space of data while ensuring the precision, as well as ensure the accuracy and reliability of the operation result and improve the operation efficiency.

Abstract: The present disclosure provides a data processing method, a board card device, computer equipment, and a storage medium for data quantization. The board card provided in the present disclosure includes a storage device, an interface apparatus, a control device, and an artificial intelligence chip of a data processing device, where the artificial intelligence chip is connected to the storage device, the control device, and the interface apparatus, respectively. The storage device is configured to store data; the interface apparatus is configured to implement data transmission between the artificial intelligence chip and an external apparatus; and the control device is configured to monitor the state of the artificial intelligence chip. The data to be quantized is quantized according to corresponding quantization parameters, which reduce the storage space of data while ensuring precision, accuracy and reliability of the operation result, and improving the operation efficiency.

Abstract: The present disclosure provides a signal processing device, including a signal collector, an instruction converter, and a processor. Examples of the present disclosure may achieve precise recognition of users' intentions and bring operational conveniences to users.

Abstract: The present disclosure relates to a neural network quantization parameter determination method and related products. A board card in the related products includes a memory device, an interface device, a control device, and an artificial intelligence chip, in which the artificial intelligence chip is connected with the memory device, the control device, and the interface device respectively. The memory device is configured to store data, and the interface device is configured to transmit data between the artificial intelligence chip and an external device. The control device is configured to monitor the state of the artificial intelligence chip. The board card can be used to perform an artificial intelligence computation.

Abstract: The present disclosure provides a data processing method, a board card device, a computer equipment, and a storage medium. The board card provided in the present disclosure includes a storage device, an interface apparatus, a control device, and an artificial intelligence chip of a data processing device, where the artificial intelligence chip is connected to the storage device, the control device, and the interface apparatus, respectively. The control device is configured to monitor a state of the artificial intelligence chip. According to the embodiments of the present disclosure, the data to be quantized is quantized according to the corresponding quantization parameter, which may reduce the storage space of data while ensuring the precision, ensure the precision and reliability of the operation result, and improve the operation efficiency.

Abstract: The present disclosure provides a data processing method, a data processing device, a computer equipment, and a storage medium. The data processing device includes a board card and the board card provided in the present disclosure includes a storage component, an interface device, a control component, and an artificial intelligence chip of a data processing device. According to the data processing method, the data processing device, the computer equipment, and the storage medium provided in the embodiments of the present disclosure, data to be quantized is quantized according to a corresponding quantization parameter, which may reduce the storage space of data while ensuring the precision, as well as ensure the accuracy and reliability of the operation result and improve the operation efficiency.

Abstract: The present disclosure relates to a neural network quantization parameter determination method and related products. A board card in the related products includes a memory device, an interface device, a control device, and an artificial intelligence chip, in which the artificial intelligence chip is connected with the memory device, the control device, and the interface device respectively. The memory device is configured to store data, and the interface device is configured to transmit data between the artificial intelligence chip and an external device. The control device is configured to monitor the state of the artificial intelligence chip. The board card can be used to perform an artificial intelligence computation.

Abstract: The present disclosure relates to a neural network quantization parameter determination method and related products. A board card in the related products includes a memory device, an interface device, a control device, and an artificial intelligence chip, in which the artificial intelligence chip is connected with the memory device, the control device, and the interface device respectively. The memory device is configured to store data, and the interface device is configured to transmit data between the artificial intelligence chip and an external device. The control device is configured to monitor the state of the artificial intelligence chip. The board card can be used to perform an artificial intelligence computation.

Abstract: The present disclosure provides a computation method and product thereof. The computation method adopts a fusion method to perform machine learning computations. Technical effects of the present disclosure include fewer computations and less power consumption.

Abstract: The present disclosure provides a computation method and product thereof. The computation method adopts a fusion method to perform machine learning computations. Technical effects of the present disclosure include fewer computations and less power consumption.

Abstract: The present disclosure provides a computation method and product thereof. The computation method adopts a fusion method to perform machine learning computations. Technical effects of the present disclosure include fewer computations and less power consumption.