Window-Based Memory Dependency Predictor for Out-of-Order Loads
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Solution Overview
Problem
Existing systems struggle with accurately tracking multiple memory dependencies in out-of-order execution scenarios, leading to inefficient pipeline flushes and performance degradation due to incorrect load instruction execution.
Innovation Solution
A window-based dependency predictor is used to track multiple store instructions dependencies for a load instruction, employing a pointer to the youngest store and a bit-vector to minimize computational overhead, ensuring accurate execution order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If out-of-order execution is employed to improve processing efficiency, then overall processing time is reduced, but pipeline flush operations become necessary when dependencies are violated, causing performance degradation
Solution Approach 1:
The patent applies preliminary action by performing dependency tracking and validation before executing load instructions out of order. The system pre-establishes a window of N store instructions and uses bit-vectors to mark dependencies, allowing the processor to proactively identify and prevent dependency violations before they occur, thereby avoiding costly pipeline flush operations while maintaining out-of-order execution benefits
2Reliability
If multiple store dependencies are tracked accurately, then load instruction execution correctness is improved, but computational overhead increases
Solution Approach 1:
The patent segments the dependency tracking problem by dividing it into two components: a window counter that tracks the number of stores in the window, and bit-vectors that efficiently represent dependency relationships. This segmentation allows the system to track multiple store dependencies accurately while keeping the computational overhead manageable through efficient data structure design
Solution Approach 2:
The patent uses bit-vectors as a compact representation (copy) of dependency information. Instead of storing full dependency metadata for each store instruction, the system creates a bit-vector copy that efficiently encodes which stores within the window are dependencies for a load instruction, significantly reducing memory usage and computational overhead while maintaining complete dependency tracking accuracy
3Measurement precision
If a window of N stores is tracked with a pointer and bit-vector, then dependency tracking precision is improved, but storage requirements increase
Solution Approach 1:
The patent changes the parameter representation from storing complete dependency metadata to using a compact bit-vector encoding. Each bit in the vector represents whether a particular store in the window is a dependency, transforming the storage requirement from proportional to the number of dependencies to proportional to the window size N, achieving O(N) storage efficiency while maintaining full tracking precision
Data Source
AI summary
Methods and systems for out of order processing are disclosed herein. A disclosed method for out-of-order instruction processing includes identifying a first load instruction for processing, determining, based on the first load instruction, whether a store instruction window has been established for the first load instruction, confirming, when the store instruction window has been established, that one or more store instructions, within the store instruction window, that the first load instruction is dependent upon have been executed, and executing the first load instruction after execution of the one or more store instructions has been confirmed.