Composition

This guide explains how to optimize cryptographic parameters by specifying composition when using modules.

When using modules, make sure to specify composition so that the compiler can select more optimal parameters based on how the functions in the module would be used.

For example:

import numpy as np
from concrete import fhe


@fhe.module()
class PowerWithoutComposition:
    @fhe.function({"x": "encrypted"})
    def square(x):
        return x ** 2

    @fhe.function({"x": "encrypted"})
    def cube(x):
        return x ** 3

without_composition = PowerWithoutComposition.compile(
    {
        "square": fhe.inputset(fhe.uint2),
        "cube": fhe.inputset(fhe.uint4),
    }
)
print(f"without composition -> {int(without_composition.complexity):>10_} complexity")


@fhe.module()
class PowerWithComposition:
    @fhe.function({"x": "encrypted"})
    def square(x):
        return x ** 2

    @fhe.function({"x": "encrypted"})
    def cube(x):
        return x ** 3

    composition = fhe.Wired(
        [
            fhe.Wire(fhe.Output(square, 0), fhe.Input(cube, 0))
        ]
    )

with_composition = PowerWithComposition.compile(
    {
        "square": fhe.inputset(fhe.uint2),
        "cube": fhe.inputset(fhe.uint4),
    }
)
print(f"   with composition -> {int(with_composition.complexity):>10_} complexity")

This prints:

without composition -> 185_863_835 complexity
   with composition -> 135_871_612 complexity

It means that specifying composition resulted in ~35% improvement to complexity for computing cube(square(x)).