Task Distribution Management for Heterogeneous Computing Devices
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Solution Overview
Problem
Existing systems face challenges in efficiently managing and distributing tasks across heterogeneous groups of computing devices with disparate attributes, such as processing speed and network bandwidth, to ensure accurate and efficient task execution.
Innovation Solution
A task-distribution management system that utilizes a task-distribution management module to manage tasks across heterogeneous computing devices, including a task management module, template management module, task-processing rule module, and task-execution system management module, which assesses and allocates tasks based on device capabilities and performance metrics to ensure efficient and accurate results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tasks are distributed across heterogeneous computing devices with disparate attributes, then task execution efficiency and accuracy are improved, but system complexity increases
Solution Approach 1:
The patent introduces a task distribution management system as an intermediary layer between task sources and heterogeneous computing devices. This mediator handles task allocation, device selection, and result aggregation, thereby improving task execution efficiency while abstracting away the complexity of heterogeneous device management from end users and task sources.
Solution Approach 2:
The task distribution management system provides universal functionality that works across diverse computing devices with different attributes. It implements a unified task distribution protocol and device evaluation mechanism that can handle various device types (CPU, GPU, FPGA, etc.) without requiring device-specific customization, thus improving productivity while managing complexity through standardization.
2Reliability
If tasks are distributed to multiple task-execution systems, then task processing accuracy is improved through assessment and validation, but communication overhead and time consumption increase
Solution Approach 1:
The patent implements a mechanism where tasks are distributed to multiple execution systems, but not all results need to be fully processed. The system uses assessment rules to evaluate results partially - accepting results that meet confidence thresholds while potentially discarding or reprocessing only those that don't. This approach improves reliability by validating results while reducing time consumption by avoiding unnecessary processing of already-sufficient results.
Solution Approach 2:
The system implements feedback mechanisms where task execution results are assessed against predefined rules and confidence thresholds. Based on this feedback, the system can determine whether additional execution is needed or if the current results are sufficient. This feedback loop improves task processing accuracy while optimizing time consumption by preventing redundant execution cycles.
Data Source
AI summary
Particular embodiments manage distribution of tasks to heterogeneous group of computing devices is disclosed. Computing devices in the group may have disparate attributes that may affect handling of a specific task (e.g., processing speed, network bandwidth, GPU availability, utilization, type of operating system, availability of certain utilities). Tasks may be received from task-requester computer systems, and each task may be associated with an information set. This information set may comprise a description of the task, a token to be provided for completion of the task, and at least one task-processing rule for a task result provided by one or more computing devices involved in handling the task. Task results are received and compared to the task-processing rule until the task-processing rule is satisfied.