Building a Fast JIT Compiler in 5μs with AI Assistance

The Challenge of Fast JIT Compilation

Historically, creating fast JIT compilers required deep knowledge of assembly language, making it a complex task. Existing production databases typically rely on LLVM or C/C++ code generation for JIT compilation, which often results in high compile times. These high compile times limit the applicability of JIT compilation, often restricting it to only a subset of operations.

AI-Assisted JIT Development

The developer of pgrust found that AI assistance significantly simplified the process of building a JIT compiler. By directly targeting assembly with AI, it became easier to achieve fast compile times. This method allowed pgrust's JIT compiler to compile code in approximately 5 microseconds.

Impact on Database Performance

The rapid compilation speed of 5 microseconds enables pgrust to JIT compile every SQL query, rather than just a select few. This capability is cited as a reason for pgrust's performance. The article suggests this approach presents an opportunity for new databases to improve upon older ones by integrating more efficient JIT compilation.

JIT Compilation Fundamentals

JIT compilation involves generating compiled code at runtime, which can lead to significant performance improvements, often 2-5 times faster. It is particularly useful when runtime information drastically alters program behavior, as seen in programming language interpreters or data parsing where schemas are unknown until runtime. The article provides a walkthrough for building a simple regular expression engine using JIT compilation as an example.