Load Store Alias Predictor for RAW Violation Gating
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Solution Overview
Problem
Conventional Out-Of-Order (OOO) microprocessors face inefficiencies due to memory read-after-write (RAW) violations and delays, which result in computational penalties and power costs, as they lack effective means to track dependencies between loads and stores, leading to unnecessary delays and resource wastage.
Innovation Solution
The introduction of a Load Store Alias Predictor (LSAP) and Load Store Hazard Predictor (LSHP) modules that prevent the issuance of loads until their corresponding forwarding stores are ready, making memory dependencies visible to the scheduler and delaying only necessary loads to avoid RAW violations, thereby enhancing instruction-level parallelism and reducing retry-related costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If out-of-order execution is enabled to improve instruction-level parallelism, then productivity is improved, but memory RAW violations occur causing loss of time and computational penalties
Solution Approach 1:
The patent applies preliminary action by checking memory dependencies before issuing load instructions. The load store alias predictor examines prediction tables to determine if a load should wait for a prior store to complete, preventing RAW violations before they occur. This allows the processor to proactively avoid pipeline flushes while maintaining out-of-order execution benefits.
2Reliability
If conventional dependency tracking is used to prevent RAW violations, then reliability is improved, but device complexity increases due to additional tracking mechanisms
Solution Approach 1:
The patent uses copying by creating compact prediction table entries that store essential dependency information (store address tags and distance values) rather than tracking full memory dependency chains. This simplified copy of dependency data enables reliable RAW violation detection while keeping the prediction table structure manageable and efficient.
3Reliability
If loads are delayed to wait for stores to complete, then memory RAW violations are prevented, but productivity decreases due to reduced instruction-level parallelism
Solution Approach 1:
The patent applies partial action by selectively delaying only those load instructions that have confirmed memory dependencies on prior stores, as identified by the load store alias predictor. Loads without dependencies proceed immediately, maintaining instruction-level parallelism. This selective approach prevents unnecessary delays while ensuring reliability for dependent instructions.
4Measurement precision
If prediction tables are used to track aliasing stores, then measurement precision is improved for dependency detection, but loss of information increases due to limited table entries
Solution Approach 1:
The patent applies local quality by making prediction table entries dynamically relevant to the current execution context. Each entry is tailored to specific load-store pairs with matching address patterns, concentrating tracking resources on the most probable dependency cases. This localized approach improves detection precision for relevant cases while managing the limited table size efficiently.
Data Source
AI summary
An apparatus for gating a load instruction is presented. The apparatus includes a memory to store a prediction table including an entry matching the load instruction. The matching entry includes a tag field to identify the load instruction, a distance field to indicate a distance of the load instruction to a prior aliasing store instruction, and a confidence field to indicate a prediction strength. The apparatus further includes a gating circuit operable to perform a look-up for the load instruction in the prediction table to find the matching entry and responsive to a determination of a valid prediction, retrieve a location of the prior aliasing store instruction using a value of the distance field of the matching entry, and perform a gating operation on the load instruction. The apparatus further includes a load store queue operable to provide feedback for updating the matching entry after the load instruction has executed.