公开(公告)号：US20240104342A1

公开(公告)日：2024-03-28

申请号：US18521425

申请日：2023-11-28

申请人： Huawei Technologies Co., Ltd.

发明人： Xinlin LI ,  Vahid PARTOVI NIA

IPC分类号： G06N3/04 ,  G06F7/499 ,  G06F7/78

CPC分类号： G06N3/04 ,  G06F7/49942 ,  G06F7/78

摘要： Methods, systems and computer readable media using hardware-efficient bit-shift operations for computing the output of a low-bit neural network layer. A dense shift inner product operator (or dense shift IPO) using bit shifting in place of multiplication replaces the inner product operator that is conventionally used to compute the output of a neural network layer. Dense shift neural networks may have weights encoded using a low-bit dense shift encoding. A dedicated neural network accelerator is designed to compute the output of a dense shift neural network layer using dense shift IPOs. A Sign-Sparse-Shift (S3) training technique trains a low-bit neural network using dense shift IPOs or other bit shift operations in computing its outputs.

公开(公告)号：US20240070221A1

公开(公告)日：2024-02-29

申请号：US18502506

申请日：2023-11-06

申请人： Huawei Technologies Co., Ltd.

发明人： Eyyüb Hachmie SARI ,  Vanessa COURVILLE ,  Mohan LIU ,  Vahid PARTOVI NIA

IPC分类号： G06F17/12 ,  G06F7/50 ,  G06F7/523 ,  G06F7/544

CPC分类号： G06F17/12 ,  G06F7/50 ,  G06F7/523 ,  G06F7/5443

摘要： Methods and systems for generating an integer neural network are described. The method includes receiving an input vector comprising a plurality of input values. The plurality of input values are represented using a desired number bits. The input vector is multiplied by a weight vector, and the products of which are summed to obtain a first value. The first value is quantized and applied to a piecewise linear activation function to obtain a second value. The piecewise linear activation function is a set of linear function that collectively approximate a nonlinear activation function. The second value is quantized to generate the output of the neuron in the integer neural network.

公开(公告)号：US20200057961A1

公开(公告)日：2020-02-20

申请号：US16540883

申请日：2019-08-14

申请人： HUAWEI TECHNOLOGIES CO., LTD.

发明人： Ali VAHDAT ,  Vahid PARTOVI NIA

IPC分类号： G06N20/00 ,  G06N5/04 ,  G06N5/00

摘要： Methods and systems are described for training a machine learning (ML) model to predict the gain of a target channel of a multi-channel amplifier device. An ML model may be pre-trained using an existing set of training objects. The trained ML model then can be utilized to suggest further useful training objects to be labelled that will improve the performance of the ML model by predicting more accurate target channel gains given the on/off value for the channel inputs.