Run-time Program Translation for Complex Processor Pipelines
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Solution Overview
Problem
Current methods for translating code for complex processor pipelines either result in reduced performance due to complete emulation or high implementation complexity and cost with global analysis, failing to effectively handle dynamic pipeline states.
Innovation Solution
The method involves determining a current target address and pipeline signature, looking up a corresponding entry in a translation cache, and generating translations based on static pipeline states, allowing for efficient and simple code translation by moving dynamic pipeline state management into the cache lookup process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complete pipeline emulation is used at all times, then code translation correctness is ensured, but processor performance is reduced
Solution Approach 1:
The patent applies dynamics by making the translation approach adaptive rather than static. The system dynamically switches between complete pipeline emulation and simplified translation based on the detected pipeline state. When the pipeline is in a stable state matching cached signatures, simplified translation is used; when instability is detected, complete emulation takes over, ensuring correctness while optimizing performance.
Solution Approach 2:
The patent changes the parameter of translation complexity based on pipeline state. By monitoring pipeline state signatures and comparing them against cached translations, the system adjusts the translation approach parameter - using full emulation only when necessary (parameter = high complexity) and simplified translation when pipeline state is stable (parameter = low complexity).
2Productivity
If global analysis approach is used for entire program, then translation performance is increased, but implementation complexity and translation cost increase
Solution Approach 1:
The patent segments the translation problem into manageable parts by dividing it into basic blocks with identifiable entry and exit points. Instead of analyzing the entire program globally, the system performs localized translation on individual basic blocks, caching results based on pipeline state signatures at block boundaries. This segmentation reduces implementation complexity while maintaining performance benefits.
Solution Approach 2:
The patent applies preliminary action by pre-computing and caching translations for basic blocks under specific pipeline state conditions. The system performs translation work in advance during idle periods or when pipeline states are stable, storing results in a cache that can be quickly retrieved during execution, thereby improving runtime performance without requiring complex real-time analysis.
3Productivity
If pipeline depth is increased to improve throughput, then instruction throughput increases, but code execution becomes more affected by dynamic pipeline state
Solution Approach 1:
The patent uses copying by creating and storing copies of translation results in a cache, keyed by pipeline state signatures. Instead of managing the complexity of deep pipeline states directly during execution, the system captures pipeline state information, creates cached translations for each state signature, and retrieves pre-computed copies during runtime. This copying approach allows deep pipelines to achieve high throughput while managing state complexity through pre-computation and caching.
Data Source
AI summary
Simplification of run-time program translation for emulating complex processor pipelines is disclosed. Dynamic pipeline states are moved into a cache lookup process leaving a code translation process to deal only with static pipeline states. With dynamic pipeline states removed from the translation process, translation becomes more simple and efficient like that of a non-pipelined processor.