Trait malachite_base::num::arithmetic::traits::ModPowPrecomputedAssign

source · [−]
pub trait ModPowPrecomputedAssign<RHS: Two = Self, M = Self>: ModPowPrecomputed<RHS, M> {
    fn mod_pow_precomputed_assign(&mut self, exp: RHS, m: M, data: &Self::Data);
}
Expand description

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

If multiple modular exponentiations with the same modulus are necessary, it can be quicker to precompute some piece of data and reuse it in the exponentiation calls. This trait provides a function for using precomputed data during exponentiation. For precomputing the data, use the precompute_mod_pow_data function in ModPowPrecomputed.

Required Methods

Implementations on Foreign Types

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Raises a number to a power modulo another number $m$, in place. Assumes the input is already reduced modulo $m$.

Assumes the input is already reduced modulo m. Some precomputed data is provided; this speeds up computations involving several modular exponentiations with the same modulus. The precomputed data should be obtained using precompute_mod_pow_data.

Worst-case complexity

$T(n) = O(n)$

$M(n) = O(1)$

where $T$ is time, $M$ is additional memory, and $n$ is exp.significant_bits().

Examples

See here.

Implementors