Runtime Code Reordering to Eliminate Processor Interlocks
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Solution Overview
Problem
Existing data processing methods fail to optimize code execution on target processors, particularly when code is compiled for earlier generation processors or is platform-independent, leading to sub-optimal performance due to processor-dependent interlocks.
Innovation Solution
A method that analyzes and reorders code sequences in real-time to remove interlocks by loading the code into a volatile data store, identifying and rearranging it based on the target processor's properties, and executing the reordered code to improve execution efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If code is compiled for earlier generation processors or uses platform-independent code, then code portability and compatibility are improved, but execution performance deteriorates due to processor-dependent interlocks
Solution Approach 1:
The system performs preliminary analysis of the code sequence to identify interlocks before execution, and reorders the code in advance to eliminate these interlocks. This preliminary optimization allows the code to execute efficiently on the target processor without requiring recompilation, thus maintaining portability while improving performance.
Solution Approach 2:
The code reordering is performed dynamically at runtime based on the specific target processor's properties. The system adapts the code sequence to match the characteristics of the executing processor, allowing the same portable code to be optimized for different processor architectures without recompilation.
2Productivity
If code is reordered to optimize for a specific processor, then execution performance is improved, but code complexity increases due to runtime analysis and reordering operations
Solution Approach 1:
The system performs self-optimization by automatically analyzing its own code sequence and reordering it without external intervention. The runtime system identifies interlocks and reorders instructions autonomously, eliminating the need for complex external optimization tools or manual code modification.
Solution Approach 2:
The system changes the execution parameters of the code by reordering instructions based on processor-specific properties. By dynamically adjusting the code sequence parameters to match the target processor's characteristics, the system achieves performance optimization without adding permanent structural complexity.
3Productivity
If code is analyzed and reordered at runtime, then performance optimization for the target processor is achieved, but processing time increases due to analysis overhead
Solution Approach 1:
The system performs partial optimization by focusing only on identifying and removing interlocks in the code sequence, rather than进行全面 optimization. This selective approach reduces the analysis overhead while still achieving significant performance improvements by eliminating the most critical execution stalls.
Data Source
AI summary
A method of reordering a sequence of code for processing by a target data processor in order to reduce an execution time for said code on said target data processor is disclosed. The method comprises the steps of: in response to a request to execute said sequence of code, loading said sequence of code into a volatile data store associated with said target data processor; analyzing said sequence of code in relation to properties of said target data processor; identifying interlocks within said sequence of code when executing on said target data processor, in which a portion of code would be stalled while waiting for an earlier portion to complete; reordering said sequence of code to remove at least some of said interlocks; and executing said reordered sequence of code; wherein said steps of analyzing, identifying, reordering and executing are performed by said target data processor.