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Error probability

This guide explains how setting p_error configuration option can affect the performance of Concrete circuits.

Adjusting table lookup error probability is discussed extensively in Table lookup exactness section. The idea is to sacrifice exactness to gain performance.

For example:

import numpy as np
from concrete import fhe

def f(x, y):
    return (x // 2) * (y // 3)

inputset = fhe.inputset(fhe.uint4, fhe.uint4)
for p_error in [(1 / 1_000_000), (1 / 100_000), (1 / 10_000), (1 / 1_000), (1 / 100)]:
    compiler = fhe.Compiler(f, {"x": "encrypted", "y": "encrypted"})
    circuit = compiler.compile(inputset, p_error=p_error)
    print(f"p_error of {p_error:.6f} -> {int(circuit.complexity):_} complexity")

This prints:

p_error of 0.000001 -> 294_773_524 complexity
p_error of 0.000010 -> 286_577_520 complexity
p_error of 0.000100 -> 275_887_080 complexity
p_error of 0.001000 -> 265_196_640 complexity
p_error of 0.010000 -> 184_144_972 complexity

Error probability

This guide explains how setting p_error configuration option can affect the performance of Concrete circuits.

Adjusting table lookup error probability is discussed extensively in Table lookup exactness section. The idea is to sacrifice exactness to gain performance.

For example:

import numpy as np
from concrete import fhe

def f(x, y):
    return (x // 2) * (y // 3)

inputset = fhe.inputset(fhe.uint4, fhe.uint4)
for p_error in [(1 / 1_000_000), (1 / 100_000), (1 / 10_000), (1 / 1_000), (1 / 100)]:
    compiler = fhe.Compiler(f, {"x": "encrypted", "y": "encrypted"})
    circuit = compiler.compile(inputset, p_error=p_error)
    print(f"p_error of {p_error:.6f} -> {int(circuit.complexity):_} complexity")

This prints:

p_error of 0.000001 -> 294_773_524 complexity
p_error of 0.000010 -> 286_577_520 complexity
p_error of 0.000100 -> 275_887_080 complexity
p_error of 0.001000 -> 265_196_640 complexity
p_error of 0.010000 -> 184_144_972 complexity