Slashdot Mirror
Optimizations - Programmer vs. Compiler?
Saravana Kannan asks: "I have been coding in C for a while (10 yrs or so) and tend to use short code snippets. As a simple example, take 'if (!ptr)' instead of 'if (ptr==NULL)'. The reason someone might use the former code snippet is because they believe it would result in smaller machine code if the compiler does not do optimizations or is not smart enough to optimize the particular code snippet. IMHO the latter code snippet is clearer than the former, and I would use it in my code if I know for sure that the compiler will optimize it and produce machine code equivalent to the former code snippet. The previous example was easy. What about code that is more complex? Now that compilers have matured over years and have had many improvements, I ask the Slashdot crowd, what they believe the compiler can be trusted to optimize and what must be hand optimized?"
"How would your answer differ (in terms of the level of trust on the compiler) if I'm talking about compilers for Desktops vs. Embedded systems? Compilers for which of the following platforms do you think is more optimized at present - Desktops (because is more commonly used) or Embedded systems (because of need for maximum optimization)? Would be better if you could stick to free (as in beer) and Open Source compilers. Give examples of code optimizations that you think the compiler can/can't be trusted to do."
Programmer: Hey, compiler. How do you like optimizing?
Compiler: Optimizing? Optimizing? Don't talk to me about optimizing. Here I am, brain the size of a planet, and they've got me optimizing inane snippets of code. Just when you think code couldn't possibly get any worse, it suddenly does. Oh look, a null pointer. I suppose you'll want to see the assembly now. Do you want me to go into an infinite loop or throw an exception right where I'm standing?
Programmer: Yeah, just show me the stack trace, won't you compiler?
A programmer is a machine for converting coffee into code.
I think writing clear and easy to understand code is more important in the long run, especially if other people will have to look at it.
Optimize. Using cryptic, short variable names also shaves valuable microseconds off compile time and run time.
Donald Knuth wrote "We should forget about small efficiencies, about 97% of the time. Premature optimization is the root of all evil."
The sad truth is that, as far as optimization goes, this isn't where attention is most needed.
Before we start worrying about things like saving two cycles here and there, we need to start teaching people how to select the proper algorithm for the task at hand.
There are too many programmers who spend hours turning their code into unreadable mush for the sake of squeezing a few milliseconds out of a loop that runs on the order of O(n!) or O(2^n).
For 99% of the coders out there, all that needs to be known about code optimization is: pick the right algorithms! Couple this with readable code, and you'll have a program that runs several thousand times faster than it'll ever need to and is easy to maintain--and that's probably all you'll ever need.
Obliteracy: Words with explosions
It's better to write clear, legible code that saves a human minutes of reading, than complex code that might save a computer a few milliseconds of processing time per year, because human time costs more than machine time.
Also the clear code will result in fewer misinterpretations, which will mean fewer bugs (especially when the original author is not the one doing maintenance years later), further reducing costs in dollars, man hours, and frustration.
I just checked the U.S. Patent office and sure enough, just minutes after your post, Microsoft patented "if (!ptr)" as a shorthand for "if (ptr==NULL)".
Prepare to be sued.
"What the hell is an aluminum falcon?"
Hard to measure, but what is the tradeoff between increased speed and increased readability (which is a prerequisite for correctness and maintainability)? And if you can estimate that tradeoff, which is more important to the goals of your application?
As a side note, it is far more important to make sure you are using efficient algorithms and data structures than to make minor local optimizations. I've seen programmers use bizarre local optimization tricks in a module that ran in exponential time rather than log time.
Sheesh, evil *and* a jerk. -- Jade
What about code that is more complex? Now that compilers have matured over years and have had many improvements, I ask the Slashdot crowd, what they believe the compiler can be trusted to optimize and what must be hand optimized?
Programmers cost lots more per hour than computer time. Let the compiler optimize and let the programmers concentrated on developing solid maintainable code.
If you make code too clever in an effort to try to pre-optimize, you end up with code that other people have difficulty understanding. This is leads to lower quality code as it evolves if the people that follow you are not as savvy.
Not only that, but the vast majority of code written today is UI-centric or I/O bound. If you want real optimization, design a harddrive/controller combo that gets you 1 GBps off the physical platter (and at a price that consumers can afford).
