> I think it is rather embarrassing that most code written in modern languages performs worse on today's computers than native code running on 1980s machines.
Ok, let's play ball.
> After the Cray-1, the Cray Corporation developed another giant named Cray-2. It remained the world’s fastest Supercomputer between the years 1985 to 1989, capable of performing 1.9 gigaflops.
( Source: http://infotology.blogspot.be/2012/04/super-computer-timelin... )
So that's tha fastest of the fast in the '80's. According to Intel, a i7-3770k consumer CPU gets 112 gflops and a Q6600 quad core, which was released in Q1 2007, has 38.40 GFlops. That's a factor 58+ faster on the i7, or a factor 20 for the Q6600.
I picked the bench config x86 quad core because this had the highest peak. Also, if you take these languages, which are more commonly used:
* C#/Mono: Worst 9x, median 2x
* Go: Worst 7x, median 3x
* Haskell: Worst 3x, median 2x
* Java: Worst 3x, median 2x
* PHP: Worst 109x, median 36x
* Python 3: Worst 129x, median 37x
* Ruby: Worst 239x, median 53x
* JRuby: Worst 115x, median 34x
But keep in mind that:
* Current CPU integer performance, cache speeds, memory bandwidth and general i/o would completely destroy the Cray-2
* GFlops are a real bad indicator of how fast a computer is. Current computers are even faster. Current GPU's are floating point optimized and run circles around any general purpose CPU when it comes to GFlops.
* These are CPU-bound artificial language comparison benchmarks.
* Native code means nothing. Bad slow code will always be slow, whatever language you use. Some of the languages included do compile to 'native code' (Go and Haskell), and a lot of the interpreted/byte code compiled languages use a JIT to generate 'native code' too.
* We don't take into account the Cray-2's bottlenecks (mainly I/O)
* All GFlop numbers are according to the manufacturer.
* Most applications hit i/o limits before hitting CPU limits (yes there are exceptions)
* this is comparing with the fastest of the fast you could get at the end of the '80s
So in worst theoretical cases, sure. In the real world? Not even close.
Ok, let's play ball.
> After the Cray-1, the Cray Corporation developed another giant named Cray-2. It remained the world’s fastest Supercomputer between the years 1985 to 1989, capable of performing 1.9 gigaflops. ( Source: http://infotology.blogspot.be/2012/04/super-computer-timelin... )
So that's tha fastest of the fast in the '80's. According to Intel, a i7-3770k consumer CPU gets 112 gflops and a Q6600 quad core, which was released in Q1 2007, has 38.40 GFlops. That's a factor 58+ faster on the i7, or a factor 20 for the Q6600.
Now let's take the Q6600 to make it easy to compare languages in a very bad way: http://benchmarksgame.alioth.debian.org/u32q/benchmark.php?t...
I picked the bench config x86 quad core because this had the highest peak. Also, if you take these languages, which are more commonly used: * C#/Mono: Worst 9x, median 2x * Go: Worst 7x, median 3x * Haskell: Worst 3x, median 2x * Java: Worst 3x, median 2x * PHP: Worst 109x, median 36x * Python 3: Worst 129x, median 37x * Ruby: Worst 239x, median 53x * JRuby: Worst 115x, median 34x
But keep in mind that: * Current CPU integer performance, cache speeds, memory bandwidth and general i/o would completely destroy the Cray-2 * GFlops are a real bad indicator of how fast a computer is. Current computers are even faster. Current GPU's are floating point optimized and run circles around any general purpose CPU when it comes to GFlops. * These are CPU-bound artificial language comparison benchmarks. * Native code means nothing. Bad slow code will always be slow, whatever language you use. Some of the languages included do compile to 'native code' (Go and Haskell), and a lot of the interpreted/byte code compiled languages use a JIT to generate 'native code' too. * We don't take into account the Cray-2's bottlenecks (mainly I/O) * All GFlop numbers are according to the manufacturer. * Most applications hit i/o limits before hitting CPU limits (yes there are exceptions) * this is comparing with the fastest of the fast you could get at the end of the '80s
So in worst theoretical cases, sure. In the real world? Not even close.