Prefetch Request Dropping Based on Source Accuracy
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Solution Overview
Problem
Existing prefetch-dropping mechanisms in computer systems fail to distinguish between accurate and inaccurate prefetches, leading to reduced system performance as they drop both types using the same criteria, which can result in delaying actual demand requests and consuming valuable memory bandwidth.
Innovation Solution
A method that selectively drops prefetch requests based on accuracy information for different prefetch sources, using accuracy values calculated from the ratio of useless to prefetched lines to determine occupancy thresholds and temporarily disable low-accuracy prefetch sources, thereby optimizing prefetch dropping and reducing cache pollution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If prefetch requests are dropped based on simple occupancy threshold, then cache pollution is reduced, but accurate prefetches are also dropped and processor performance deteriorates
Solution Approach 1:
The patent applies local quality by differentiating prefetch sources into multiple categories (e.g., stream-based, pattern-based, random) and applying different occupancy thresholds to each category. This allows the system to treat different prefetches differently based on their specific characteristics and accuracy profiles, rather than applying a uniform threshold to all prefetches.
Solution Approach 2:
The patent implements dynamics by making the occupancy threshold adaptive rather than fixed. The threshold is dynamically adjusted based on the measured accuracy of each prefetch source, allowing the system to optimize prefetch dropping behavior in real-time based on actual performance data and changing workload conditions.
2Loss of energy
If all prefetch requests are dropped to reduce cache pollution, then memory bandwidth consumption decreases, but useful prefetches are lost and demand request latency increases
Solution Approach 1:
The patent applies local quality by categorizing prefetch sources and applying selective dropping based on source type and measured accuracy. High-accuracy prefetch sources maintain lower occupancy thresholds while low-accuracy sources have higher thresholds, ensuring that useful prefetches from reliable sources are retained while discarding useless ones.
Solution Approach 2:
The patent implements feedback by measuring the accuracy of each prefetch source through monitoring hit rates and occupancy patterns, then using this feedback information to adjust occupancy thresholds and dropping decisions. This closed-loop approach continuously optimizes the balance between prefetch utility and resource consumption.
3Stability of the object's composition
If occupancy threshold is set low to prevent cache pollution, then cache freshness is maintained, but valid prefetches are dropped and processor stalls increase
Solution Approach 1:
The patent applies dynamics by making the occupancy threshold adaptive based on measured prefetch accuracy. The system continuously monitors cache behavior and adjusts thresholds dynamically, allowing lower thresholds for high-accuracy prefetch sources that maintain cache freshness while preventing drops for low-accuracy sources that would cause unnecessary stalls.
Solution Approach 2:
The patent implements parameter changes by adjusting the occupancy threshold parameter based on the accuracy characteristics of different prefetch sources. Different sources receive different threshold values as parameters, allowing the system to optimize both cache freshness and processor performance by matching threshold strictness to prefetch reliability.
Data Source
AI summary
The disclosed embodiments relate to a system that selectively drops a prefetch request at a cache. During operation, the system receives the prefetch request at the cache. Next, the system identifies a prefetch source for the prefetch request, and then uses accuracy information for the identified prefetch source to determine whether to drop the prefetch request. In some embodiments, the accuracy information includes accuracy information for different prefetch sources. In this case, determining whether to drop the prefetch request involves first identifying a prefetch source for the prefetch request, and then using accuracy information for the identified prefetch source to determine whether to drop the prefetch request.