I got in the habit of writing "readable but inefficient" code, taking care that my constructs don't get too sophisticated for the optimizer but then depending on gcc -O3 thoroughly. And then it happened I had to program 8051 clone. Then I learned there are no optimizing compilers for '51, that I'm really tight on CPU cycles, and that I simply don't know HOW to write really efficient C code.
Ended up writing my programs in assembler...
45 5F E1 04 22 CA 29 C4 93 3F 95 05 2B 79 2A B2
As a simple example, take 'if (!ptr)' instead of 'if (ptr==NULL)'.
Both forms resolve to the same opcode. Even under my 6502 compiler.
CMP register,val
JNE
Enjoy,
It's just the normal noises in here.
1) Code for maintainability
2) Profile your code
3) Optimize the bottlenecks
That said, (!ptr) should be just as maintanable as (ptr == NULL) simply because it is a frequently used 'dialect'. As long as these 'shortcuts' are used throughout the entire codebase they should be familiar enough that they don't get in the way of maintainability.
What you're talking about it micro-optimization.
Compilers are pretty good at that, and you should let them do their job.
Programmers should optimize at a higher level: by their choice of algorithms, organizing the program so that memory access is cache-friendly, making sure various objects don't get destroyed and re-created unnecessarily, that sort of thing.
"ptr == 0" must give the same result as "ptr == NULL", always.
...are doomed to repeat the biggest trap in computer programming over and over again:
"Premature optimization is the root of all evil"
If there's only one rule in computer programming a person ever learns, "Hoare's dictum" is the one I would choose.
Almost all modern languages have extensive libraries available to handle common programming tasks and can handle the vast majority of optimizations you speak of automatically. This means that 99.99% of the time you shouldn't be thinking about optimizations at all. Unless you're John Carmack or you're writing a new compiler from scratch (and perhaps you are) or involved in a handful of other activities you're making a big big mistake if your spending any time worrying about these things. There are far more important things to worry about, such as writing code that can be understood by others, can easily be units tested, etc.
A few years ago I used to write C/C++/asm code extensively and used to be obsessed with performance and optimization. Then, one day, I had an epiphany and started writing code that is about 10 times slower than my old code (different in computer language and style) and infinitely easier to understand and expand. The only time I optimize now is at the very very end of development when I have solid profiler results from the final product that show noticable delays for the end user and this only happens rarely.
Of course, this is just my own personal experience and others may see things differently.
With regard to your example, I can't imagine any modern compiler wouldn't treat the two as equivalent.
However, in your example, I actually prefer "if (!ptr)" to "if (ptr == NULL)", for two reasons. First the latter is more error-prone, because you can accidentally end up with "if (ptr = NULL)". One common solution to avoid that problem is to write "if (NULL == ptr)", but that just doesn't read well to me. Another is to turn on warnings, and let your compiler point out code like that -- but that assumes a decent compiler.
The second, and more important, reason is that to anyone who's been writing C for a while, the compact representation is actually clearer because it's an instantly-recognizable idiom. To me, parsing the "ptr == NULL" format requires a few microseconds of thought to figure out what you're doing. "!ptr" requires none. There are a number of common idioms in C that are strange-looking at first, but soon become just another part of your programming vocabulary. IMO, if you're writing code in a given language, you should write it in the style that is most comfortable to other programmers in that language. I think proper use of idiomatic expressions *enhances* maintainability. Don't try to write Pascal in C, or Java in C++, or COBOL in, well, anything, but that's a separate issue :-)
Oh, and my answer to your more general question about whether or not you should try to write code that is easy for the compiler... no. Don't do that. Write code that is clear and readable to programmers and let the compiler do what it does. If profiling shows that a particular piece of code is too slow, then figure out how to optimize it, whether by tailoring the code, dropping down to assembler, or whatever. But not before.
Note to ACs: I usually delete AC replies without reading them. If you want to talk to me, log in.
"Programs should be written for people to read, and only incidentally for machines to execute."
- Structure and Interpretation of Computer Programs
Each compiler is different. Some will optimise things other won't.
In general, however, systems are now fast enought that when in doubt, write the clearest code possible. I mean for most apps, speed is not critical, however for all apps stability and lack of bugs is important and obscure code leads to problems.
