github.com/rbjorklin/fib

Performance Benchmark of top Github languages


Install
go get github.com/rbjorklin/fib

Documentation

Recursive Fibonacci Benchmark using top languages on Github

Top 10: JavaScript, Java, Python, Ruby, Php, C++, C#, C, Go reference

Others: Crystal, Rust, Swift, Mono, Elixir, Perl, R, Julia, D

This code performs a recursive fibonacci to the 46th position with the result of 2,971,215,073.

All tests are run on:

  • iMac (Retina 5K, 27-inch, Late 2015)
  • OS: macOS High Sierra 10.13.6
  • Processor: 3.2 GHz Intel Core i5
  • Memory: 16 GB 1867 MHz DDR3

Last benchmark was ran on September 25th, 2018

Natively compiled, statically typed

Language Time, s Compile Run
Nim 4.622 nim cpp -d:release fib.nim time ./fib
Crystal 5.687 crystal build --release fib.cr time ./fib
C++ 5.751 g++ -O3 -o fib fib.cpp time ./fib
C 6.258 gcc -O3 -o fib fib.c time ./fib
Rust 6.567 rustc -O fib.rs time ./fib
D 6.993 ldc2 -O3 -release -flto=full -of=fib fib.d time ./fib
Swift 10.307 swiftc -O -g fib.swift time ./fib
Go 10.600 go build fib.go time ./fib

NOTE: Swift and Go do not seem to use Tail Call Optimization so this may be why they are showing up as twice as slow. Thank you Ammrage for pointing this out.

VM compiled bytecode, statically typed

Language Time, s Compile Run
Java 7.447 javac Fib.java time java Fib
C# 7.874 dotnet build -c Release -o ./bin time dotnet ./bin/fib.dll
C# (Mono) 12.596 mcs fib.cs time mono fib.exe

VM compiled before execution, mixed/dynamically typed

Language Time, s Run
Dart 10.467 time dart fib.dart
Julia 10.799 time julia fib.jl
Node 18.874 time node fib.js
Elixir 69.101 time elixir fib.exs

NOTE: These languages include compilation time which should be taken into consideration when comparing.

Interpreted, dynamically typed

Language Time, s Run
Ruby 195.601 time ruby fib.rb
Php 206.346 time php fib.php
Python 502.036 time python fib.py
Python3 758.681 time python3 fib.py
Perl 1133.131 time perl fib.pl
R 1796.495 time r -f fib.r

Optimized code that breaks the benchmark

The following code examples use techniques that break the benchmark. They do not perform the same internal tasks as the other examples so are not a good apples to apples comparisons. It demonstrates that all benchmarks will have some caveat.

Language Time, s Compile Run
Go (mem) 0.005* go build -o fib fib-mem.go time ./fib
Nim (mem) 0.006* nim cpp -d:release fib_mem.nim time ./fib_mem
C++ (constexpr) 0.086* g++-8 -O3 -o fib fib-constexpr.cpp time ./fib
Node (mem) 0.112* time node fib-mem.js

NOTE: The C++ (constexpr) is using a constexpr which optimizes the recursive call to a constant. It was provided by Ole Christian Eidheim. The Go (mem) is using memoization. It was provided by Alexander F. Rødseth. The Node (mem) is another example using memoization. It was provided by YSTYLE-L.X.Y The Nim (mem) version is provided by PMunch

Versions

  • go version go1.11 darwin/amd64
  • g++-8 (Homebrew GCC 8.2.0) 8.2.0
  • crystal Crystal 0.26.1 (2018-08-27) LLVM: 6.0.1
  • g++ Apple LLVM version 10.0.0 (clang-1000.11.45.2)
  • gcc Apple LLVM version 10.0.0 (clang-1000.11.45.2)
  • nim Nim Compiler Version 0.18.0 [MacOSX: amd64]
  • swiftc Apple Swift version 4.2 (swiftlang-1000.11.37.1 clang-1000.11.45.1)
  • rustc 1.29.0
  • javac 10.0.1
  • mcs Mono C# compiler version 5.12.0.226
  • dotnet 2.1.4
  • dart Dart VM version: 2.0.0 (Fri Aug 3 10:53:23 2018 +0200)
  • julia version 0.6.3
  • node v9.4.0
  • elixir Elixir 1.7.3 (compiled with Erlang/OTP 21)
  • ruby 2.5.1p57 (2018-03-29 revision 63029)
  • php 7.1.16 (cli) (built: Apr 1 2018 13:14:42)
  • python 2.7.15
  • python3 3.7.0
  • perl 5, version 26, subversion 2 (v5.26.2)
  • r version 3.5.0 (2018-04-23)
  • lcd2 the LLVM D compiler (1.11.0)

Caveats

Fibonacci Benchmark