Multi-Level TLB Prefetcher Feedback for Lower Miss Rates
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Solution Overview
Problem
Existing translation lookaside buffer (TLB) systems suffer from inefficiencies due to high rates of TLB misses, which require time-consuming page walks and hinder processor performance, as they lack effective prefetching mechanisms to anticipate and populate TLB entries.
Innovation Solution
A TLB prefetcher with multi-level prefetches and feedback architecture that trains on demand request patterns to proactively fill TLB entries, using a state machine to manage and adjust prefetch distances based on confirmation and miss queue feedback, enabling efficient memory access by sending L1 and L2 TLB prefetches dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a TLB prefetcher is implemented to reduce TLB misses, then memory access performance is improved, but device complexity increases
Solution Approach 1:
The prefetcher is divided into multiple independent components including a state machine for pattern detection, a prefetch issue queue for managing prefetch requests, and multi-level prefetch buffers. Each component operates independently but coordinates through standardized interfaces, reducing overall system complexity while maintaining high performance
Solution Approach 2:
The patent implements a hierarchical prefetcher structure where L1 TLB prefetches are nested within L2 TLB prefetches, which are in turn nested within higher-level prefetching mechanisms. This nested architecture allows each level to handle specific aspects of address translation while leveraging the work of lower levels, improving performance without proportionally increasing complexity
2Reliability
If multi-level TLB prefetches are implemented, then TLB miss reduction is improved, but device complexity increases
Solution Approach 1:
The prefetcher performs preliminary actions by detecting access patterns and issuing prefetch requests before actual TLB misses occur. The state machine monitors demand requests and proactively populates TLB entries in advance, ensuring high hit rates without requiring complex real-time response mechanisms
Solution Approach 2:
The patent implements feedback mechanisms where the prefetcher monitors the effectiveness of its prefetch requests and adjusts its behavior accordingly. Hit/miss information from TLB operations feeds back to the state machine and prefetch issue queue, enabling dynamic optimization of prefetch parameters and pattern detection without manual intervention
3Loss of time
If adaptive prefetch distance adjustment is implemented, then memory latency hiding is improved, but device complexity increases
Solution Approach 1:
The prefetch distance is made dynamic rather than fixed, allowing the system to adapt to varying access patterns and workload characteristics. The state machine adjusts prefetch distances based on detected stride patterns and access frequency, optimizing latency hiding without requiring complex external control mechanisms
Data Source
AI summary
Described is a translation lookaside buffer (TLB) prefetcher with multi-level TLB prefetches and feedback architecture. A processing system includes two or more translation lookaside buffer (TLB) levels, each TLB level including a miss queue, and a TLB prefetcher connected to each of the two or more TLB levels. The TLB prefetcher configured to receive feedback from the miss queue at each TLB level for previously sent TLB prefetches and control number of TLB prefetches sent for a trained TLB entry to each TLB level of the two or more TLB levels based on the feedback.