A broadcast subsystem of a processor system includes: a set of broadcast buses, each broadcast bus in the set of broadcast buses electrically coupled to a subset of primary memory units in the set of primary memory units; a primary memory unit queue: configured to store a first set of data transfer requests associated with the set of primary memory units; electrically coupled to the data buffer a broadcast scheduler: electrically coupled to the primary memory unit queue; electrically coupled to the set of broadcast buses; and configured to transfer source data from the data buffer to a target subset of primary memory units in the set of primary memory units via the set of broadcast buses based on the set of data transfer requests stored in the primary memory unit queue.
G06N 3/10 - Interfaces, langages de programmation ou boîtes à outils de développement logiciel, p. ex. pour la simulation de réseaux neuronaux
G06F 13/16 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus de mémoire
G06F 13/28 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus d'entrée/sortie utilisant le transfert par rafale, p. ex. acces direct à la mémoire, vol de cycle
G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
A broadcast subsystem of a processor system includes: a set of broadcast buses, each broadcast bus in the set of broadcast buses electrically coupled to a subset of primary memory units in the set of primary memory units; a primary memory unit queue: configured to store a first set of data transfer requests associated with the set of primary memory units; electrically coupled to the data buffer a broadcast scheduler: electrically coupled to the primary memory unit queue; electrically coupled to the set of broadcast buses; and configured to transfer source data from the data buffer to a target subset of primary memory units in the set of primary memory units via the set of broadcast buses based on the set of data transfer requests stored in the primary memory unit queue.
G06N 3/10 - Interfaces, langages de programmation ou boîtes à outils de développement logiciel, p. ex. pour la simulation de réseaux neuronaux
G06F 13/16 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus de mémoire
G06F 13/28 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus d'entrée/sortie utilisant le transfert par rafale, p. ex. acces direct à la mémoire, vol de cycle
G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
A method includes: accessing a static schedule of a target neural network for execution by a processing device, the target neural network including a set of layers; generating a set of expected performance metrics of the target neural network based on the static schedule, the set of expected performance metrics including a first expected performance metric for a first layer in the set of layers; accessing a set of runtime performance metrics captured during execution of the target neural network by the processing device, the set of runtime performance metrics including a first runtime performance metric for the first layer; and, in response to detecting a difference between the first runtime performance metric and the first expected performance metric exceeding a threshold, serving an alert at a user interface.
A method includes: accessing a static schedule of a target neural network for execution by a processing device, the target neural network including a set of layers; generating a set of expected performance metrics of the target neural network based on the static schedule, the set of expected performance metrics including a first expected performance metric for a first layer in the set of layers; accessing a set of runtime performance metrics captured during execution of the target neural network by the processing device, the set of runtime performance metrics including a first runtime performance metric for the first layer; and, in response to detecting a difference between the first runtime performance metric and the first expected performance metric exceeding a threshold, serving an alert at a user interface.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Microprocessors; integrated circuit modules; multichip
modules; downloadable computer software development tools;
downloadable software development kits (SDKs); downloadable
proxy software; downloadable computer software; all of the
foregoing for use in edge computing, fog computing,
decentralized computing, Internet of Things, artificial
intelligence, machine learning, deep learning, image feature
extraction, predictive analytics, software development, high
performance computing and computer and telecommunication
networks. Development and implementation of computer software,
computer hardware and technology solutions for edge AI
applications for the purpose of low power consumption and
highly efficient AI computing and distributed device
management; consulting services in the fields of artificial
intelligence and edge computing.
6.
A PROCESSOR SYSTEM AND METHOD FOR INCREASING DATA-TRANSFER BANDWIDTH DURING EXECUTION OF A SCHEDULED PARALLEL PROCESS
A broadcast subsystem of a processor system includes: a set of broadcast buses, each broadcast bus in the set of broadcast buses electrically coupled to a subset of primary memory units in the set of primary memory units; a primary memory unit queue: configured to store a first set of data transfer requests associated with the set of primary memory units; and electrically coupled to the data buffer a broadcast scheduler: electrically coupled to the primary memory unit queue; electrically coupled to the set of broadcast buses; and configured to transfer source data from the data buffer to a target subset of primary memory units in the set of primary memory units via the set of broadcast buses based on the set of data transfer requests stored in the primary memory unit queue.
Disclosed herein is a processor for deep learning. In one embodiment, the processor comprises: a load and store unit configured to load and store image pixel data and stencil data; a register unit, implementing a banked register file, configured to: load and store a subset of the image pixel data from the load and store unit, and concurrently provide access to image pixel values stored in a register file entry of the banked register file, wherein the subset of the image pixel data comprises the image pixel values stored in the register file entry; and a plurality of arithmetic logic units configured to concurrently perform one or more operations on the image pixel values stored in the register file entry and corresponding stencil data of the stencil data.
G06K 9/56 - Combinaisons de fonctions de prétraitement en utilisant un opérateur local, c. à d. des moyens pour opérer sur un point image élémentaire en fonction des éléments situés à proximité immédiate de ce point
G06T 5/20 - Amélioration ou restauration d'image utilisant des opérateurs locaux
