I use == and != a lot in my code and I was wondering which is quicker in objective c so that I can make my app as fast as possible.
Situation
I have a variable which is one of two things and I want the quickest method to see which one it is
Thanks in advance
You should not worry about this level of detail for performance reasons, unless you've identified a performance issue.
However, wondering to satisfy an inquiring mind is a different matter! :-) The answer is they are identical.
A comparison is usually compiled as an instruction which sets condition flags; this could be a specific comparison instruction or something like an arithmetic instruction which sets condition codes; followed by a conditional jump which tests the condition flags - and a test for "equal" is the same cost as for "not equal", just a different setting of those condition flags.
This also means that statements such as if([some method call]) ... and if(![some method call]) ... have the same cost - the "not" operator produces no extra code.
You can test yourself.
Check current milliseconds before and after operating.
I guess there's no differences..
If you really need to know,
you could make a lot of operating with loop.
then you will get the answer.
This is silly. You would have to execute millions of iterations of code using the 2 versions of if statement in order to even detect a difference in speed. This is a triviality, and not worth worrying about.
As the other poster said, == and != should take exactly the same amount of time for non-floatingpoint values. For floating point, there might be some differences, since for an equal comparison the processor has to first normalize the 2 floating point values, then compare them, and normalizing is relatively time-consuming. I don't know if testing for non-equality if slower than equality. IT's unlikely but not impossible.
Related
I am trying to find an optimal solution using the Z3 API for python. I have used set_option("verbose", 1) to print statements that Z3 generates while checking for sat. One of the statements it prints is pb.conflict statements. The statements look something like this -
pb.conflict statements.
I want to know what exactly is pb.conflict. What do these statements signify? Also, what are the two numbers that get printed along with it?
pb stands for Pseudo-boolean. A pseudo-boolean function is a function from booleans to some other domain, usually Real. A conflict happens when the choice of a variable leads to an unsatisfiable clause set, at which point the solver has to backtrack. Keeping the backtracking to a minimum is essential for efficiency, and many of the SAT engines carefully track that number. While the details are entirely solver specific (i.e., those two numbers you're asking about), in general the higher the numbers, the more conflict cases the solver met, and hence might decide to reset the state completely or take some other action. Often, there are parameters that users can set to specify when such actions are taken and exactly what those are. But again, this is entirely solver and implementation specific.
A google search on pseudo-boolean optimization will result in a bunch of scholarly articles that you might want to peruse.
If you really want to find Z3's treatment of pseudo-booleans, then your best bet is probably to look at the implementation itself: https://github.com/Z3Prover/z3/blob/master/src/smt/theory_pb.cpp
I'm experimenting with Z3 (using the python api) where I'm building up a scheduling model for a class assignment, where I have to use modulo quite often (because its periodic). Modulo seems already to slow down z3 by a lot, but if I try do some optimization on top (minimize a cost function which is a sum), then it takes quite some time for fairly small problems.
Without optimization it works okayish (few seconds for a smaller problem). So that being said, I have now 2 questions:
1) Is there any trick with the modulo function of how to use it? I already assign the modulo value to a function. Or is there any other way to express periodic/ring behavior?
2) I am not interested in finding THE best solution. A good one, will be good enough. Is there a way to set some bounds for the cost function. Like, if know the upper and lower bound of it? Any other tricks, where I could use domain knowledge to find solutions fast.
Furthermore, I thought that if I ll use timeout option solver.set("timeout" 10000), then the solver would time out with the best solution so far. That doesnt seem to be the case. It just times out.
Impossible to comment on the mod function without seeing some code. But as a rule of thumb, division is difficult. Are you using Int values, or bit-vectors? If you are using unbounded integers, you might want to try bit-vectors which might benefit from better internal heuristics. Or try Real values, and then do a proper reduction.
Regarding how to get the "best so far" optimal value, see this answer: Finding suboptimal solution (best solution so far) with Z3 command line tool and timeout
Instead of using the built-in modulo and division, you could introduce uninterpreted functions mymod and mydiv, for which you only provide the necessary axioms of division and modulo that your problem requires. If I remember correctly, Microsoft's Ironclad and/or Ironfleet team did that when they had modulo/division-related performance problems (using the pipeline Dafny -> Boogie -> Z3).
Instead of adding the PLinq extension statement AsParallel() manually could not the compiler figure this out for us auto-magically? Are there any examples where you specifically do not want parallelization if the code supports it?
I do research in the area of automatic parallelization. This is a very tricky topic that is the subject of many Ph.D. dissertations. Static code analysis and automatic parallelization has been done with great success for languages such as Fortran, but there are limits to the compiler's ability to analyze inter-regional dependencies. Most people would not be willing to sacrifice the guarantee of code correctness in exchange for potential parallel performance gains, and so the compiler must be quite conservative in where it inserts parallel markers.
