For a brief report I have to do, our class ran code on a cluster using both gcc -O0 and icc -O0. We found that gcc was about 2.5 times faster than icc without any optimizations? Why is this? Does gcc -O0 actually do some minor optimization or does it simply happen to work better for this system?
The code was an implementation of the naive string searching algorithm found here, written in c.
Thank you
Performance at -O0 is not interesting or indicative of anything. It explicitly says "I don't care about performance", and the compiler takes you up on that; it just does whatever happens to be simplest. By random luck, what is simplest for GCC is faster than what is simplest for ICC for one highly specific microbenchmark on your specific hardware configuration. If you ran 100 other microbenchmarks, you would probably find some where ICC is faster, too. Even if you didn't, that still wouldn't mean much. If you're going to compare performance across compilers, turn on optimizations, because that's what you do if you care about performance.
If you want to understand why one is faster, profile the execution. Where is the execution time being spent? Where are there stalls? Why do those stalls occur?
A few things to take into account:
The instruction set each compiler uses by default. For example if your GCC build produces i686 code by default, while ICC restricts itself to i586 opcodes, you would probably see a significant performance difference.
The actual CPUs in your cluster. If you are using AMD processors, instead of Intel CPUs, then ICC is at a disadvantage because it is, of course, targeted specifically to Intel processors.
You mentioned using a cluster. Does this speed difference exist on a single processor as well? If you used any parallelisation facilities provided by your compiler, there could be significant differences there.
Simplistically, when optimisations are disabled, the compiler uses pre-made "templates" for each code construct. Since these templates are intended to be optimised afterwards, they are constructed in a way that enables the optimisation passes to produce better code. The fact that they may be slower or faster with -O0 does not really mean anything - for example, more explicit initial code could be easier to optimise but far slower to execute.
That said, the only way to find out what is going on is to profile the execution of your code and, if necessary, have a look at the assembly of those parts of the code where the major differences lie.
Related
My program heavily depends on the special functions from GSL and thus I would like to make it run faster, so I wish to compile GSL with higher optimization levels.
When I compile gsl, the default CFLAGS is "-g -O2" if I do nothing when I configure with "./configure". I am wondering why gsl is defaulting to an optimization level of O2 only since O3 is compliant to standards. I tried to compile and test with "./configure CFLAGS='-g -O3'", things worked. But I'm still not sure if everything would work.
Can anyone tell me why GSL is defaulting to O2 instead of O3? Would it be dangerous if I default to O3? Thanks!
The optimization level 3 is something that should only be used in case it is absolutely sure that it helps the library.
Since that level activates optimizations that may increase the size of the code a lot. This means in some cases it creates binaries that are even slower compared to a binary optimized with -O2. How ever that happens rarely. More likely are effects like a massively increased time to compile it, along with a increased binary size and a barely measurable performance change.
That -O3 actually breaks something was pretty common some time back, but in the last couple of years I did not have a single case where -O3 actually optimized something that caused the binary to break.
In the end the optimization level is something you can just test. Since -O2 is the default, it is a pretty safe bet that this is the best settings for the compile operation in this case. If you feel like it you could try to compile it with a different setting to see if it makes any performance difference.
Interesting options are -O3 and even -Os. I had cases in the past were both options gave improved performance over -O2.
So the real answer is: Try it and see what happens.
I need to write optimized NEON code for a project and I'm perfectly happy to write assembly language, but for portability/maintainability I'm using NEON instrinsics. This code needs to be as fast as possible, so I'm using my experience in ARM optimization to properly interleave instructions and avoid pipe stalls. No matter what I do, GCC works against me and creates slower code full of stalls.
Does anyone know how to have GCC get out of the way and just translate my intrinsics into code?
