Dynamic Hardware Resource Addition for Neural Network Learning

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

In neural network learning processes, users face challenges in intuitively adding hardware resources when the learning does not progress as expected, necessitating a technology to dynamically enhance resources during the learning process.

Innovation Solution

An information processing device with a display control unit that shows the learning process progress and an addition button, allowing users to dynamically add a second hardware resource to a first hardware resource executing the learning process, enabling intuitive resource augmentation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If hardware resources are increased to improve learning process speed, then productivity is improved, but device complexity increases

Engineering Contradiction:

Improvelearning process speedVSAvoidhardware resource management complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system dynamically adjusts hardware resources during the learning process based on real-time progress monitoring. The display control unit presents addition buttons that allow users to add computation nodes on-demand, transforming static resource allocation into dynamic adaptation. This resolves the contradiction by enabling productivity improvement through resource scaling while maintaining operational simplicity through automated presentation of addition options.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The display control unit provides continuous feedback on learning process progress to the user. By monitoring and displaying learning status, the system enables informed decision-making about when to add hardware resources. This feedback mechanism resolves the contradiction by allowing productivity optimization based on actual learning progress while keeping device complexity manageable through user-guided resource addition.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If hardware resources are added dynamically during learning process, then adaptability is improved, but device complexity increases

Engineering Contradiction:

Improveresource scalabilityVSAvoidresource management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements self-service by automatically presenting addition buttons to users based on monitored learning progress. Instead of requiring users to manually configure complex resource management settings, the system autonomously determines when resource addition is beneficial and presents simple addition options. This resolves the contradiction by enabling adaptability through on-demand resource scaling while maintaining ease of operation through automated decision-support.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The resource allocation system transitions from static pre-configuration to dynamic on-demand adjustment. The display control unit adaptively presents addition buttons during the learning process, allowing the system to scale resources according to actual needs. This dynamic approach resolves the contradiction by improving adaptability while keeping device complexity manageable through automated resource management protocols.

Inventive Principle:

Principle #15Dynamics

3Productivity

If more hardware resources are allocated to learning process, then learning process efficiency is improved, but loss of energy increases

Engineering Contradiction:

Improvelearning process efficiencyVSAvoidcomputation resource energy consumption

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system applies partial action by adding hardware resources incrementally through addition buttons rather than allocating maximum resources upfront. The display control unit presents options to add computation nodes based on actual learning progress, allowing the system to use only the necessary amount of energy for achieving the desired learning outcomes. This resolves the contradiction by improving learning efficiency through targeted resource allocation while minimizing energy loss through avoidance of excessive resource provisioning.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11086678B2Information processing device, method of processing information, and method of providing information

Publication Date: 2021.08.10 SONY GROUP CORP

AI summary

There is provided an information processing device capable of intuitively adding a hardware resource intended to execute the learning, the information processing device including: a display control unit configured to control display of information indicating progress of a learning process and an addition button used to add dynamically a second hardware resource intended to execute the learning process to a first hardware resource on which the learning process is being executed.