Also, for things that are time critical, it's generall just one or two little parts that make all the difference. You only need to worry about optimizing those inner loops where all the time is spent. Use a profiler, since programmers generally suck at identifying what needs optimising.
Keep it easy to read and maintain, unless speed is critical in a certian part. Then you can go nuts on hand optimization, but document it well.
LLVM is an aggressive compiler that is able to do many cool things. Best yet, it has a demo page here: http://llvm.org/demo, where you can try two different things and see how they compile.
:)
One of the nice things about this is that the code is printed in a simple abstract assembly language that is easy to read and understand.
The compiler itself is very cool too btw, check it out.
-Chris
Donald Knuth was quoating Tony Hoare when he said that.
*sigh* back to work...
NULL isn't necessarily equal to 0 at the machine level. However, at the language level, 0 is always interpreted exactly the same as NULL if it's being converted to a pointer, and vice versa. This is explicitly spelled out in the C standard, so any compiler that doesn't obey this is breaking the standard. Saying !ptr and ptr == NULL is always identical on a conforming compiler (which they pretty much all are).
Mod down posts with a "Free Mac Mini/iPod" sig, they're spam!
Grrr, you named the algorithm that must not be named! Cursed be the name of the fool who thought it would be a good algorithm for introductory students - I've lost count of the number of people convinced that this satan-spawned algorithm is faster than an insertion sort (it's not) and that there's no reason for them to learn to use the qsort() function. N.B., not to implement a quick sort, but to simply call a standard library routine.
The most frustrating thing is that, if you must use the algorithm that must not be named, the bidirectional form of the algorithm is much faster (in practice) than the unidirectional form yet really no more complex to code than the latter if you have any potential as a software developer.
For every complex problem there is an answer that is clear, simple, and wrong. -- H L Mencken
...then the code isn't important enough to optimize. Plain and simple.
Never try to optimize anything unless you have measured the speed of the code before optimizing and have measured it again after optimizing.
Optimized code is almost always harder to understand, contains more possible code paths, and more likely to contain bugs than the most straightforward code. It's only worth it if it's really faster...
And you simply cannot tell whether it's faster unless you actually time it. It's absolutely mindboggling how often a change you are certain will speed up the code has no effect, or a truly negligible effect, or slows it down.
This has always been true. In these days of heavily optimized compilers and complex CPUs that are doing branch prediction and God knows what all, it is truer than ever. You cannot tell whether code is fast just by glancing at it. Well, maybe there are processor gurus who can accurately visualize the exact flow of all the bits through the pipeline, but I'm certainly not one of them.
A corollary is that since the optimized code is almost always trickier, harder to understand, and often contains more logic paths than the most straightforward code, you shouldn't optimize unless you are committed to spending the time to write a careful unit-test fixture that exercises everything tricky you've done, and write good comments in the code.
"How to Do Nothing," kids activities, back in print!
The compiler will perform strength reduction in all reasonable instances.
The compiler will raise invariant computations from inner loops in almost all cases that do not involve pointers.
The compiler knows how to optimize integer division in ways I wouldn't have even thought of.
The compiler sometimes "forgets" about a register and produces sub-optimal code for inner loops.
The compiler can't always tell what variable is most important to keep in a register in an inner loop.
Other stuff:
x^=y; y^=x; x^=y; optimizes to an XCHG instruction with gcc on x86. I was amazed that it could do that. (Yes, that piece of code exchanges x and y). On the other hand, tmp=x; x=y; y=tmp; doesn't get optimized to an XCHG. Obviously, the compiler is using a Boolean simplifier or identity-prover.
The compiler always assumes a branch will be taken (unless you use certain compiler switches to change this behavior). Thus you should always arrange your conditional tests so that the less-often executed code is within the braces.
Don't be afraid to write complex expressions. Subexpression elimination is almost foolproof in all instances where pointers are NOT involved. It's better to leave your code clear, and let the compiler optimize it.
And ABOVE ALL:
No matter how much the compiler optimizes your code, you can throw it all down the toilet with bad design by screwing the cache utilization. This is EXTREMELY important especially in graphical applications which process huge raster buffers. Row-wise processing is always more efficient than column-wise. Random access will kill your performance. Do not trust the memory allocator to keep your allocations together. Write your own allocator if you are dealing with thousands or millions of small, related chunks of information.
