Patents by Inventor Xuda ZHOU
Xuda ZHOU has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11907844Abstract: 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.Type: GrantFiled: November 28, 2019Date of Patent: February 20, 2024Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTDInventors: Zidong Du, Xuda Zhou, Shaoli Liu, Tianshi Chen
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Patent number: 11727276Abstract: 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.Type: GrantFiled: November 28, 2019Date of Patent: August 15, 2023Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTDInventors: Zai Wang, Xuda Zhou, Zidong Du, Tianshi Chen
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Patent number: 11593658Abstract: The application provides a processing method and device. Weights and input neurons are quantized respectively, and a weight dictionary, a weight codebook, a neuron dictionary, and a neuron codebook are determined. A computational codebook is determined according to the weight codebook and the neuron codebook. Meanwhile, according to the application, the computational codebook is determined according to two types of quantized data, and the two types of quantized data are combined, which facilitates data processing.Type: GrantFiled: July 13, 2018Date of Patent: February 28, 2023Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTDInventors: Shaoli Liu, Xuda Zhou, Zidong Du, Daofu Liu
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Patent number: 11537858Abstract: 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.Type: GrantFiled: November 28, 2019Date of Patent: December 27, 2022Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTD.Inventors: Tianshi Chen, Xuda Zhou, Shaoli Liu, Zidong Du
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Publication number: 20220335299Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: October 20, 2022Inventors: Zai Wang, Xuda Zhou, Zidong Du, Tianshi Chen
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Patent number: 11086634Abstract: 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.Type: GrantFiled: November 28, 2019Date of Patent: August 10, 2021Assignee: Shanghai Cambricon Information Technology Co., Ltd.Inventors: Zai Wang, Xuda Zhou, Zidong Du, Tianshi Chen
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Patent number: 10971221Abstract: Aspect for storage device with fault tolerance capability for neural networks are described herein. The aspects may include a first storage unit of a storage device. The first storage unit is configured to store one or more first bits of data and the data includes floating point type data and fixed point type data. The first bits include one or more sign bits of the floating point type data and the fixed point type data. The aspect may further include a second storage unit of the storage device. The second storage unit may be configured to store one or more second bits of the data. In some examples, the first storage unit may include an ECC memory and the second storage unit may include a non-ECC memory. The ECC memory may include an ECC check Dynamic Random Access Memory and an ECC check Static Random Access Memory.Type: GrantFiled: April 30, 2020Date of Patent: April 6, 2021Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTD.Inventors: Shaoli Liu, Xuda Zhou, Zidong Du, Daofu Liu
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Publication number: 20210035628Abstract: Aspect for storage device with fault tolerance capability for neural networks are described herein. The aspects may include a first storage unit of a storage device. The first storage unit is configured to store one or more first bits of data and the data includes floating point type data and fixed point type data. The first bits include one or more sign bits of the floating point type data and the fixed point type data. The aspect may further include a second storage unit of the storage device. The second storage unit may be configured to store one or more second bits of the data. In some examples, the first storage unit may include an ECC memory and the second storage unit may include a non-ECC memory. The ECC memory may include an ECC check Dynamic Random Access Memory and an ECC check Static Random Access Memory.Type: ApplicationFiled: April 30, 2020Publication date: February 4, 2021Inventors: Shaoli LIU, Xuda ZHOU, Zidong DU, Daofu LIU
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Patent number: 10755772Abstract: Aspect for storage device with fault tolerance capability for neural networks are described herein. The aspects may include a first storage unit of a storage device. The first storage unit is configured to store one or more first bits of data and the data includes floating point type data and fixed point type data. The first bits include one or more sign bits of the floating point type data and the fixed point type data. The aspect may further include a second storage unit of the storage device. The second storage unit may be configured to store one or more second bits of the data. In some examples, the first storage unit may include an ECC memory and the second storage unit may include a non-ECC memory. The ECC memory may include an ECC check Dynamic Random Access Memory and an ECC check Static Random Access Memory.Type: GrantFiled: August 1, 2019Date of Patent: August 25, 2020Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTDInventors: Shaoli Liu, Xuda Zhou, Zidong Du, Daofu Liu
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Publication number: 20200265300Abstract: The application provides an operation method and device. Quantized data is looked up to realize an operation, which simplifies the structure and reduces the computation energy consumption of the data, meanwhile, a plurality of operations are realized.Type: ApplicationFiled: March 26, 2020Publication date: August 20, 2020Inventors: Shaoli LIU, Xuda ZHOU, Zidong DU, Daofu LIU
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Publication number: 20200250539Abstract: The application provides a processing method and device. Weights and input neurons are quantized respectively, and a weight dictionary, a weight codebook, a neuron dictionary, and a neuron codebook are determined. A computational codebook is determined according to the weight codebook and the neuron codebook. Meanwhile, according to the application, the computational codebook is determined according to two types of quantized data, and the two types of quantized data are combined, which facilitates data processing.Type: ApplicationFiled: July 13, 2018Publication date: August 6, 2020Inventors: Shaoli LIU, Xuda ZHOU, Zidong DU, Daofu LIU
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Patent number: 10657439Abstract: The application provides an operation method and device. Quantized data is looked up to realize an operation, which simplifies the structure and reduces the computation energy consumption of the data, meanwhile, a plurality of operations are realized.Type: GrantFiled: August 1, 2019Date of Patent: May 19, 2020Assignee: SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTDInventors: Shaoli Liu, Xuda Zhou, Zidong Du, Daofu Liu
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Publication number: 20200134460Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: April 30, 2020Inventors: Zidong Du, Xuda Zhou, Zai Wang, Tianshi Chen
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Publication number: 20200110635Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: April 9, 2020Inventors: Shuai HU, Xuda ZHOU, Tianshi CHEN
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Publication number: 20200110609Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: April 9, 2020Inventors: Tianshi CHEN, Xuda ZHOU, Shaoli LIU, Zidong DU
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Publication number: 20200104207Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: April 2, 2020Inventors: Zai WANG, Xuda ZHOU, Zidong DU, Tianshi CHEN
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Publication number: 20200104693Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: April 2, 2020Inventors: Zidong Du, Xuda Zhou, Shaoli Liu, Tianshi Chen
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Publication number: 20200097827Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: March 26, 2020Inventors: Zai Wang, Xuda Zhou, Zidong Du, Tianshi Chen
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Publication number: 20200097828Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: March 26, 2020Inventors: Zidong Du, Xuda Zhou, Zai Wang, Tianshi Chen
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Publication number: 20200097826Abstract: 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.Type: ApplicationFiled: November 28, 2019Publication date: March 26, 2020Inventors: Zidong Du, Xuda Zhou, Shaoli Liu, Tianshi Chen