公开(公告)号：GB2606600A

公开(公告)日：2022-11-16

申请号：GB202116839

申请日：2021-11-23

Applicant: IBM

Inventor： JUN SAWADA ,  MYRON D FLICKNER ,  ANDREW STEPHEN CASSIDY ,  JOHN VERNON ARTHUR ,  PALLAB DATTA ,  DHARMENDRA S MODHA ,  STEVEN KYLE ESSER ,  BRIAN SEISHO TABA ,  JENNIFER KLAMO ,  RATHINAKUMAR APPUSWAMY ,  FILIPP AKOPYAN ,  CARLOS ORTEGA OTERO

IPC: G06N3/04 ,  G06N3/063

Abstract: A neural inference chip is provided, including at least one neural inference core. The at least one neural inference core is adapted to apply a plurality of synaptic weights to a plurality of input activations to produce a plurality of intermediate outputs. The at least one neural inference core comprises a plurality of activation units configured to receive the plurality of intermediate outputs and produce a plurality of activations. Each of the plurality of activation units is configured to apply a configurable activation function to its input. The configurable activation function has at least a re-ranging term and a scaling term, the re-ranging term determining the range of the activations and the scaling term determining the scale of the activations. Each of the plurality of activations units is configured to obtain the re-ranging term and the scaling term from one or more look up tables.

公开(公告)号：GB2604963A

公开(公告)日：2022-09-21

申请号：GB202114617

申请日：2021-10-13

Applicant: IBM

Inventor： ALEXANDER ANDREOPOULOS ,  DHARMENDRA S MODHA ,  CARMELO DI NOLFO ,  MYRON D FLICKNER ,  ANDREW STEPHEN CASSIDY ,  BRIAN SEISHO TABA ,  PALLAB DATTA ,  RATHINAKUMAR APPUSWAMY ,  JUN SAWADA

IPC: G06N3/063 ,  G06F30/3308 ,  G06N3/04

Abstract: Simulation and validation of neural network systems is provided. In various embodiments, a description of an artificial neural network is read. A directed graph is constructed comprising a plurality of edges and a plurality of nodes, each of the plurality of edges corresponding to a queue and each of the plurality of nodes corresponding to a computing function of the neural network system. A graph state is updated over a plurality of time steps according to the description of the neural network, the graph state being defined by the contents of each of the plurality of queues. Each of a plurality of assertions is tested at each of the plurality of time steps, each of the plurality of assertions being a function of a subset of the graph state. Invalidity of the neural network system is indicated for each violation of one of the plurality of assertions.