Processing

Please wait...

Settings

Settings

Goto Application

1. WO2020169182 - METHOD AND APPARATUS FOR ALLOCATING TASKS

Publication Number WO/2020/169182
Publication Date 27.08.2020
International Application No. PCT/EP2019/054078
International Filing Date 19.02.2019
IPC
G06N 3/04 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
G06N 3/08 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
G06N 3/00 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
G06N 7/00 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
G06F 9/50 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
46Multiprogramming arrangements
50Allocation of resources, e.g. of the central processing unit
CPC
G06F 9/5044
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
46Multiprogramming arrangements
50Allocation of resources, e.g. of the central processing unit [CPU]
5005to service a request
5027the resource being a machine, e.g. CPUs, Servers, Terminals
5044considering hardware capabilities
G06N 3/006
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
004Artificial life, i.e. computers simulating life
006based on simulated virtual individual or collective life forms, e.g. single "avatar", social simulations, virtual worlds or particle swarm optimisation
G06N 3/04
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
G06N 3/08
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
G06N 7/005
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
005Probabilistic networks
Applicants
  • NOKIA SOLUTIONS AND NETWORKS OY [FI]/[FI]
Inventors
  • AIT AOUDIA, Faycal
  • ENRICI, Andrea
Agents
  • NOVAGRAAF TECHNOLOGIES
Priority Data
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) METHOD AND APPARATUS FOR ALLOCATING TASKS
(FR) PROCÉDÉ ET APPAREIL D'ATTRIBUTION DE TÂCHE
Abstract
(EN) An apparatus (100) and method (500) for allocating tasks (v) in a program to hardware units (u) in a target platform is described. A state (st) is input into a system (110) that includes an algorithm (120) having at least some trainable weights. The state (st) comprises a representation of the program (G) and hardware resource data (H) indicating an amount of resource types available to each hardware unit on the target platform (P). Performance value estimates (qi) for allocations (ai) of tasks (vi) to hardware units (ui) are determined by the algorithm (120) having at least some trainable weights from the state (st). A task is allocated to a hardware unit according to the determined performance value estimates.
(FR) L'invention concerne un appareil (100) et un procédé (500) permettant d'attribuer des tâches (v) dans un programme à des unités matérielles (u) dans une plateforme cible. Un état (st) est entré dans un système (110) qui comprend un algorithme (120) ayant au moins certains poids d'apprentissage. L'état (st) comprend une représentation du programme (G) et des données de ressources matérielles (H) indiquant une quantité de types de ressources disponibles pour chaque unité matérielle sur la plateforme cible (P). Des estimations de valeur de performance (qi) pour des attributions (ai) de tâches (vi) à des unités matérielles (ui) sont déterminées par l'algorithme (120) ayant au moins certains poids d'apprentissage à partir de l'état (st). Une tâche est attribuée à une unité matérielle selon les estimations de valeur de performance déterminées.
Latest bibliographic data on file with the International Bureau