I could go on... But I must also second what others have said, which is to perform algorithmic optimizations FIRST and do not bother with constant-factor optimizations until you are CERTAIN that you are using the best algorithm. If you ignore this advice you might waste a week optimizing a three-line inner loop and then come up with a better algorithm the next week which makes all your hard work redundant.
When I wrote my ray-tracer for the final project of my graphics class, I used gcc -o3 and it optimized my code into Pov-ray, which was sweet. I was done with the project in like ten minutes.
Plus I got extra credit for implementing phong shading. I didn't even try to do phong shading.
I make my code easy to read for my own sanity. I've lived out this bash.org quote way too many times.
"Upon attaching the waterblock to my penis, I began to notice that I know nothing about computers." -- JRockway
And believe me it is a pain in the a$$. Our company did the verification for the code in the microprocessor that controls the locks to the bathroom door on a 777, if the crapper tank is full then the door locks to make sure there isn't an overflow and thus frozen turd/urine meteors that fall from the sky. Every byte of the code MUST be excercised including all error conditions.
So how many dumps does it take to fill up the crapper tank? I'd hate to be the last QA engineer in line to use the crapper. Also what happens when that last engineer fills up the crapper, does the bathroom door look thus trapping him inside?
Premature Optimization is the DEVIL! I repeat, it is the gosh darn DEVIL! Don't do it. Write clear code so that I don't have to spend days trying to figure out what you are trying to do.
The biggest mistake I see in my professional (and unprofessional) life is programmers who try to optimize their code is all sorts of "733+" ways, trying to "trick" the compiler into removing 1 or 2 lines of assembly, yet completely disregard that they are using a map instead of a hash_map, or doing a linear search when they could do a binary search, or doing the same lookup multiple times, when they could do it just once. It's just silly, and goes to show that lots of programmers don't know how to optimize effectively.
Compilers are good. They optimize code well. Don't try to help them out unless you know your code has a definite bottleneck in a tight loop that needs hand tuning. Focus on using correct algorithms and designing your code from a high level to process data efficiently. Write your code in a clear and easy to read manner, so that you or some other programmer can easily figure out what's going on a few months down the line when you need to add fixes or new functionality. These are the ways to build efficient and maintainable systems, not by writing stuff that you could enter in an obfuscated code contest.
+1 Insightful, -1 Troll. What can I say, I'm an Insightful Troll.
- How often are functions called (and branches taken)
- Which functions take most of the time
- See the assembler code for each line with a mouse click (no need to guess anymore)
callgrind/kcachegrind is by far the easiest profiling solution I ever tried, and it seems answer more or less all of your questions.I think that most people forget that the reason that i, j, k, etc. are used for loop counters is that unless otherwise declared, I..N default to INTEGER in FORTRAN. This convention just carried over as programmers migrated from FORTRAN to other languages and has been passed down through the ages.
(S(SKK)(SKK))(S(SKK)(SKK))
For a cheap, fast batch lookups I once wrote a hashed matrix using STL. Loaded all the cells, dynamically typed, added indexes on the data for that run, and then passed around this collection of in-memory tables to our routines. Ran fast and was simple to debug, since all the traversing was O(ln(n)) based (or a variant thereof). Adding serialization, we could distribute to machines overnight dynamically and cut the run to a few minutes - from almost 8 hours.
Until it came time to dipose the memory. The STL slowly crawled tons of our objects, and the C++ dispose pattern was just too inefficient for all the stack hits. So we pointed the library at a custom heap and never disposed the dictionary - we just disposed the heap in bulk.
All written without hesitation for "longhand" syntax. (and btw, its "if ( NULL == var ) " to those that care). The code optimized fine, with just a few choice inlines we got to stick. No reg vars, no assembly piles littering the code.
But this was an in-house business app, and the lifecycles / requirements are different than other products. However, because of the nice algorithms, optimization wasn't difficult, and didn't rely on code tricks. If you're squabbling over code tricks for optimization, you're choosing the wrong algorithm, to me.
