crystal-chars-vs-codepoints-bench
chars
vs codepoints
benchmark
I was curious if (like in some other languages) evaluating numeric representations of strings was faster than their character representations.
The short answer is: in Crystal codepoints
is negligibly faster.
The following is example output performed on a ThinkPad E480.
Benchmark #1: ../bin/hamming --chars
Time (mean ± σ): 3.263 s ± 0.029 s [User: 2.276 s, System: 0.975 s]
Range (min … max): 3.247 s … 3.375 s 50 runs
Benchmark #2: ../bin/hamming --codepoints
Time (mean ± σ): 3.251 s ± 0.040 s [User: 2.265 s, System: 0.974 s]
Range (min … max): 3.228 s … 3.395 s 50 runs
Summary
'../bin/hamming --codepoints' ran
1.00 ± 0.02 times faster than '../bin/hamming --chars'
The results are fairly stable, codepoints
always beat chars
, but the difference is tiny. I wouldn't look here for an optimization, especially if you need to actually do anything with the characters (like display).
What it's doing
The code under benchmark (src/hamming.cr
) is calculating the Hamming distance between two files of 100,000,000 characters each. The test (test/bench
) is a bash script that generates test data (using src/gen_input.cr
) and runs hyperfine
for a performance comparision.
The idea for the using Hamming distance, and this benchmark in general, came from this exercism.io exercise where my solution got some reasonable questions from the Crystal mentor reviewing it.
Running the tests
- Install hyperfine
- Clone this repo
- Build the crystal bits with
shards build --release
- Run
test/bench
- ...
- Profit!
crystal-chars-vs-codepoints-bench
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- over 3 years ago
- February 18, 2021
MIT License
Thu, 07 Nov 2024 19:26:05 GMT