Shanghai Cambricon Information Technology Co., Ltd

Cambricon Technologies Corporation Limited

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

Xiaobing Chen

Tianshi Chen

Shuai Hu

Shaoli Liu

Yunji Chen

Nan Wang

Zidong Du

Zai Wang

Tian Zhi

Daofu Liu

Yimin Zhuang

Yongwei Zhao

Yongzhe Sun

The invention provides an artificial intelligence computing device and a related product. The artificial intelligence computing device is used for executing machine learning computation. According to the device of the invention, for the instructions in the more than two instruction sets forming the loop body, the same operation code in the operation code storage area is used for the repeated instructions, so that the storage space of the operation code is saved, the code amount of each instruction in the instruction set in the second time slice can be reduced, the instruction storage space can also be saved, and the operation efficiency is improved.

Artificial intelligence computing device and related product

The present disclosure discloses an image processing device including: a receiving module configured to receive a voice signal and an image to be processed; a conversion module configured to convert the voice signal into an image processing instruction and determine a target area according to a target voice instruction conversion model, in which the target area is a processing area of the image to be processed; and a processing module configured to process the target area according to the image processing instruction and a target image processing model. The examples may realize the functionality of using voice commands to control image processing, which may save users' time spent in learning image processing software prior to image processing, and improve user experience.

Image processing apparatus and method

Aspects of processing data for Long Short-Term Memory (LSTM) neural networks are described herein. The aspects may include one or more data buffer units configured to store previous output data at a previous timepoint, input data at a current timepoint, one or more weight values, and one more bias values. The aspects may further include multiple data processing units configured to parallelly calculate a portion of an output value at the current timepoint based on the previous output data at the previous timepoint, the input data at the current timepoint, the one or more weight values, and the one or more bias values.

Apparatus for executing LSTM neural network operation, and operational method

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 computation speed and energy-saving.

Operation device and related products

Growing community of inventors

Shanghai, China

Xiaobing Chen