Why java is slow

The Real World

The moment you start using objects in your program, Java looses the potential
for optimization. This section lists some of the reasons why.

1. All Objects are Allocated on the Heap

Java only allocates primitive data types like int and double and object
references on the stack. All objects are allocated on the heap.

For large objects which usually have identity semantics, this is not a handicap.
C++ programmers will also allocate these objects on the heap.
However, for small objects with value semantics, this is a major performance killer.

What small objects? For me these are iterators. I use a lot of them in my designs.
Someone else may use complex numbers. A 3D programmer may use a
vector or a point class. People dealing with time series data will use a time class.
Anybody using these will definitely hate trading a zero-time stack
allocation for a constant-time heap allocation. Put that in a loop and that becomes
O (n) vs. zero. Add another loop and you get O (n^2) vs. again, zero.

2. Lots of Casts

With the advent of templates, good C++ programmers have been able to avoid casts
almost completely in high-level programs. Unfortunately, Java doesn’t have templates,
so Java code is typically full of casts.

What does that mean for performance? Well, all casts in Java are dynamic casts,
which are expensive. How expensive? Consider how you would implement a dynamic cast:

The fastest thing you could do is assign a number to each class and then have a
matrix that tells if any two classes are related, and if they are, what is the
offset that needs to be added to the pointer in order to make the cast.
In that case, the pseudo-code for the cast would look something like this:

DestinationClass makeCast (Object o, Class destinationClass) {
Class sourceClass = o.getClass (); // JIT compile-time
int sourceClassId = sourceClass.getId (); // JIT compile-time

int destinationId = destinationClass.getId ();

int offset = ourTable [sourceClassId][destinationClassId];

if (offset != ILLEGAL_OFFSET_VALUE) {
return ;
else {
throw new IllegalCastException ();
Quite a lot of code, this little cast! And this here is a rosy picture
-using a matrix to represent class relationships takes up a lot of memory and no
sane compiler out there would do that. Instead, they will either
use a map or walk the inheritance hierarchy – both of which will slow things down even further.

3. Increased Memory Use

Java programs use about double the memory of comparable C++ programs
to store the data. There are three reasons for this:

Programs that utilize automatic garbage collection typically use
about 50% more memory that programs that do manual memory management.
Many of the objects that would be allocated on stack in C++ will
be allocated on the heap in Java.
Java objects will be larger, due to all objects having a virtual table
plus support for synchronization primitives.
A larger memory footprint increases the probability that parts of the
program will be swapped out to the disk. And swap file usage kills the
speed like nothing else.

4. Lack of Control over Details

Java was intentionally designed to be a simple language. Many of the
features available in C++ that give the programmer control over details were
intentionally stripped away.

For example, in C++ one can implement schemes that improve the locality
of reference. Or allocate and free many objects at once. Or play pointer
tricks to make member access faster. Etc.

None of these schemes are available in Java.

5. No High-Level Optimizations

Programmers deal with high-level concepts. Unlike them, compilers deal
exclusively with low-level ones. To a programmer, a class named Matrix
represents a different high-level concept from a class named Vector.
To a compiler, those names are only entries in the symbol table.
What it cares about are the functions that those classes contain,
and the statements inside those functions.

Now think about this: say you implement the function exp (double x, double y)
that raises x to the exponent y. Can a compiler,
just by looking at the statements in that function, figure out that exp (exp (x, 2), 0.5)
can be optimized by simply replacing it with x? Of course not!

All the optimizations that a compiler can do are done at the statement level,
and they are built into the compiler.
So although the programmer might know that two functions are symmetric and
cancel each other now, or that the order of some function calls is irrelevant
in some place,
unless the compiler can figure it out by looking at the statements,
the optimization will not be done.

So, if a high-level optimization is to be done, there has to be a way
for the programmer to specify the high-level optimization rules for the compiler.

No popular programming language/system does this today. At least not
in the totally open sense, like what the Microsoft’s Intentional
Programming project promises.
However, in C++ you can do template metaprogramming to implement
optimizations that deal with high-level objects. Temporary elimination,
partial evaluation,
symmetric function call removal and other optimizations can be implemented
using templates. Of course, not all high-level optimizations can be done this way.
And implementing some of these things can be cumbersome. But a lot can be done,
and people have implemented some snazzy libraries using these techniques.

Unfortunately, Java doesn’t have any metaprogramming facilities, and thus high-level
optimizations are not possible in Java.


Java, with the current language features, will never be as fast as C++. This pretty much means that it’s not a sensible choice for high-performance software and
the highly competitive COTS arena. But its small learning curve, its forgiveness, and its large standard library make it a good choice for some small and
medium-sized in-house and custom-built software.

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