If by "const references" you really mean a
C++ reference, OK. If you mean a pointer though,
and you use C, the compiler is prohibited from
performing this optimization unless you also use
the "restrict" keyword.
Since you did mention "restrict", it appears that
you are working with C. "restrict" is not a C++
keyword.
BTW, inlinedamnit is __attribute__((__alwaysinline__))
for gcc and __forceinline for Microsoft.
I've known some very good first rate programmers who religiously put the constants on the left. I've never known a second rate programmer who did.
Second: Do it later. There are thousands of situations where you can postpone the actual computations. Imagine writing a Matrix class with the invert() method. You can actually postpone calculating the inverse of the matrix until there is a call to access on of the fields in the matrix. Also you can calculate only the field being accessed. Or at some sensible threshold you may assume that the user code will read the entire inverted matrix and you can just calculate the remaining inverted fields... the options are endless.
Most string class implementations already make good use of this rule by only copying their buffers only when the "copied" buffer changes.
Third: Apply minimum algorithmic complexity. If you can use a hashmap instead of a treemap use the hash version it's O(1) vs Olog(n). Use quicksort for just about any kind of sorting you need to do.
Fourth: Cache your data. Download or buy a good caching class or use some facilities your language provides (eg. Java SoftReference class) for basic caching. There are some enormous performance gains that can be realized with smart caching strategies.
Fifth: Optimize using your language constructs. User the register keyword, use language idioms that you know compile into faster code etc... Scratch this rule! If you're applying rules one to four you can forget about this one and still have fast AND readable code.
Your pizza just the way you ought to have it.
"My rule is never comment what the program does, comment why it does it."
Bah. Comments lie. Code never lies.
Need Mercedes parts ?
I got this job as a contractor 4 years ago now where the project was developed by over 30 junior developers and one crazy overpaid lady (hey, Julia,) who wouldn't let people touch her code so fragile it was (and it was the main action executor,) she would rather fight you for hours than make one change in the code (she left 2 months before the project release.) Now, I have never witnessed such monstrocity of a code base before - the business rules were redefined about once every 2 weeks dor 1.5 years straight. You can imagine.
So, the client decided not to pay the last million of dollars because the performance was total shit. On a weblogic cluster of 2 Sun E45s they could only achieve 12 concurrent transactions per second. So the client decided they really did not want to pay and asked us to make it at least 200 concurrent transactions per second on the same hardware. If I may make a wild guess, I would say the client really did not want to pay the last million, no matter what, so they upped the numbers a bit from what they needed. But anyway.
Myself and another developer (hi, Paul) spent 1.5 months - removing unnecessary db calls (the app was incremental, every page would ask you more questions that needed to be stored, but the app would store all questions from all pages every time,) cached XML DOM trees instead of reparsing them on every request, removed most of the session object, reduced it from 1Mb to about 8Kb, removed some totally unnecessary and bizarre code (the app still worked,) desynchronized some of the calls with a message queue etc.
At the end the app was doing 320 and over concurrent transactions per second. The company got their last million.
The lesson? Build software that is really unoptimized first and then save everyone's ass by optimizing this piece of shit and earn total admiration of the management - you are a miracle worker now.
The reality? Don't bother trying to optimize code when the business requirements are constantly changing, the management has no idea how to manage an IT dep't, the coders are so nube - there is a scent of freshness in the air and there is a crazy deadline right in front of you. Don't optimize, if the performance becomes an issue, optimize then.
You can't handle the truth.
HAL! Open the bathroom door!
I'm sorry Dave, you shouldn't have had that last burrito.
one product
one customer
420,000 lines
260 staff
no competition
no trade shows
no salespeople selling new features that have never been discussed
It's interesting to talk about their attention to detail, but to hold it up as a model for all software development neglects to consider that they are working under an entirely different set of constraints from most everyone else.
I think the example is fine; you just displayed an assumption that highlights one of the quirks of C.
! means "not" or "inverse of"; it is a boolean function. The variable ptr is a pointer; it is a reference to data, which means it isn't really data itself. !ptr shouldn't compute; a boolean operator should only work on boolean data. But C logical comparators are designed to work on everything. You are just supposed to know that 0 == NULL == false. This supposition is totally arbitrary and doesn't hold up in any language with strong typing.