Bottom line: yes, a compiler can parallelize code. But a human can often parallelize it better, and having the compiler figure out where to put the markers can be very, very, very tricky. There are dozens of research papers available on the subject, such as the background work for the Mitosis parallelizing compiler or the D-MPI work.
Auto parallelization is trickier than it might initially appear. It's that "if the code supports it" part that gets you. Consider something like
counter = 0
f(i)
{
counter = counter + 1
return i + counter
}
result = map(f, {1,2,3,4})
If the compiler just decides to parallelize map here, you could get different results on each run of the program. Granted, it is obvious that f doesn't actually support being used in this manner because it has a global variable. However if f is in a different assembly the compiler can't know that it is unsafe to parallelize it. It could introspect the assembly f is in at runtime and decide then, but then it becomes a question of "is the introspection fast enough and the dynamic parallelization fast enough to not negate the benefits from doing this?" And sometimes it may not be possible to introspect, f could be a P/Invoked function, that might actually be perfectly suited to parallelization, but since the runtime/compiler has no way of knowing it has to assume it can't be. This is just the tip of the iceberg.
In short, it is possible, but difficult, so the trade-off between implementing the magic and the benefits of the magic were likely skewed too far in the wrong direction.
The good news is that the compiler researchers say that we are really close to having automatically parallelizing compilers. The bad news is that they have been saying that for fifty years.
The problem with impure languages such as C# is usually that there is not enough parallelism. In an impure language, it is very hard for a human and pretty much impossible for a program to figure out if and how two pieces of code interact with each other or with the environment.
In a pure, referentially transparent, language, you have the opposite problem: everything is parallelizable, but it usually doesn't make sense, because scheduling a thread takes way longer than just simply executing the damn thing.
For example, in a pure, referentially transparent, functional language, if I have something like this:
if a <= b + c
foo
else
bar
end
I could fire up five threads and compute a, b, c, foo and bar in parallel, then I compute the + and then the <= and lastly, I compute the if, which simply means throwing away the result of either foo or bar, which both have already been computed. (Note how this depends on being functional: in an impure language, you cannot simply compute both branches of an if and then throw one away. What if both print something? How would you "unprint" that?)
But if a, b, c, foo and bar are really cheap, then the overhead of those five threads will be far greater than the computations themselves.
Seems like it's inconsistent in the lists module. For example, split has the number as the first argument and the list as the second, but sublists has the list as the first argument and the len as the second argument.
OK, a little history as I remember it and some principles behind my style.
As Christian has said the libraries evolved and tended to get the argument order and feel from the impulses we were getting just then. So for example the reason why element/setelement have the argument order they do is because it matches the arg/3 predicate in Prolog; logical then but not now. Often we would have the thing being worked on first, but unfortunately not always. This is often a good choice as it allows "optional" arguments to be conveniently added to the end; for example string:substr/2/3. Functions with the thing as the last argument were often influenced by functional languages with currying, for example Haskell, where it is very easy to use currying and partial evaluation to build specific functions which can then be applied to the thing. This is very noticeable in the higher order functions in lists.
The only influence we didn't have was from the OO world. :-)
Usually we at least managed to be consistent within a module, but not always. See lists again. We did try to have some consistency, so the argument order in the higher order functions in dict/sets match those of the corresponding functions in lists.
The problem was also aggravated by the fact that we, especially me, had a rather cavalier attitude to libraries. I just did not see them as a selling point for the language, so I wasn't that worried about it. "If you want a library which does something then you just write it" was my motto. This meant that my libraries were structured, just not always with the same structure. :-) That was how many of the initial libraries came about.
This, of course, creates unnecessary confusion and breaks the law of least astonishment, but we have not been able to do anything about it. Any suggestions of revising the modules have always been met with a resounding "no".
My own personal style is a usually structured, though I don't know if it conforms to any written guidelines or standards.
I generally have the thing or things I am working on as the first arguments, or at least very close to the beginning; the order depends on what feels best. If there is a global state which is chained through the whole module, which there usually is, it is placed as the last argument and given a very descriptive name like St0, St1, ... (I belong to the church of short variable names). Arguments which are chained through functions (both input and output) I try to keep the same argument order as return order. This makes it much easier to see the structure of the code. Apart from that I try to group together arguments which belong together. Also, where possible, I try to preserve the same argument order throughout a whole module.
None of this is very revolutionary, but I find if you keep a consistent style then it is one less thing to worry about and it makes your code feel better and generally be more readable. Also I will actually rewrite code if the argument order feels wrong.
