我使用BigUint
在Rust中实现了Miller-Rabin强伪Pseudoprime测试,以支持任意大质数。要运行5到10 ^ 6之间的数字,cargo run --release
需要大约40秒。
我使用Java的BigInteger
实现了相同的算法,同样的测试需要10秒才能完成。 Rust似乎慢了4倍。我认为这是由num::bigint
的实现引起的。
这只是num::bigint
的当前状态,还是有人发现我的代码有明显的改进? (主要是关于我如何使用该语言。无论我的算法实现是好还是坏,它在两种语言中的实现几乎完全相同 - 所以不会导致性能上的差异。)
我注意到由于Rust的所有权模型,需要大量的clone()
才能将速度提升到某种程度。但我想没有办法解决这个问题,对不对?
以下是代码:
extern crate rand;
extern crate num;
extern crate core;
extern crate time;
use std::time::{Duration};
use time::{now, Tm};
use rand::Rng;
use num::{Zero, One};
use num::bigint::{RandBigInt, BigUint, ToBigUint};
use num::traits::{ToPrimitive};
use num::integer::Integer;
use core::ops::{Add, Sub, Mul, Div, Rem, Shr};
fn find_r_and_d(i: BigUint) -> (u64, BigUint) {
let mut d = i;
let mut r = 0;
loop {
if d.clone().rem(&2u64.to_biguint().unwrap()) == Zero::zero() {
d = d.shr(1usize);
r = r + 1;
} else {
break;
}
}
return (r, d);
}
fn might_be_prime(n: &BigUint) -> bool {
let nsub1 = n.sub(1u64.to_biguint().unwrap());
let two = 2u64.to_biguint().unwrap();
let (r, d) = find_r_and_d(nsub1.clone());
'WitnessLoop: for kk in 0..6u64 {
let a = rand::thread_rng().gen_biguint_range(&two, &nsub1);
let mut x = mod_exp(&a, &d, &n);
if x == 1u64.to_biguint().unwrap() || x == nsub1 {
continue;
}
for rr in 1..r {
x = x.clone().mul(x.clone()).rem(n);
if x == 1u64.to_biguint().unwrap() {
return false;
} else if x == nsub1 {
continue 'WitnessLoop;
}
}
return false;
}
return true;
}
fn mod_exp(base: &BigUint, exponent: &BigUint, modulus: &BigUint) -> BigUint {
let one = 1u64.to_biguint().unwrap();
let mut result = one.clone();
let mut base_clone = base.clone();
let mut exponent_clone = exponent.clone();
while exponent_clone > 0u64.to_biguint().unwrap() {
if exponent_clone.clone() & one.clone() == one {
result = result.mul(&base_clone).rem(modulus);
}
base_clone = base_clone.clone().mul(base_clone).rem(modulus);
exponent_clone = exponent_clone.shr(1usize);
}
return result;
}
fn main() {
let now1 = now();
for n in 5u64..1_000_000u64 {
let b = n.to_biguint().unwrap();
if might_be_prime(&b) {
println!("{}", n);
}
}
let now2 = now();
println!("{}", now2.to_timespec().sec - now1.to_timespec().sec);
}
答案 0 :(得分:6)
您可以非常轻松地删除大多数克隆。 BigUint
还为&BigUint
的操作实现了所有操作特征,而不仅仅是使用值。有了它,它变得更快,但仍然是Java的一半......
另外(与性能无关,只是可读性)您不需要明确使用add
,sub
,mul
和shr
;他们会覆盖常规的+
,-
,*
和>>
运营商。
例如,您可以像这样重写might_be_prime
和mod_exp
,这已经在我的机器上提供了很好的加速(平均从40到24秒):
fn might_be_prime(n: &BigUint) -> bool {
let one = BigUint::one();
let nsub1 = n - &one;
let two = BigUint::new(vec![2]);
let mut rng = rand::thread_rng();
let (r, mut d) = find_r_and_d(nsub1.clone());
let mut x;
let mut a: BigUint;
'WitnessLoop: for kk in 0..6u64 {
a = rng.gen_biguint_range(&two, &nsub1);
x = mod_exp(&mut a, &mut d, &n);
if &x == &one || x == nsub1 {
continue;
}
for rr in 1..r {
x = (&x * &x) % n;
if &x == &one {
return false;
} else if x == nsub1 {
continue 'WitnessLoop;
}
}
return false;
}
true
}
fn mod_exp(base: &mut BigUint, exponent: &mut BigUint, modulus: &BigUint) -> BigUint {
let one = BigUint::one();
let zero = BigUint::zero();
let mut result = BigUint::one();
while &*exponent > &zero {
if &*exponent & &one == one {
result = (result * &*base) % modulus;
}
*base = (&*base * &*base) % modulus;
*exponent = &*exponent >> 1usize;
}
result
}
请注意,我已经移动了println!超出时间,以便我们不对IO进行基准测试。
fn main() {
let now1 = now();
let v = (5u64..1_000_000u64)
.filter_map(|n| n.to_biguint())
.filter(|n| might_be_prime(&n))
.collect::<Vec<BigUint>>();
let now2 = now();
for n in v {
println!("{}", n);
}
println!("time spent seconds: {}", now2.to_timespec().sec - now1.to_timespec().sec);
}