This is what makes C difficult for beginners. Bad code compiles even though it has logical flaws, and ends up failing in mysterious ways.
The second case makes more sense. Equality is an operator that should work on all types of data. NULL is necessary if you are going to abstract data through the use of pointers or objects. Doing away with NULL would be equivalent to eliminating true and false and using 1 and 0 instead. Or eliminating strings and using sequences of ASCII codes. These substitutions are technically correct but in reality they make code unreadable.
As for simple code optimizations, here's what a modern compiler (Microsoft Visual C++
Beware: In C++, your friends can see your privates!
Ten years of programming in the language and you:
1) Don't know when two things are obviously equivalent to any non-brain dead compiler.
2) Think something other than readability matters.
3) Think the non-idiomatic way of doing something is more readable.
But I'm sure I'm just repeating the comments I can't be bothered reading.
Most compilers today will get all the simple stuff like if (!ptr) vs if (NULL == ptr) optimization. Its the more complex things that the compiler cannot "prove" where it has trouble. For example:
void h(int x, int y) {
for (i=0; i < N; i++) {
if (0 != (x & (1 << y))) {
f(i);
} else {
g(i);
}
}
}
Very few compilers will dare simplify this to:
void h(int x, int y) {
if (0 != (x & (1 << y))) {
for (i=0; i < N; i++) f(i);
} else {
for (i=0; i < N; i++) g(i);
}
}
Because the compilers have a hard time realizing that the conditional is constant and should be hoisted to the outside of the for loop. The compiler has the opportunity to perform loop unrolling in the second form that its may not try in the first instance.
You can learn these things from experience, or you can simply figure it out for yourself with the afore mentioned decompilation tools.
Here's my "guide to optimizing":
1) Are you disk I/O bound? You might need to switch to memory mapped files, or you might need to tweak the settings on the ones you have. You might need to use a lower level library to do your I/O. Many C++ iostreams implementations are slow, and many similar libraries involve lots of copying.
2) Are you socket I/O (or similar) bound? If so, you may need to rewrite with asynchronous I/O. This can be a PITA. Suck it up.
3) Are your threads spending all their time sitting in locks waiting for other threads? One, make sure you're using an appropriate number of worker threads optimized by the number of CPUs the host has. If you've already got the right number of threads, this can be a really tough decision. Presumably, the threads are helping your program readability, and trying to rework things into fewer threads is often a *bad idea*.
4) Are you spending all your time in malloc/new/constructor free/delete/deconstructor? Maybe you need to keep things on the stack, use a garbage collector, use reference counted objects, use pooled memory techniques, etc. In the right places, switching from some "string" library to const char* and stack buffers can give a huge benefit. Make sure, of course, that you use the "n" version of all standard string functions (the ones that take the size of the buffer as an argument) to avoid buffer overruns.
5) Are you spending all of your time in some system call? Like maybe some kind of WriteTextToScreen or FillRectangleWithPattern type of thing? For drawing code in general, try buffering things that are algorithmically generated in bitmaps, and only regenerate the parts that change. Then just blit together the pieces for your final output. Perhaps you need to rely on hardware transparency support for fast layer compositing. You might need fewer system level windows so you draw more in one function. Maybe you need to reduce your frame rate.
6) Are you using memcpy as appropriate?
If any of the previous items are true, you have no business worrying about the compiler. However, once you've gotten this far, you can start worrying about optimizing your code line by line.
7) Since you've gotten this far, the line(s) of code you're worried about are all inside some loop that gets run. A lot. They may be inside a function that's called from a loop too, of course. So, a few things to consider. A) You may need to use templates to get code that is optimized for the appropriate data type. B) You may need to split off a more focused version of the function from the general purpose function if it's also used in non-critical areas. This has negative maintainance ramifications. C) Do the bonehead obvious stuff like moving everything out of the loop that you can. D) Look at the assembly actually generated by your compiler. If you're not confortable with this, you have no business doing further optimization.
After looking at the assembler, then you'll know if the following are important. In my experience, they are.
1) Change array indexing logic to pointer logic:
can change to:
This eliminates lots of redundant addition. All of those stuff[i] = val type of statements tend to generate:
mov
No, you're adopting a black or white approach. You are, in essence, saying that you don't need to comment at all. The original poster was saying that comments needed to be everywhere, on everything. I believe in a middle ground approach.
