Local Device Cluster Task Processing for GPU-Limited Workloads
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Solution Overview
Problem
The challenge of completing tasks requiring large computing power is exacerbated by the limitations of local GPUs in personal computers, as existing solutions like NV-Link, client-edge cloud architectures, and Docker containers face hardware constraints, high costs, and security issues.
Innovation Solution
A task processing method that establishes a device cluster among multiple electronic devices, allowing for the distribution of processing tasks across these devices, utilizing their combined computing resources to handle tasks that exceed the capabilities of a single device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If local GPU computing power is used, then data security is maintained, but computing power requirements cannot be satisfied
Solution Approach 1:
The patent segments the computing task into multiple parts and distributes them across multiple electronic devices in a cluster. Each device processes a portion of the task locally, maintaining data security while collectively providing sufficient computing power through distributed processing.
Solution Approach 2:
The patent combines the computing resources of multiple electronic devices into a unified cluster system. By merging local GPU resources across devices, the system achieves enhanced computing power while keeping data processing distributed and secure across the network.
2Power
If cloud computing is used, then computing power requirements are satisfied, but cloud fees increase
Solution Approach 1:
The patent enables electronic devices to serve each other's computing needs through peer-to-peer task distribution. Instead of relying on external cloud services, the system uses its own distributed resources to satisfy computing power requirements, eliminating cloud fees while maintaining adequate processing capability.
3Power
If NV-Link technology is used, then computing power is enhanced, but hardware constraints increase
Solution Approach 1:
The patent introduces a task management system as an intermediary that coordinates computing tasks across devices through software-based communication protocols. This approach achieves enhanced computing power without requiring specialized hardware interconnects like NV-Link, thereby reducing hardware constraints and improving system compatibility.
4Productivity
If Docker containers are used, then task distribution is enabled, but security issues arise
Solution Approach 1:
The patent segments tasks into executable units that can be distributed across devices while maintaining local execution environments. This segmentation enables task distribution similar to Docker containers but avoids the security vulnerabilities associated with containerization by keeping processing distributed and isolated across separate electronic devices rather than within a shared system.
Data Source
AI summary
A task processing method includes: in response to a first electronic device in a target device cluster obtaining a target processing task triggered by a target application, establishing a target communication connection with at least one second electronic device determined from the target device cluster; and sending a first part of the target processing task to the at least one second electronic device through the target communication connection, such that the at least one second electronic device processes the first part of the target processing task. The first part of the target processing task is the remaining task in the target processing task except a second part of the target processing task processed by the first electronic device, and the target device cluster is a resource cluster including multiple electronic devices.