Here's an example: I have a simple loop which negates and copies floating point values. It works with 4 sets of 4 at a time to allow some time for the memory to load and instructions to execute. There are plenty of registers left over, so it's got no reason to mangle things so badly.
float32x4_t f32_0, f32_1, f32_2, f32_3;
int x;
for (x=0; x<n-15; x+=16)
{
f32_0 = vld1q_f32(&s[x]);
f32_1 = vld1q_f32(&s[x+4]);
f32_2 = vld1q_f32(&s[x+8]);
f32_3 = vld1q_f32(&s[x+12]);
__builtin_prefetch(&s[x+64]);
f32_0 = vnegq_f32(f32_0);
f32_1 = vnegq_f32(f32_1);
f32_2 = vnegq_f32(f32_2);
f32_3 = vnegq_f32(f32_3);
vst1q_f32(&d[x], f32_0);
vst1q_f32(&d[x+4], f32_1);
vst1q_f32(&d[x+8], f32_2);
vst1q_f32(&d[x+12], f32_3);
}
This is the code it generates:
vld1.32 {d18-d19}, [r5]
vneg.f32 q9,q9 <-- GCC intentionally causes stalls
add r7,r7,#16
vld1.32 {d22-d23}, [r8]
add r5,r1,r4
vneg.f32 q11,q11 <-- all of my interleaving is undone (why?!!?)
add r8,r3,#256
vld1.32 {d20-d21}, [r10]
add r4,r1,r3
vneg.f32 q10,q10
add lr,r1,lr
vld1.32 {d16-d17}, [r9]
add ip,r1,ip
vneg.f32 q8,q8
More info:
GCC 4.9.2 for Raspbian
compiler flags: -c -fPIE -march=armv7-a -Wall -O3 -mfloat-abi=hard -mfpu=neon
When I write the loop in ASM code patterned exactly as my intrinsics (without even making use of extra src/dest registers to gain some free ARM cycles), it's still faster than GCC's code.
Update: I appreciate James' answer, but in the scheme of things, it doesn't really help with the problem. The simplest of my functions perform a little better with the cortex-a7 option, but the majority saw no change. The sad truth is that GCC's optimization of intrinsics is not great. When I worked with the Microsoft ARM compiler a few years ago, it consistently created well crafted output for NEON intrinsics while GCC consistently stumbled. With GCC 4.9.x, nothing has changed. I certainly appreciate the FOSS nature of GCC and the greater GNU effort, but there is no denying that it doesn't do as good a job as Intel, Microsoft or even ARM's compilers.
Broadly, the class of optimisation you are seeing here is known as "instruction scheduling". GCC uses instruction scheduling to try to build a better schedule for the instructions in each basic block of your program. Here, a "schedule" refers to any correct ordering of the instructions in a block, and a "better" schedule might be one which avoids stalls and other pipeline hazards, or one which reduces the live range of variables (resulting in better register allocation), or some other ordering goal on the instructions.
To avoid stalls due to hazards, GCC uses a model of the pipeline of the processor you are targeting (see here for details of the specification language used for these, and here for an example pipeline model). This model gives some indication to the GCC scheduling algorithms of the functional units of a processor, and the execution characteristics of instructions on those functional units. GCC can then schedule instructions to minimise structural hazards due to multiple instructions requiring the same processor resources.
Without a -mcpu or -mtune option (to the compiler), or a --with-cpu, or --with-tune option (to the configuration of the compiler), GCC for ARM or AArch64 will try to use a representative model for the architecture revision you are targeting. In this case, -march=armv7-a, causes the compiler to try to schedule instructions as if -mtune=cortex-a8 were passed on the command line.
So what you are seeing in your output is GCC's attempt at transforming your input in to a schedule it expects to execute well when running on a Cortex-A8, and to run reasonably well on processors which implement the ARMv7-A architecture.
To improve on this you can try:
Explicitly setting the processor you are targeting (-mcpu=cortex-a7)
Disabling instruction scheduling entirely (`-fno-schedule-insns -fno-schedule-insns2)
Note that disabling instruction scheduling entirely may well cause you problems elsewhere, as GCC will no longer be trying to reduce pipeline hazards across your code.