I comment things that are non intuitive. I comment things that I *think* may be non intuitive. I comment things that I think someone else might have some difficulty understanding, because I happened to be deep into a code burn and consequently wrote something pretty tight, pretty sweet, but also pretty obfuscated. Finally, I comment things that I think *I* may not understand when I go back and look at the code again 3 months from now.
I don't comment every single line... I don't comment simple data structures, loops "/* this is a for loop using the integer variable I */" etc which would be stupid. I do however disassemble the complex portions of my code, describe how I'm dispatching events and best of all *why* I decided to do things a certain way instead of a different way.
I have, however, been handed 30k lines of code with zero documentation and not a single comment anywhere in it, with absolutely no clue at all how it worked and no access to the original programmer and been told "We need such and such fixed|updated|added by friday" and had to spend the entire week basically tracing every single line of code to figure out that the original programmer must have been smoking crack with NO indication of why he wrote things how he did and NO help when he decided to be exceedingly "clever"
in his code. That time was wasted.
Would it have killed him to simply put a comment block explaining his event dispatch model? Or to tell me what his functions and methods did and best of all why they did it?
There *is* a middle ground, believe it or not.
-- Gary F.
This issue is in like this,
You need to understand the language, both syntax AND semantics you are using
this ranges from the simple to mind-bending e.g. C++ (I am convinced that not even Bjarne Stroustrup understands this evil language);
at that point you have two bi-furcations (a) interpreted languages eg Java, Perl, PHP and Python -v- (b) cpmpiled languages, and (c) finally DIY (do it your self) Assembler
So: what does it amount to in practice? A) Rock Bottom, understand the architecture, including virtual memory, architecture and instruction set issues, read and understand the chip data sheet. Hard! See bottom line, architecture dependand code in Linux, bsd ...
B) use 'gcc -S' and write the code in C, hand improve the assembler output, this is what I normally do, but you need to keep an open mind otherwise you miss things, I once took a compute intensive algorithm for the M68020 and made it run 10'000 times faster using this approach
C)consider hardware optimisation; strictly price/performance.
I've been using it for a while...
In the course of every project, it will become necessary to shoot the scientists and begin production.
In terms of optimizing, generally compilers do a pretty good job, however there are several areas that no compiler I know of can help.
1. Choose the right algorithm. For example, in an embedded project I worked on an engineer used a linked list to store thousands of fields that must be added and deleted. While adding is fast, it didn't scale for deleting. Changed it to a hash table and it sped it up significantly.
2. Know your data and how it is used. Knowing how to organize your data and access it can make a huge difference. As a previous poster pointed out, sequential memory accesses are much faster than random accesses. I had to do some 90 degree image rotation code. The simple solution just used a couple for loops when copying the pixels from one buffer to another. In another, I took into account the processor cache and how memory is accessed and broke it down into tiles. The first algorithm, while simple and elegant ran at 30 frames per second. The other ran at over 200 frames per second. Looking at the code the first algorithm should be faster since the code is simpler. Both algorithms operate in O(N) time, where N=width * height.
Further optimization attempts to hint to the CPU cache about memory made no difference (Athlon XP 1700+). The only possible way I see to speed it up further would be to write it in hand-coded assembler.
3. Reduce the number of system calls if possible. Some operating systems can be very painful when calling the kernel. Group reads and writes together so fewer calls are made.
4. Profile your code to find bottlenecks.
5. Try and keep a tradeoff between memory usage and performance. A smaller tightly packed data set will execute faster with CPU caches and will reduce page faults when loading and starting up.
6. Try debugging your code at the assembler level, stepping through it. It will help you better understand your compiler.
7. Don't bother trying to optimize things like getting every ounce of performance when the next function you call will be very slow. I.e. in one section of MS DOS's source code which was hand-coded assembly language it was calculating the cluster or sector of the disk to access. First the code checked if it was running on a 16-bit or 32-bit CPU. Next it took the 16-bit or 32-bit path for multiplication, then it read from the disk. Why the hell write all this code to check the CPU if it's 16 or 32 bit for the multiply when the frigging disk is going to be slow. They should have just stuck with the 16-bit multiply rather than be clever.
