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公开(公告)号：EP3657398A1
公开(公告)日：2020-05-27
申请号：EP19214010.1
申请日：2018-05-23
发明人： LIU, Shaoli , DU, Zidong , ZHOU, Xuda , CHEN, Tianshi , HAO, Yifan , WANG, Zai
IPC分类号： G06N3/063 , G06N3/04 , G06N3/08 , G06F12/0875 , G06F12/0846
摘要： The present disclosure provides a data quantization configured to perform the following steps: grouping the weights of a neural network; performing a clustering operation on each group of weights by using a clustering algorithm, dividing a group of weights into m classes, computing a center weight for each class, and replacing all the weights in each class by the center weights, where m is a positive integer; encoding the center weight to get a weight codebook and a weight dictionary; and retraining the neural network, where only the weight codebook is trained, and the weight dictionary remains unchanged.
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公开(公告)号：EP3637327A1
公开(公告)日：2020-04-15
申请号：EP18818258.8
申请日：2018-06-12
发明人： WANG, Zai , ZHOU, Shengyuan , DU, Zidong , CHEN, Tianshi , HU, Shuai , ZHOU, Xuda , LIU, Shaoli
IPC分类号： G06N3/063
摘要： A computing device, comprising: a computing module, comprising one or more computing units; and a control module, comprising a computing control unit, and used for controlling shutdown of the computing unit of the computing module according to a determining condition. Also provided is a computing method. The computing device and method have the advantages of low power consumption and high flexibility, and can be combined with the upgrading mode of software, thereby further increasing the computing speed, reducing the computing amount, and reducing the computing power consumption of an accelerator.
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公开(公告)号：EP4372620A2
公开(公告)日：2024-05-22
申请号：EP24168317.6
申请日：2018-04-04
发明人： CHEN, Tianshi , CHEN, Xiaobing , ZHI, Tian , DU, Zidong
IPC分类号： G06N3/063
摘要： The present disclosure provides a neural network processor and neural network computation method that deploy a memory and a cache to perform a neural network computation, where the memory may be configured to store data and instructions of the neural network computation, the cache may be connected to the memory via a memory bus, thereby, the actual compute ability of hardware may be fully utilized, the cost and power consumption overhead may be reduced, parallelism of the network may be fully utilized, and the efficiency of the neural network computation may be improved.
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公开(公告)号：EP3786786A1
公开(公告)日：2021-03-03
申请号：EP19214371.7
申请日：2018-04-17
发明人： CHEN, Tianshi , GUO, Qi , ZHOU, Shengyuan , DU, Zidong
摘要： The present disclosure relates to a processing device including a memory configured to store data to be computed; a computational circuit configured to compute the data to be computed, which includes performing acceleration computations on the data to be computed by using an adder circuit and a multiplier circuit; and a control circuit configured to control the memory and the computational circuit, which includes performing acceleration computations according to the data to be computed. The present disclosure may have high flexibility, good configurability, fast computational speed, low power consumption, and other features.
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公开(公告)号：EP3637325A1
公开(公告)日：2020-04-15
申请号：EP18806558.5
申请日：2018-05-23
发明人： LIU, Shaoli , DU, Zidong , ZHOU, Xuda , CHEN, Tianshi , HAO, Yifan , WANG, Zai
摘要： 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.
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6.发明公开
公开(公告)号：EP3798850A1
公开(公告)日：2021-03-31
申请号：EP19824842.9
申请日：2019-06-25
发明人： SU, Zhenyu , ZHANG, Dingfei , ZHOU, Xiaoyong , ZHANG, Yao , LI, Chongwen , DU, Zidong , LIU, Shaoli
摘要： The present invention relates to an on-chip code breakpoint debugging method, an on-chip processor, and a chip breakpoint debugging system. The method comprises: the on-chip processor starts and executes an on-chip code, and an output function is set at a breakpoint position of the on-chip code; the on-chip processor obtains output information of the output function, the output information is output information of the output function when the on-chip code is executed to the output function; the on-chip processor stores the output information into an off-chip memory. In the embodiments of the present invention, according to the output information, which is stored in the off-chip memory, of the output function, the on-chip processor can obtain execution conditions of breakpoints of the on-chip code in real time, can achieve the purpose of debugging multiple breakpoints in the on-chip code at the same time, and debugging efficiency of the on-chip code is improved.
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公开(公告)号：EP3660706A1
公开(公告)日：2020-06-03
申请号：EP19215860.8
申请日：2018-07-13
发明人： LIU, Shaoli , ZHOU, Xuda , DU, Zidong , LIU, Daofu , ZHANG, Lei , CHEN, Tianshi , HU, Shuai , WEI, Jie , MENG, Xiaofu
摘要： The application provides a Dynamic Voltage Frequency Scaling device. The Dynamic Voltage Frequency Scaling device in a convolutional operation device acquires working state information of the convolutional operation device and its internal units/ modules in real time and scales working voltage or working frequency of the convolutional operation device and its internal units/ modules according to the working state information of the convolutional operation device and its internal units/ modules, so as to reduce the overall running power consumption of the convolutional operation device during the convolutional operation.
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公开(公告)号：EP3660629A1
公开(公告)日：2020-06-03
申请号：EP19218378.8
申请日：2018-07-05
发明人： CHEN, Tianshi , ZHANG, Lei , LIU, Shaoli , WANG, Zai , ZHOU, Xuda , DU, Zidong , HU, Shuai , HE, Haoyuan , ZHOU, Shengyuan
IPC分类号： G06F1/324 , G06F1/3296 , G06N3/063
摘要： The disclosure provides a data processing device and method. The data processing device may include: a task configuration information storage unit and a task queue configuration unit. The task configuration information storage unit is configured to store configuration information of tasks. The task queue configuration unit is configured to configure a task queue according to the configuration information stored in the task configuration information storage unit. According to the disclosure, a task queue may be configured according to the configuration information.
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公开(公告)号：EP3627397A1
公开(公告)日：2020-03-25
申请号：EP18868807.1
申请日：2018-07-13
发明人： LIU, Shaoli , ZHOU, Xuda , DU, Zidong , LIU, Daofu , ZHANG, Lei , CHEN, Tianshi , HU, Shuai , WEI, Jie , MENG, Xiaofu
IPC分类号： G06N3/02
摘要： Provided are a processing method and apparatus. The method involves: respectively quantizing a weight and an input neuron to determine a weight dictionary, a weight code book, a neuron dictionary and a neuron code book; and determining a calculation code book according to the weight code book and the neuron code book. In addition, in the present application, a calculation code book is determined according to quantized data, and the two types of quantized data are combined, thereby facilitating data processing.
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公开(公告)号：EP4372620A3
公开(公告)日：2024-07-17
申请号：EP24168317.6
申请日：2018-04-04
发明人： CHEN, Tianshi , CHEN, Xiaobing , ZHI, Tian , DU, Zidong
摘要： The present disclosure provides a neural network processor and neural network computation method that deploy a memory and a cache to perform a neural network computation, where the memory may be configured to store data and instructions of the neural network computation, the cache may be connected to the memory via a memory bus, thereby, the actual compute ability of hardware may be fully utilized, the cost and power consumption overhead may be reduced, parallelism of the network may be fully utilized, and the efficiency of the neural network computation may be improved.
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