Introduce Rayon for parallel iteration and sorting

- Use `into_par_iter()` before setting out to calculate scores and then
  filter by them

This represents a more efficient parallelism approach, with no mutex
or global state at top level.

ivy_files(kubernetes)   time:   [4.5800 ms 4.6121 ms 4.6467 ms]
                        change: [-55.056% -54.570% -54.133%] (p = 0.00 < 0.05)
                        Performance has improved.

ivy_match(file.lua)     time:   [1.1514 µs 1.1599 µs 1.1694 µs]
                        change: [+0.4116% +2.0753% +3.6710%] (p = 0.01 < 0.05)
                        Change within noise threshold.

Cargo.lock

@@ -274,6 +274,7 @@ dependencies = [
  "fuzzy-matcher",
  "ignore",
  "lazy_static",
+ "rayon",
 ]
 
 [[package]]

Cargo.toml

@@ -12,6 +12,7 @@ path = "rust/lib.rs"
 ignore = "0.4"
 fuzzy-matcher = "0.3.7"
 lazy_static = "1.4.0"
+rayon = "1.5.3"
 
 [dev-dependencies]
 criterion = "0.3.6"

rust/sorter.rs

@@ -1,8 +1,5 @@
 use super::matcher;
-use super::thread_pool;
-
-use std::sync::mpsc;
-use std::sync::Arc;
+use rayon::prelude::*;
 
 pub struct Match {
     pub score: i64,
@@ -27,7 +24,7 @@ pub fn sort_strings(options: Options, strings: Vec<String>) -> Vec<Match> {
     let matcher = matcher::Matcher::new(options.pattern);
 
     let mut matches = strings
-        .into_iter()
+        .into_par_iter()
         .map(|candidate| Match {
             score: matcher.score(candidate.as_str()),
             content: candidate,