Shared Prediction Resource Allocation for Multi-Type Prediction Units
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Solution Overview
Problem
Existing prediction units in processing circuitry, while improving performance, incur significant resource and power consumption overheads, especially when multiple types are implemented simultaneously.
Innovation Solution
Implementing a system with shared prediction resources and resource allocation circuitry to dynamically allocate resources to prediction units based on their sensitivity and current processing conditions, optimizing overall performance without increasing total resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple types of prediction units are implemented simultaneously, then prediction functionality and processing performance are improved, but resource usage and power consumption increase
Solution Approach 1:
Multiple prediction units of different types share common prediction resources (such as prediction buffers, lookup tables, and control logic) through a unified resource allocation mechanism. The resource allocation circuitry dynamically assigns shared resources to different prediction units based on current processing needs, allowing multiple prediction functions to coexist without requiring separate dedicated resources for each unit.
Solution Approach 2:
The system employs dynamic resource allocation where the resource allocation circuitry continuously monitors processing conditions and adjusts the distribution of shared prediction resources among different prediction units in real-time. This dynamic adjustment allows the system to optimize resource utilization based on current workload requirements, ensuring that resources are allocated to the most needed prediction units at any given time.
2Productivity
If multiple types of prediction units are implemented simultaneously, then prediction functionality is improved, but power consumption increases
Solution Approach 1:
Multiple prediction units share common prediction resources including prediction buffers, lookup tables, and control logic through a unified resource allocation mechanism. This merging of resources reduces the total hardware footprint and associated power consumption compared to having separate dedicated resources for each prediction unit type.
Solution Approach 2:
The resource allocation circuitry periodically adjusts the distribution of shared prediction resources based on monitoring processing conditions over time. This periodic reallocation ensures that resources are activated only when needed by active prediction units, reducing idle power consumption while maintaining prediction functionality when required.
3Ease of operation
If dedicated resources are allocated to each prediction unit, then each unit operates independently, but overall resource utilization efficiency decreases
Solution Approach 1:
The prediction resource system is segmented into shared prediction resources that can be dynamically allocated to different prediction units. The resource allocation circuitry divides and manages these shared resources based on the specific needs of each prediction unit, allowing for flexible allocation while maintaining the operational independence of each prediction unit through controlled access to shared resources.
Solution Approach 2:
The system transitions from static dedicated resource allocation to dynamic shared resource allocation. The resource allocation circuitry continuously monitors processing conditions and adjusts resource distribution in real-time, allowing prediction units to access shared resources based on actual demand. This dynamic approach optimizes resource utilization efficiency while preserving the operational independence of each prediction unit through controlled access mechanisms.
Data Source
AI summary
Aspects of the present disclosure relate to apparatus comprising prediction circuitry comprising a plurality of prediction units, said plurality comprising a plurality of types of prediction unit. Each prediction unit is configured to perform a corresponding type of prediction in respect of operations that are to be executed by the apparatus. Shared prediction resource circuitry comprises shared prediction resources configurable to perform said types of prediction. Resource allocation circuitry is configured to determine an allocation of said shared prediction resources to one or more of said plurality of prediction units, and allocate the shared prediction resources according to the determination.