Shadow Memory JIT Compilation for Non-Native Instruction Execution
Solution Overview
Problem
Dynamic translation systems face inefficiencies due to the time required to translate non-native instructions into native instructions during runtime, as they involve retrieval and parsing of instructions, which can lead to overhead in decoding processes.
Innovation Solution
A method and system that utilize a shadow memory to store precompiled code fragments corresponding to non-native instructions, allowing for direct execution from the shadow memory during subsequent passes, reducing the need for repeated parsing and interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic translation is used to translate non-native instructions to native instructions during runtime, then the system can execute non-native code without pre-compilation, but the translation time and processing overhead increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-compiling non-native code segments into native code before execution. The system identifies non-native code regions, compiles them to native instructions in advance, and stores the compiled code for direct execution, eliminating the need for time-consuming runtime translation of each instruction.
Solution Approach 2:
The patent implements dynamics by dynamically determining which code segments require compilation based on execution context. The system uses heuristics to identify candidate non-native code regions, selectively compiles them based on predicted execution frequency and characteristics, and adapts the compilation strategy during runtime to optimize performance.
2Reliability
If each non-native instruction is parsed and translated individually during execution, then the translation is accurate, but the processing overhead and execution time increase
Solution Approach 1:
The patent applies segmentation by dividing non-native code into distinct compilable segments or blocks. Instead of translating individual instructions, the system identifies contiguous non-native code regions, compiles them as unified native code blocks, and executes them directly, maintaining accuracy while improving performance through batch processing.
Solution Approach 2:
The patent merges multiple non-native instructions into a single native code sequence through compilation. By combining several individual translation operations into one compilation pass that generates a complete native code block, the system reduces overhead while preserving the semantic accuracy of each original instruction.
3Productivity
If non-native code is pre-translated to native instructions, then execution speed improves, but the system loses the flexibility to handle runtime branch computations
Solution Approach 1:
The patent uses dynamics to enable both pre-compilation and runtime adaptability. The system pre-compiles non-native code segments into native instructions for fast execution, while simultaneously maintaining the ability to dynamically identify and compile new code regions based on runtime branch outcomes and execution patterns, ensuring both speed and flexibility.
Solution Approach 2:
The patent implements self-service by enabling the system to automatically identify when pre-compiled code needs to be updated or recompiled based on runtime conditions. The compilation mechanism monitors execution patterns and autonomously triggers re-compilation of affected code segments without external intervention, maintaining optimal performance while adapting to runtime changes.
Data Source
AI summary
Systems and methods for executing non-native instructions in a computing system having a processor configured to execute native instructions are provided. A dynamic translator uses instruction code translation in parallel with just-in-time (JIT) compilation to execute the non-native instructions. Non-native instructions may be interpreted to generate instruction codes, which may be stored in a shadow memory. During a subsequent scheduling of a non-native instruction for execution, the corresponding instruction code may be retrieved from the shadow memory and executed, thereby avoiding reinterpreting the non-native instruction. In addition, the JIT compiler may compile instruction codes to generate native instructions, which may be made available for execution, further speeding up the execution process. A system implementing the aforementioned translator may improve performance and speed associated with executing non-native instructions by optimizing the use of instruction codes and JIT-compiled native instructions corresponding to the instruction codes when executing the non-native instructions.