This article delves into the popular use of JIT decorators in Python programming, particularly in machine learning contexts. It explains how these decorators transform functions into presentation language suitable for specialized compilation, using libraries like JAX and Triton. The workflow described involves translating a function into expression IR, which is then converted into LLVM IR for JIT execution, utilizing llvmlite as a critical component. The article aims to provide a clear educational illustration of these processes through a simple example.
The 'JIT decorator' pattern is highly favored in Python for machine learning, enabling functions to be compiled and executed through specialized libraries like JAX and Triton.
Pyhton acts as a meta-language to define computations, with libraries translating these to an expression IR and then to LLVM IR for JIT execution.
We'll illustrate how various JIT decorators function through a simplified example that processes Python functions into ir and ultimately into executable code.
The process includes translating the function to an expression IR, converting it to LLVM IR, and then using llvmlite to JIT execute the final code.
Collection
[
|
...
]