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June 5, 2014 00:56
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Fibonacci Benchmark: Swift vs Rubinius vs JRuby vs MRI
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| require 'benchmark' | |
| def fib n | |
| if n <= 1 | |
| n | |
| else | |
| fib(n - 1) + fib(n - 2) | |
| end | |
| end | |
| irb> Benchmark.realtime { fib(40) } | |
| # Rubinius: 3.87664 | |
| # JRuby : 6.228 | |
| # MRI 2.0 : 16.847601 | |
| # MRI 2.1 : 14.56271 |
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| import Cocoa | |
| func fib(n: Int) -> Int { | |
| if n <= 1 { | |
| return n | |
| } else { | |
| return fib(n - 1) + fib(n - 2) | |
| } | |
| } | |
| func benchmark(closure: () -> Int) -> NSTimeInterval { | |
| let start = NSDate() | |
| closure() | |
| return NSDate().timeIntervalSinceDate(start) | |
| } | |
| 27> benchmark { fib(40) } | |
| // $R41: NSTimeInterval = { | |
| // value = 0.5169379711151123 | |
| // } |
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JRuby on an invokedynamic-capable JVM should be at least as fast as Rubinius. Here's my numbers.
MRI 2.1.1: 24.554626
JRuby 1.7.12 (Java 8 + invokedynamic): 3.463000
JRuby 1.7.12 (Java 8 - invokedynamic): 6.256000
Rubinius 2.2.6ish: 6.018709
Given your tweet that Swift is 29x faster than MRI, which came in at 24s on my system, I guess that would mean JRuby's only in the <5x slower range. Not bad competing against a statically-compiled and statically-analyzed language.
Of course, JRuby 9000 will have two new runtimes that should easily match or exceed native math performance. JRuby's still your best bet for fast, compatible Ruby.