AI Compiler Translating Portable Code for Hardware
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Solution Overview
Problem
Existing methods for compiling portable code fail to effectively translate and optimize machine-readable instructions for different hardware platforms, leading to inefficiencies and errors due to lack of platform-specific tuning.
Innovation Solution
The use of artificial intelligence models, specifically single-stage and multi-stage AI models, to translate and optimize code for specific hardware platforms by generating semantic data and rewriting code to utilize available platform features, thereby improving performance and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing compilation methods are used to translate portable code for different hardware platforms, then code portability is maintained, but translation efficiency and execution performance deteriorate due to lack of platform-specific optimization
Solution Approach 1:
The compilation process is segmented into distinct stages: initial compilation to portable intermediate code, semantic analysis of the intermediate code, and targeted optimization for specific hardware platforms. This segmentation allows each stage to focus on specific tasks, improving both translation efficiency and execution performance without compromising code portability.
Solution Approach 2:
A semantic analysis module acts as an intermediary between the portable code compiler and platform-specific compilers. This intermediary analyzes the semantic meaning of portable code and generates optimized machine code tailored to specific hardware platforms, thereby improving execution performance while maintaining the benefits of portable code development.
2Ease of manufacture
If portable code is compiled without platform-specific tuning, then development simplicity is maintained, but execution accuracy and performance deteriorate
Solution Approach 1:
The system performs preliminary semantic analysis on portable code to identify optimization opportunities before generating platform-specific machine code. This preliminary action enables the system to maintain development simplicity while preparing the code for accurate and efficient execution on target hardware platforms.
Solution Approach 2:
The compilation system dynamically adjusts compilation parameters and optimization strategies based on the target hardware platform characteristics. This allows the same portable code to be compiled with different parameters for different platforms, improving execution accuracy without affecting development simplicity.
3Device complexity
If traditional compilation approaches are used, then compiler complexity is kept low, but code optimization capability and processor cycle efficiency worsen
Solution Approach 1:
The compilation system is segmented into modular components: a portable code compiler, a semantic analysis module, and platform-specific code generators. This segmentation allows the system to achieve high processor cycle efficiency through targeted optimizations while keeping each individual component relatively simple and manageable.
Solution Approach 2:
The semantic analysis module automatically analyzes portable code and identifies optimization opportunities without requiring complex manual configuration. The system serves itself by autonomously determining the appropriate optimization strategies for different hardware platforms, improving processor cycle efficiency while maintaining reasonable compiler complexity.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed that compile portable code for specific hardware are disclosed herein that include an apparatus including computer readable instructions, and programmable circuitry to at least one of execute or instantiate the instructions to receive input code, the input code written for operation on a first platform, determine a target platform, the target platform different than the first platform, and translate, via an artificial intelligence (AI) model, the input code to output code, the output code written for operation on the target platform.