https://github.com/theodus/pony-benchmark
Improved Micro-Benchmarking for Pony
https://github.com/theodus/pony-benchmark
benchmarking microbenchmarks pony-language
Last synced: 5 months ago
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Improved Micro-Benchmarking for Pony
- Host: GitHub
- URL: https://github.com/theodus/pony-benchmark
- Owner: Theodus
- License: mit
- Created: 2018-01-02T01:39:52.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-02-28T14:19:14.000Z (over 8 years ago)
- Last Synced: 2025-11-30T08:24:16.693Z (7 months ago)
- Topics: benchmarking, microbenchmarks, pony-language
- Language: Pony
- Size: 351 KB
- Stars: 5
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# PonyBench (Version 2)
## Standard Output:
#### Pony Code
```pony
actor Main is BenchmarkList
new create(env: Env) =>
PonyBench(env, this)
fun tag benchmarks(bench: PonyBench) =>
bench(Fib(5))
bench(Fib(10))
bench(Fib(20))
bench(Fib(40))
class iso Fib is MicroBenchmark
let _n: U64
new iso create(n: U64) =>
_n = n
fun name(): String =>
"Fib(" + _n.string() + ")"
fun apply() =>
DoNotOptimise[U64](_fib(_n))
DoNotOptimise.observe()
fun _fib(n: U64): U64 =>
if n < 2 then 1
else _fib(n - 1) + _fib(n - 2)
end
```
#### Output
```
$ ponyc -V0 --runtimebc examples/simple -b simple && ./simple --ponynoyield
Benchmark results will have their mean and median adjusted for overhead.
You may disable this with --noadjust.
Benchmark mean median deviation iterations
Fib(5) 15 ns 16 ns ±0.11% 1000000
Fib(10) 180 ns 180 ns ±0.55% 500000
Fib(20) 21525 ns 21511 ns ±0.30% 10000
Fib(40) 324952472 ns 324871552 ns ±0.21% 1
```
## CSV Output
#### Output
```bash
$ ponyc -V0 --runtimebc examples/custom-config -b custom-config && ./custom-config --ponynoyield -csv > data.csv
```
#### Matlab Code (Visualization example)
```matlab
close all; clear; clc
M = csvread('data.csv',0,1);
M = M'; % transpose so that results are column vectors
overhead = median(M(:,1:2:end));
ops = M(:,2:2:end);
pows = 0:1:20;
sizes = 2.^pows;
%% box plot
boxplot(ops-overhead)
grid on
xticklabels('2^'+string(pows))
title('Persistent Vec Apply')
xlabel('size')
ylabel('runtime (ns)')
ax = gca;
ax.FontSize = 24;
%% histogram
figure
idxs = fliplr(5+1:5:21);
for i = idxs
histogram(ops(:,i)-overhead(i))
hold on
end
title('Histogram of Persistent Vec Apply (sizes 32^n)')
legend('size ' + string(sizes(idxs)))
xlabel('runtime (ns)')
ylabel('occurences')
ax = gca;
ax.FontSize = 24;
```
#### Charts
