Cache Arbitration for Prefetch Requests
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Solution Overview
Problem
Conventional processor cache arbitration schemes, such as round-robin, inefficiently utilize cache resources, leading to reduced instruction throughput and unnecessary power consumption due to concurrent demand and prefetch requests, where prefetch hits consume time and energy without reducing demand request latency.
Innovation Solution
Implementing a prefetch prediction module that de-prioritizes prefetch requests predicted to hit the cache, discarding them from the pending queue, and adjusting arbitration priorities to favor demand requests and prefetch misses, thereby optimizing cache utilization and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple arbitration schemes like round-robin are used to select memory access requests, then the arbitration process is simple and easy to implement, but cache utilization is inefficient and instruction throughput is reduced
Solution Approach 1:
The arbitration scheme transitions from static round-robin to dynamic priority-based arbitration. The arbiter dynamically adjusts request priorities based on real-time cache state information (hit/miss predictions) and request types (demand vs. prefetch), allowing the system to adapt to varying workload conditions and maximize cache utilization while maintaining implementation feasibility.
Solution Approach 2:
The system changes the arbitration parameter from fixed round-robin selection to variable priority levels. By introducing priority as a dynamic parameter that can be adjusted based on request characteristics and cache predictions, the arbitration process becomes more efficient without requiring complete redesign of the arbitration logic.
2Productivity
If prefetch requests are processed concurrently with demand requests, then the cache can service prefetch operations, but power consumption increases unnecessarily due to prefetch hits
Solution Approach 1:
The system discards prefetch requests that are predicted to result in cache hits, as these requests would not bring new data into the cache and would only consume power. The arbiter uses priority assignment to effectively discard low-value prefetch requests (those likely to hit) while maintaining service for high-value requests (demand requests and prefetch requests likely to miss).
Solution Approach 2:
The harmful element (unnecessary prefetch requests that would hit in cache) is extracted and removed from the arbitration process. By identifying and separating these low-value requests from the main arbitration pool, the system eliminates their negative impact on power consumption while preserving the functionality of processing necessary prefetch requests.
3Adaptability or versatility
If prefetch requests are given equal priority with demand requests, then all requests are treated equally, but demand request latency increases as cache ports are occupied by prefetch requests
Solution Approach 1:
Different priority levels are assigned to different types of requests based on their characteristics and urgency. Demand requests receive higher priority to ensure timely service, while prefetch requests receive lower priority. This local differentiation in treatment allows the system to maintain fairness in the sense that each request type receives appropriate attention based on its needs, while minimizing impact on critical demand requests.
Solution Approach 2:
The arbitration system uses feedback from cache predictions (hit/miss predictions) to dynamically adjust request priorities. This feedback mechanism allows the arbiter to make informed decisions about which requests to service first, ensuring that demand requests are not blocked by prefetch requests that would not result in cache hits, thereby reducing demand request latency.
Data Source
AI summary
A processor employs a prefetch prediction module that predicts, for each prefetch request, whether the prefetch request is likely to be satisfied from (“hit”) the cache. The arbitration priority of prefetch requests that are predicted to hit the cache is reduced relative to demand requests or other prefetch requests that are predicted to miss in the cache. Accordingly, an arbiter for the cache is less likely to select prefetch requests that hit the cache, thereby improving processor throughput.