Iterator Unit Dynamic Workload Sizing for Data Processing
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Solution Overview
Problem
Existing data processing systems face inefficiencies in task distribution due to reliance on pre-defined parameters, leading to undersized tasks and inefficient use of processing resources, as they do not account for real-time system information such as available cores or storage, resulting in suboptimal processing performance.
Innovation Solution
The system generates workloads with task characteristics dependent on real-time system information, such as core availability and storage status, allowing for dynamic task sizing and distribution to optimize processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-defined parameters are used for task distribution, then task generation is simple and fast, but task sizing is inaccurate and processing efficiency deteriorates
Solution Approach 1:
The system dynamically adjusts task characteristics based on real-time system information. The iterator unit monitors system state (available cores, storage status, component health) and adapts task sizing and distribution parameters accordingly, transitioning from static pre-defined parameters to dynamic adaptive parameters that optimize processing efficiency under varying system conditions.
Solution Approach 2:
The system implements feedback mechanisms where the iterator unit continuously monitors system information and uses this feedback to adjust task generation parameters. The system information storage maintains real-time data about system state, which feeds back into the task generation process to optimize task distribution and sizing based on current system capabilities and conditions.
2Productivity
If real-time system information is used for task generation, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The iterator unit is designed as a multi-functional component that handles multiple responsibilities: monitoring system information, generating tasks, distributing tasks to execution units, and adapting task parameters based on system state. By consolidating these functions in a single versatile unit rather than separate specialized components, the system achieves dynamic task generation without proportionally increasing overall system complexity.
Solution Approach 2:
The system optimizes task generation by dynamically changing task parameters (such as task size, number of tasks, distribution patterns) based on system information. The iterator unit adjusts these parameters in response to system conditions, allowing efficient processing without requiring a completely complex reconfiguration of the entire system architecture.
3Productivity
If tasks are sized based on pre-defined parameters, then task generation is straightforward, but resource utilization becomes inefficient
Solution Approach 1:
Task sizing transitions from static pre-defined values to dynamic values that adapt to real-time system conditions. The iterator unit adjusts task characteristics based on available resources, ensuring that tasks are sized appropriately to maximize resource utilization and minimize idle time as system conditions change during operation.
Solution Approach 2:
The system performs self-optimization where the iterator unit automatically adjusts task generation parameters based on monitored system information without external intervention. The system serves itself by using its own system information to optimize its task distribution, reducing idle time and improving resource utilization through autonomous adaptive behavior.
Data Source
AI summary
According to the present techniques there is provided a method of operating a data processor unit to generate processing tasks: the data processor unit comprising: a control circuit to receive, from a host processor unit, a request for the data processor unit to perform a processing job; an iterator unit to process the request and generate a workload comprising one or more tasks for the requested job; one or more execution units to perform the one or more tasks; storage to store system information indicative of a status of at least one component of the data processor unit; the method comprising: receiving, at the control circuit, a first request to perform a first processing job; processing, at the iterator unit, the first request and generating a workload comprising one or more tasks for the first processing job based on or in response to the system information in storage, wherein at least one characteristic of the workload is dependent on the system information.