Consistently twice as slow, with memory usage between 2 and 400(!) times larger. Java is slow and bloated compared to native.
Your next argument will be something about how micro-benchmarks don't reflect reality for larger programs...
What do you mean by "native"? C/C++? Yes, given enough effort you can write C code that outperforms Java code, sometimes handily, especially in single threaded or low-contention cases. Yet we did write applications in C/C++ before we switched to Java, we had excellent reasons to make the switch, and there have been precious few companies making the switch back. That shows you that the microbenchmarks don't tell the whole story.
Right now, the JVM's biggest performance issue is the lack of value types. Once they arrive -- and work is well underway -- beating Java would be harder and harder, especially given new compilers like Graal. But in any event, I just don't see large developers switch back to C++ (or Rust) en masse. Memory usage is hardly an issue, as RAM is very cheap and underutilized in server environments anyway. Spending effort to conserve RAM just doesn't make any sense, unless you're targeting RAM constrained environments.
2. How are Java's value types limited?
3. I find your calculation extremely pessimistic. Lambda expression are widespread a couple of years after their release, and I see no reason why value types will be different. I think that 5 years are a better estimate for wide use of value types.
> Except for pointer equality checks, forbidden operations will throw some sort of exception. How to control pointer equality checks is an open question with several possible answers.
And more:
Rules for permanently locked objects:
- restrictions on classes of locked objects
- all non-static fields must be final
- there must be no finalizer method (no override to `Object.finalize`)
- these restrictions apply to any superclasses as well
- an array can be marked locked, but then (of course) its elements cannot be stored to
- if not an array, the object's class must implement the marker type `PermanentlyLockable` (is this a good idea?)
- restricted operations on locked objects (could be enforced, or else documented as producing undefined results)
- do not use any astore or putfield instructions, nor their reflective equivalents, to change any field
- do not lock (you may get a hang or a LockedObjectException)
- do not test for pointer equality; use Object.equals instead (there may be a test for this)
- do not ask for an identity hash code; use Object.hashCode instead (there may be a test for this)
- do not call wait, notify, or notifyAll methods in Object
- at the time it is marked locked, an object's monitor must not be locked (in fact, should never have been?)
- side effects
- elements of locked arrays are stably available to readers just like final object fields (i.e., there is a memory fence)
- a locked object can be locked again, with no additional effect
- any attempt to mutate a permanently locked object raises java.lang.LockedObjectException
- any attempt to synchronize on a permanently locked object raises java.lang.LockedObjectException
- object lifecycle
- all objects are initially created in a normal (unlocked) state
- an object marked locked cannot be "unlocked" (reverted to a normal state)
- an object marked locked must be unreferenced by any other thread (can we enforce this?)
- the reference returned from the (unsafe) marking primitive must be used for all future accesses
- any previous references (including the one passed to the marking primitive) must be unused
- in practice, this means you must mark an object locked immediately after constructing it
- API
- the method `lockPermanently` is used to lock an object permanently
- there is a predicate `isLockedPermanently` which can test whether an object is locked or not
- for initial experiments, these methods are in `sun.misc.Unsafe`; perhaps they belong on `Object` (cf. `clone`)`
I'm not seeing the 400x more memory - there is a 40x though. But if you add up the columns for the programs that have both C and Java versions, you get this rough summary...
secs KB gz
Java 76.33 2004048 12775
C gcc 37.32 793652 11651
- Cyberduck is written in Java, yet nobody seems to be complaining about how slow and bloated it is.
- There exists a version of Quake 2 written in Java: http://bytonic.de/html/benchmarks.html It seems to be able to push out more frames than native, actually.
Both of those are real software that actually run well on Java, regardless of penalty paid for running in a VM, JIT, and GC.
Also when looking at the amount of memory and time taken when comparing C to Java in the microbenchmarks, always be sure to mentally factor in the base overhead of starting up the JVM both in time and memory. It's pretty easy to see that when a C version takes up something like 100KB of memory and the Java one takes up 30MB, Java consistently takes up at least ~30MB regardless of how much memory is required for that microbenchmark. When the C version takes up 300MB and the Java one takes up 700MB, that's a bit better of a comparison. (though still not perfect, because the Java GC will reserve a lot of memory for itself, even if it isn't using the full 700MB, if it feels it needs that much, etc.)
Lol I just double checked that after you said it, it never felt "Javaish" even the interface is really sane.
Actually they are using JNA for a lot of stuff and they written foundation bindings... (https://g.iterate.ch/projects/ITERATE/repos/cyberduck/browse...) cool stuff I keep that for reference. However he should put the bindings stuff under something like LGPL since most stuff will fall under fair use anyway (simple class Names which you would use anyway even without looking at the Source when making a JNA binding to Cocoa)
The table in your link shows it being 6% faster in one (literally) corner case, while all the other entries show it being slower by varying amounts. Keep in mind that in this benchmark a lot of the "heavy lifting" is being done by the GPU via OpenGL, so it isn't great for benchmarking languages that run on the CPU. It also doesn't mention what the "Original C Code" was compiled with.
Not much for those programs:
http://benchmarksgame.alioth.debian.org/sometimes-people-jus...
>> It's pretty easy to see … memory
mandelbrot 17% slower
fannkuch-redux 34% slower
fasta 38% slower
fasta-redux 39% slower
pidigits 44% slower
spectral-norm 115% slower
reverse-compliment 121% slower
n-body 136% slower
regex-dna 235% slower
k-nucleotide 253% slower
As for being dishonest, well, you're commenting from a newly minted temp account so it would seem you didn't have the courage/backbone to use your real one.