公开(公告)号：US20230078203A1

公开(公告)日：2023-03-16

申请号：US17467079

申请日：2021-09-03

Applicant: QUALCOMM Incorporated

Inventor： Ren LI ,  Prajakt KULKARNI ,  Suren MOHAN ,  Aaron Douglass LAMB

IPC: G06N3/04 ,  G06N3/063 ,  G06F1/03

Abstract: Certain aspects of the present disclosure provide a method for processing input data by a configurable nonlinear activation function circuit, including determining a nonlinear activation function for application to input data; determining, based on the determined nonlinear activation function, a set of parameters for a configurable nonlinear activation function circuit; and processing input data with the configurable nonlinear activation function circuit based on the set of parameters to generate output data.

公开(公告)号：US20230185532A1

公开(公告)日：2023-06-15

申请号：US18105159

申请日：2023-02-02

Applicant: QUALCOMM Incorporated

Inventor： Rexford Alan HILL ,  Aaron Douglass LAMB ,  Michael GOLDFARB ,  Amin ANSARI ,  Christopher LOTT

IPC: G06F7/544 ,  G06F5/06

CPC classification number: G06F7/5443 ,  G06F5/06 ,  G06N3/063

Abstract: A method of exploiting activation sparsity in deep neural networks is described. The method includes retrieving an activation tensor and a weight tensor where the activation tensor is a sparse activation tensor. The method also includes generating a compressed activation tensor comprising non-zero activations of the activation tensor, where the compressed activation tensor has fewer columns than the activation tensor. The method further includes processing the compressed activation tensor and the weight tensor to generate an output tensor.

公开(公告)号：US20150095274A1

公开(公告)日：2015-04-02

申请号：US14195988

申请日：2014-03-04

Applicant: QUALCOMM Incorporated

Inventor： Aaron Douglass LAMB

IPC: G06N3/08 ,  G06F7/58

CPC classification number: G06F7/584 ,  G06N3/0472 ,  G06N3/049 ,  G06N3/063

Abstract: Certain aspects of the present disclosure provide methods and apparatus for producing programmable probability distribution function of pseudo-random numbers that can be utilized for filtering (dropping and passing) neuron spikes. The present disclosure provides a simpler, smaller, and lower-power circuit than that typically used. It can be programmed to produce any of a variety of non-uniformly distributed sequences of numbers. These sequences can approximate true probabilistic distributions, but maintain sufficient pseudo-randomness to still be considered random in a probabilistic sense. This circuit can be an integral part of a filter block within an ASIC chip emulating an artificial nervous system.

Abstract translation: 本公开的某些方面提供了用于产生可用于过滤（丢弃和传递）神经元峰值的伪随机数的可编程概率分布函数的方法和装置。 本公开提供了比通常使用的电路更简单，更小和更低功率的电路。 它可以被编程以产生各种不均匀分布的数字序列。 这些序列可以近似真实的概率分布，但是保持足够的伪随机性仍然在概率上被认为是随机的。 该电路可以是模拟人造神经系统的ASIC芯片内的滤波器块的组成部分。

公开(公告)号：US20230185533A1

公开(公告)日：2023-06-15

申请号：US18165802

申请日：2023-02-07

Applicant: QUALCOMM Incorporated

Inventor： Ren LI ,  Prajakt KULKARNI ,  Suren MOHAN ,  Aaron Douglass LAMB

IPC: G06F7/556 ,  G06F7/50

CPC classification number: G06F7/556 ,  G06F7/50

Abstract: Certain aspects of the present disclosure provide a method for processing input data by a set of configurable nonlinear activation function circuits, including generating an exponent output by processing input data using one or more first configurable nonlinear activation function circuits configured to perform an exponential function, summing the exponent output of the one or more first configurable nonlinear activation function circuits, and generating an approximated log softmax output by processing the summed exponent output using a second configurable nonlinear activation function circuit configured to perform a natural logarithm function.

公开(公告)号：US20220004362A1

公开(公告)日：2022-01-06

申请号：US16920242

申请日：2020-07-02

Applicant: QUALCOMM Incorporated

Inventor： Aaron Douglass LAMB

IPC: G06F7/485 ,  G06F7/556 ,  G06F5/01

Abstract: Certain aspects of the present disclosure are directed to methods and apparatus for circular floating point addition. An example method generally includes obtaining a first floating point number represented by a first significand and a first exponent, obtaining a second floating point number represented by a second significand and second exponent, and adding the first floating point number and the second floating point number using a circular accumulator device.