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: A fractal computing device according to an embodiment of the present application may be included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also include a storage device. The storage device is respectively connected with the calculating device and other processing devices and is used for data storage of the computing device and other processing devices.

Abstract: The present disclosure relates to a computing device, and related products. The product includes a control unit. The control unit includes an instruction caching unit, an instruction processing unit and a storage queue unit. The instruction caching unit is used for storing a calculation instruction associated with an artificial neural network operation; the instruction processing unit is used for analyzing the calculation instruction to obtain a plurality of operation instructions; and the storage queue unit is used for storing an instruction queue, where the instruction queue includes a plurality of operation instructions or calculation instructions to be executed in the order of the queue. By using the computing device and related products, the present disclosure may improve the operation efficiency of the related products when performing neural network model operations.

Abstract: A fractal calculating device according to an embodiment of the present application is included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also comprise a storage device. The storage device is respectively connected with the calculating device and other processing devices and is used for data storage of the computing device and other processing devices.

Abstract: A method is for optimizing a convolution operation of an on-chip system and related products. The on-chip system is included in a computing processing apparatus of a combined processing apparatus. The computing processing apparatus includes one or a plurality of integrated circuit apparatuses. The combined processing apparatus further includes an interface apparatus and other processing apparatus. The computing processing apparatus interacts with other processing apparatus to jointly complete a computing operation specified by a user. The combined processing apparatus further includes a storage apparatus. The storage apparatus is connected to the apparatus and other processing apparatus, respectively. The storage apparatus is configured to store data of the apparatus and other processing apparatus.

Abstract: The present disclosure discloses a method for performing a matrix multiplication on an on-chip system and related products. The on-chip system is included in a computing processing apparatus of a combined processing apparatus. The computing processing apparatus includes one or a plurality of integrated circuit apparatuses. The combined processing apparatus further includes an interface apparatus and other processing apparatus. The computing processing apparatus interacts with other processing apparatus to jointly complete a computing operation specified by a user. The combined processing apparatus further includes a storage apparatus. The storage apparatus is connected to the apparatus and other processing apparatus, respectively. The storage apparatus is configured to store data of the apparatus and other processing apparatus.

Abstract: A fractal computing device according to an embodiment of the present application may be included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also include a storage device. The storage device is respectively connected with the calculating device and other processing devices and is used for data storage of the computing device and other processing devices.

Abstract: A fractal calculating device according to an embodiment of the present application is included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also comprise a storage device.

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, which includes a storage component, an interface apparatus, a control component, and an artificial intelligence chip. 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 an external device; and 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: A fractal computing device according to an embodiment of the present application may be included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also include a storage device. The storage device is respectively connected with the calculating device and other processing devices and is used for data storage of the computing device and other processing devices.

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: A fractal computing device according to an embodiment of the present application may be included in an integrated circuit device. The integrated circuit device includes a universal interconnect interface and other processing devices. The calculating device interacts with other processing devices to jointly complete a user specified calculation operation. The integrated circuit device may also include a storage device. The storage device is respectively connected with the calculating device and other processing devices and is used for data storage of the computing device and other processing devices.

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: A method and system for calibrating extrinsic parameters between a depth camera and a visible light camera. Acquiring depth images and visible light images of the checkerboard plane in different transformation poses; determining visible light checkerboard planes of different transformation poses in a coordinate system of the visible light camera and depth checkerboard planes of different transformation poses in a coordinate system of the depth camera; determining a rotation matrix from the coordinate system of the depth camera to the coordinate system of the visible light camera; determining a translation vector from the coordinate system of the depth camera to the coordinate system of the visible light camera; rotating and translating the coordinate system of the depth camera, so that the coordinate system of the depth camera coincides with the coordinate system of the visible light camera to complete the extrinsic calibration of the dual cameras.

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 invention relates to a medium-pressure hydrocracking process which uses a fresh hydrogen resource and a hydrosaturation catalyst with reduced metals of group VIB and/or group VIII as the active ingredients to selectively and deeply hydrosaturate jet fuel and/or diesel cuts derived in the medium-pressure hydrocracking process.

Abstract: The present invention relates to a medium-pressure hydrocracking process which uses a fresh hydrogen resource and a hydrosaturation catalyst with reduced metals of group VIB and/or group VIII as the active ingredients to selectively and deeply hydrosaturate jet fuel and/or diesel cuts derived in the medium-pressure hydrocracking process.