MagLev handles trees like a monkey
Antonio Cangiano June 5th, 2008
Over the past couple of nights, I tried out MagLev on my Mac laptop (Mac OS X Leopard, 2.2GHz, 2GB Ram). While the shootout will provide us with a detailed comparison between MagLev and the other major Ruby implementations (on many tests) I thought I’d share my first impressions.
MagLev is going to be a fast implementation of Ruby. How many times faster? Well, it depends on the test, and I don’t have systematic numbers yet to come up with a geometric mean of the ratios (the shootout will do just that). What I can tell you now though, is that it’s fast, significantly faster than MRI. You know that slowness that you’ve almost come to expect when running a Ruby script? It’s simply not there with MagLev. And let’s not forget, that MagLev’s added value is not limited to performance, in the same way that JRuby’s integration with Java is a strong selling point.
It’s not mature, of course, and there are a few things which haven’t been implemented yet. But it’s complete enough to run WEBrick and several other small programs I tried. A truly impressive accomplishment if you think about what was achieved in just three months. So let me reassure you that it’s not vaporware, it’s real and it’s fast.
I want to leave you with an example of a non-trivial benchmark. Running the binary-trees test from the Computer Language Benchmarks Game (chosen because it’s the first test), I obtained the following results:
| PHP 5.2.5 | 100.603s |
| Perl 5.8.8 | 70.885s |
| Ruby 1.8.6 | 60.089s |
| Python 2.5.1 | 29.908s |
| MagLev | 7.673s |
| C++ (gcc 4.0.1) | 6.265s |
Aside from being much faster than Ruby 1.8.6, MagLev’s speed is pretty darn close to that of the extremely fast C++ (complied with g++ and all the optimizations), in this specific case.
You can’t read too much from a single test, especially when we are not comparing different VMs from the same identical script like we’ll do for the shootout. It’s impressive nevertheless and it should give you a hint about MagLev’s speed even when facing non-trivial, non-ad-hoc benchmarks.
