Use AI Model as Compiler - Install Meta LLM Compiler 13B Locally

 This video locally installs Meta LLM Compiler 13B and shows a step-by-step tutorial to optimize Python code into LLVM-IR Code.

Code:

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Python Function:

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def add_two(a, b):

    return a + b

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Convert Python code to LLVM-IR Code:

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pip install llvmlite

from llvmlite import ir, binding

# Define the function type

func_type = ir.FunctionType(ir.IntType(32), [ir.IntType(32), ir.IntType(32)])

# Create a module

module = ir.Module(name="my_module")

module.triple = binding.get_default_triple()

# Create the function and add it to the module

func = ir.Function(module, func_type, name="add_two")

# Define the entry block

entry_block = func.append_basic_block(name="entry")

builder = ir.IRBuilder(entry_block)

# Define function arguments

a, b = func.args

a.name = "a"

b.name = "b"

# Add the instruction to add the two arguments

result = builder.add(a, b, name="res")

# Return the result

builder.ret(result)

# Print the LLVM-IR

print(module)

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Ask LLM Compiler to Optimize it:

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Optimize the following LLVM-IR code using opt -O3:

; ModuleID = 'my_module'

target triple = "x86_64-unknown-linux-gnu"

define i32 @add_two(i32 %a, i32 %b) {

entry:

  %res = add i32 %a, %b

  ret i32 %res

}