Shanghai Cambricon Information Technology Co., Ltd

Cambricon (Xi'an) Semiconductor Co., Ltd.

Zai Wang

Tianshi Chen

Shaoli Liu

Shuai Hu

Zidong Du

Xuda Zhou

Shengyuan Zhou

Tian Zhi

Jie Wei

Qi Guo

Daofu Liu

Yimin Zhuang

Yifan Hao

Xiaobing Chen

Yuzhe Luo

Wei Li

Xiaobin Chen

The present disclosure provides a processing device including: a coarse-grained pruning unit configured to perform coarse-grained pruning on a weight of a neural network to obtain a pruned weight, an operation unit configured to train the neural network according to the pruned weight. The coarse-grained pruning unit is specifically configured to select M weights from the weights of the neural network through a sliding window, and when the M weights meet a preset condition, all or part of the M weights may be set to 0. The processing device can reduce the memory access while reducing the amount of computation, thereby obtaining an acceleration ratio and reducing energy consumption.

Processing method and accelerating device

Disclosed are an information processing method and a terminal device. The method comprises: acquiring first information, wherein the first information is information to be processed by a terminal device; calling an operation instruction in a calculation apparatus to calculate the first information so as to obtain second information; and outputting the second information. By means of the embodiments in the present disclosure, a calculation apparatus of a terminal device can be used to call an operation instruction to process first information, so as to output second information of a target desired by a user, thereby improving the information processing efficiency.

Information processing method and terminal device

The application provides a processor and processing method. The processor includes a task segmentation device configured to perform task segmentation according to a task segmentation granularity and a hardware resource division device configured to divide hardware resources of the processor according to a task segmentation result. The processor and processing method provided by the application improve the processing performance and reduce the overhead by performing task segmentation and configuring different hardware according to task segmentation.

Data sharing system and data sharing method therefor

Disclosed are an information processing method and a terminal device. The method comprises: acquiring first information, wherein the first information is information to be processed by a terminal device, calling an operation instruction in a calculation apparatus to calculate the first information so as to obtain second information, and outputting the second information. By means of the examples in the present disclosure, a calculation apparatus of a terminal device can be used to call an operation instruction to process first information, so as to output second information of a target desired by a user, thereby improving the information processing efficiency. The present technical solution has advantages of a fast computation speed and high efficiency.

Information processing method and system

Disclosed are an information processing method and a terminal device. The method comprises: acquiring first information, wherein the first information is information to be processed by a terminal device; calling an operation instruction in a calculation apparatus to calculate the first information so as to obtain second information; and outputting the second information. By means of the examples in the present disclosure, a calculation apparatus of a terminal device can be used to call an operation instruction to process first information, so as to output second information of a target desired by a user, thereby improving the information processing efficiency. The present technical solution has advantages of a fast computation speed and high efficiency.

An information processing method applied to a computation circuit is disclosed. The computation circuit includes a communication circuit and an operation circuit. The method includes controlling, by the computation circuit, the communication circuit to obtain a voice to be identified input by a user; controlling, by the computation circuit, the operation circuit to obtain and call an operation instruction to perform voice identification processing on the voice to be identified to obtain target text information corresponding to the voice to be identified. The operation instruction is a preset instruction for voice identification.

Voice recognition based on neural networks

Image retouching method and terminal device

The present disclosure provides a computing method that is applied to a computing device. The computing device includes: a memory, a register unit, and a matrix computing unit. The method includes the following steps: controlling, by the computing device, the matrix computing unit to obtain a first operation instruction, where the first operation instruction includes a matrix reading instruction for a matrix required for executing the instruction; controlling, by the computing device, an operating unit to send a reading command to the memory according to the matrix reading instruction; and controlling, by the computing device, the operating unit to read a matrix corresponding to the matrix reading instruction in a batch reading manner, and executing the first operation instruction on the matrix. The technical solutions in the present disclosure have the advantages of fast computing speed and high efficiency.

Calculation method and related product

The present application provides an operation device and related products. The operation device is configured to execute operations of a network model, wherein the network model includes a neural network model and/or non-neural network model; the operation device comprises an operation unit, a controller unit and a storage unit, wherein the storage unit includes a data input unit, a storage medium and a scalar data storage unit. The technical solution provided by this application has advantages of a fast calculation speed and energy-saving.

Sparse processing in neural network processors

The present disclosure provides a counting device and counting method. The device includes a storage unit, a counting unit, and a register unit, where the storage unit may be connected to the counting unit for storing input data to be counted and storing a number of elements satisfying a given condition in the input data after counting; the register unit may be configured to store an address where input data to be counted is stored in the storage unit; and the counting unit may be connected to the register unit, and may be configured to acquire a counting instruction, read a storage address of the input data to be counted in the register unit according to the counting instruction, acquire corresponding input data to be counted in the storage unit, perform statistical counting on a number of elements in the input data to be counted that satisfy the given condition, and obtain a counting result. The counting device and the method may improve the computation efficiency by writing an algorithm of counting a number of elements that satisfy a given condition in input data into an instruction form.

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Pudong New Area, China

Zai Wang