Instruction Set

Instruction sets, the fundamental language understood by computer processors, are the subject of ongoing research aimed at improving their efficiency and adaptability. Current efforts focus on automating the translation between different instruction sets using techniques like neural machine translation (e.g., transformer models) and optimizing code generation for specific instruction sets (e.g., AVX, NEON) through compiler optimizations and machine learning-based register allocation. These advancements are crucial for improving software portability, accelerating machine learning computations, and enhancing the security and analysis of binary code.