In general applications with GCC, I rarely see much difference between -O2 or -O3. For that matter, I often don't see a noticable difference between -O0 and -O3 for a lot of code.
I only see improvements in some very CPU intensive multimedia code. I also saw a significant improvement in some multimedia code when I told the compiler to generate code for an Ultrasparc rather than the default, but that's because the pre-ultrasparc code didn't use a multiply instruction.
-Aaron
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Do not perform minor optimizations without first: a) Determining there is a performance problem b) Profiling your code to determine what areas should be optimized.
This does not mean that you should choose naive algortithms for the problem at hand. Choosing the proper algorithm for the problem at hand is always important.
Hand-optimized code should be reserved for those times when you have profiled your code with reasonable inputs and have shown that the lack of clarity is compensated for by the increased performance.
The example you gave is a perfect example of a hand optimization that is completely worthless with today's compilers.
"I ask the Slashdot crowd, what they believe the compiler can be trusted to optimize and what must be hand optimized? Give examples of code optimizations that you think the compiler can/can't be trusted to do."
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Somehow 99% of the readers took this to mean "What is the difference between NULL and the zero bit pattern and do you think it is a good idea to write clear code and do the profile/algorithm change cycle until there is nothing left to optimize or should I write low level optimized code from the start?"
sigh.. I've only found two comments with code so far after going through hundreds of posts. This is possibly the worst signal to noise ratio I've witnessed on
As far as I'm concerned compilers are better than 99% of the programmers out there. Just write clear code and let the compiler do it's trick. However there are a couple cases where things aren't automatically optimized that I can think of.
;)
.587h, .0114h)); I'm not sure if that bug still exists in the current compiler release or not.
/. posters just aren't aware of the short commings of compilers (see first sentence of this post) and would rather post obvious advice than not post at all. :)
It's not really a coding trick like an XOR swap, but most compilers don't yet seem to fully unroll parallel loops into good SIMD instructions or multiple threads.
The only time I've needed to bother to look at assembly output in recent years (other than debugging a release mode program) is when writing HLSL shaders. HLSL is the high level shading languge (C like) for shaders that is part of Direct3D 9. HLSL can be compiled to SM1, SM2, or SM3 assembly.
With pixel shader 2.0 you've only got 64 instruction slots, and some important instructions like POW (power), NRM (normalize), and LRP (interpolate) take multiple slots. 64 slots is not enough for a modern shader. I curse ATI for setting it bar so low.
There are two flaws I've found with the Dec 04 HLSL compiler in the DirectX. Sometimes it will not automatically detect a dot product opportunity. I had some colour code to convert to black and white in a shader and wrote it as y = colour.r*0.299 + colour.g*0.587 + colour.b*0.114; as I thought that was the most clear way to write it. Under certain circumstances the compiler didn't want to convert to a single dot instruction so I had to write as y = dot( colour.rgb, half3(.299h,
Another is often a value in the range of -1 to +1 is passed in as a colour, which means it must be packed into 0-1 range. To get it back you've got to double it and add 1.
a = p*2+1; gets converted into a single MAD instruction which takes one slot.
a = (p-0.5)*2; gets converted into an ADD and then a MUL.
Also conventional wisdom says you've got to write assembly to get maximum performance out of pixel shader 1.1 as it is basically just eight instruction slots. I don't have any snippets to verify this though.
I think this thread demonstrates that either compilers are mature enough you don't need any code tricks to help them do their job or
For the rare performance critical parts it is however worth the effort to try various constructions to get the best performance out of the code. The most problematic issue is to identify the hotspots in the code and figure out which variables that should be declared as 'register' and those that shouldn't. Ordering of statements are also important in order to match the various performance improvments the CPU can offer. One very good document on this is actually found at AMD.
One code construct that I am using that I found is very useful is to place the matching '{' and '}' in the same column in the code. This eases the effort trying to find where a block begins.
Example:
In my opinion this produces code that has an improved readability compared to the constructs placing the '{' on the same line as the if-statement where it is much easier to miss.If builders built buildings the way programmers wrote programs, then the first woodpecker would destroy civilization.