A small example which may help:
fubar({f,A0,B0}, Arg2, Ch0, Arg4, St0) ->
{A1,Ch1,St1} = foo(A0, Arg2, Ch0, St0),
{B1,Ch2,St2} = bar(B0, Arg4, Ch1, St1),
Res = baz(A1, B1),
{Res,Ch2,St2}.
Here Ch is a local chained through variable while St is a more global state. Check out the code on github for LFE, especially the compiler, if you want a longer example.
This became much longer than it should have been, sorry.
P.S. I used the word thing instead of object to avoid confusion about what I was talking.
No, there is no consistently-used idiom in the sense that you mean.
However, there are some useful relevant hints that apply especially when you're going to be making deeply recursive calls. For instance, keeping whichever arguments will remain unchanged during tail calls in the same order/position in the argument list allows the virtual machine to make some very nice optimizations.
Should I use unsigned integers for my count class members?
Answer
For example, assume a class
TList <T> = class
private
FCount : Cardinal;
public
property Count : Cardinal read FCount;
end;
That does make sense, doesn't it? The number of items stored in a list can't be negative, so why not use an unsigned integer type for it? I think it's in general a good principle to always use the least general (ergo the most special) type possible.
Now, iterating over a list looks like this:
for I := 0 to List.Count - 1 do
Writeln (List [I]);
When the number of items stored in the list is zero, the compiler tries to evaluate
List.Count - 1
which results in a nice Integer overflow (underflow to be exact). Combined with the fact that the debugger does not show the appropriate location where the exception occured, this was very hard to find for me.
Let me add that if you have overflow checking turned off, the resulting errors will be even harder to track, because then you will often access memory that doesn't belong to you - and that results in undefined behaviour.
I will be using plain Integers for all my count members from now on to avoid situations like this.
If that's complete nonsense, please point it out to me :)
(I just spent an hour tracking an integer overflow in my code, so I decided to share that - most people on here will know that of course, but perhaps I can save someone some time.)
No, definitely not. Delphi idiom is to use integers here. Don't fight the language.
In a 32 bit environment you'll not have more elements in the list, except if you try to build a bitmap.
Let's be clear: every programmer who is going to have to use your code is going to hate you for using a Cardinal instead of an integer.
Unsigned integers are almost always more trouble than they're worth because you usually end up mixing signed and unsigned integers in expressions at some point. That means that the type will need to be widened (and probably have a performance hit) to get correct semantics (ideally the compiler does this as per language definition), or else you'll need to be very careful in your range checking.
Take C/C++ for example: size_t is the type of the integer for memory sizes and allocation, and is unsigned, but ptrdiff_t is the type for the offset you get when you subtract one pointer from another, and necessarily is signed. Want to know how many elements you've allocated in an array? Perhaps you subtract the first element address from the last+1 element address and divide by sizeof(element-type)? Well, now you've just mixed signed and unsigned integers.
Regarding your statement that "I think it's in general a good principle to always use the least general (ergo the most special) type possible." - actually I think it's a good principle to use the data type that will cause you least angst and trouble.
Generally for me that's a signed int since:
I don't usually have lists with 231 or more elements in them.
You shouldn't have lists that big either :-)
I don't like the hassle of having special edge cases in my code.
But it's really a style issue. If 'purity' of code is more important to you than brevity of code, your method is best (with modifications to catch the edge cases). Myself, I prefer brevity since edge cases tend to clutter the code and reduce understanding.
Don't.
It's not just going against a programming idiom, it's an explicit request to the compiler to use unsigned arithmetic, that is either prone to anomalous behaviors (if you don't guard against overflows) or to irrelevant runtime exceptions (if you guard against overflows, a temporary overflow will be fatal, f.i when you subtract before adding, even if the final result is positive, and I'm referring to the CPU opcode-level ordering of operations, which may not bear a trivial relationship to what you have in your code).
Keep in mind "unsigned" does not translate to "positive", it translates to "doesn't have a sign", which is different. The term "unsigned" was picked for good reason (and naming it "Cardinal" in Delphi was a poor choice IMO).
Unsigned types are for raw storage specifications, bitwise operations, ASM code, embedded controllers and other specialty uses. When you're doing high-level programming, you should forget you ever heard about unsigned types.
Moral: use iterators and foreach when you can, because it avoids this question altogether.
Boundary conditions frequently present problems. Allowing for a type that can go negative may just shift the issue. Perhaps it shifts it in a way that's easier to debug, perhaps not. I started off using integers for counting loops like that, but later on switched to cardinals to help me catch errors.