Edit With regards to your edit, performance bugs in GCC can be reported in the GCC Bugzilla (see https://gcc.gnu.org/bugs/ ) just as correctness bugs can be. Naturally with all optimisations there is some degree of heuristic involved and a compiler may not be able to beat a seasoned assembly programmer, but if the compiler is doing something especially egregious it can be worth highlighting.
If I run gcc with -O0, and hand-optimize my code using techniques such as the ones mentioned here, will it generally be the case that my optimized code will run faster than my unoptimized code when I run gcc with -O3?
That is, if I hand-optimize code under a particular compiler optimization level, is it generally true that these optimizations will still be productive (rather than counterproductive) under a different (higher or lower) compiler optimization level?
It might not be same in different compiler. Even the compiler can do away with your hand optimization, i mean ignore them. It heavily depends the implementation and behavior of the compiler itself. Most of the optimizations are like a request to compiler, which can be dropped at any time, (mostly without any notification)
If I want to achieve better performance from, let's say for example, MySQLdb, I can compile it myself and I will get better performance because it's not compiled on i386, i486 or what ever, just on my CPU. Further I can choose the compile options and so on...
Now, I was wondering if this is true also for non-regular Software, such as compiler.
Here come the 1st part:
Will compiling a compiler like GCC result in better performance?
and the 2nd part:
Will the code compiled by my own compiled compiler perform better?
(Yes, I know, I can compile my compiler and benchmark it... but maybe ... someone already knows the answer, and will share it with us =)
In answer to your first question, almost certainly yes. Binary versions of gcc will be the "lowest common denominator" and, if you compile them with special flags more appropriate to your system, it will most likely be faster.
As to your second question, no.
The output of the compiler will be the same regardless of how you've optimised it (unless it's buggy, of course).
In other words, even if you totally stuffed up your compiler flags when compiling gcc, to the point where your particular compiled version of gcc takes a week and a half to compile "Hello World", the actual "Hello World" executable should be identical to the one produced by the "lowest common denominator" gcc (if you use the same flags).
(1) It is possible. If you introduce a new optimization to your compiler, and re-compile it with this optimization included - it is possible that the re-compiled code will perform better.
(2) No!!!! A compiler cannot change the logic of the code! In your case, the logic of the code is the native code produced at the end. So, if compiler A_1 is compiled using compiler A_2 or B, has no affect on the native code produced by A_1 [in here A_1, A_2 are the same compilers, the index is just for clarity].
a.Well, you can compile the compiler to your system, and maybe it will run faster. like any program. (I think that usualy it's not worth it, but do whatever you want).
b. No. Even if you compile the compiler in your computer, it's behavior should not change, and so the code that it generates also doesn't change.
Will compiling a compiler like GCC result in better performance?
A program compiled specifically to the target platform it is used on will usually perform better than a program compiled for a generic platform. Why is this? Knowledge about the harware can help the compiler align data to be cache friendly and choose an instruction ordering that plays well with a CPUs pipelining.
The most benefit is usally achieved by leveraging specific instruction sets such as SSE (in its various versions).
On the other hand, you should ask yourself if a programm like GCC is really CPU bound (much more likely it will be IO bound) and tuning its CPU performance provides any measurable benefit.
Will the code compiled by my own compiled compiler perform better
Hopefully not! Allowing a compiler to optimize a program should never change its behavior. No matter how you compiled your GCC, it should compile code to the same binaries as a generic binary distribution of GCC would.
If code compiled to the specific platform is faster than code compil for a generic platform, why dont we all ship code instead of binaries? Guess what, some linux distros actually follow this phillosophy, such as Gentoo. And while you're at it, make sure to built statically linked binaries, disk space is so cheap nowadays and it gives you at least another 0.001% of performance.
Alright, that was a bit sarcastic. The reason people distribute generic binaries is pretty obvious: It's geneirc, the lowest common denominator and it will work everywhere. Thats a big bonus in terms of flexibility and user friendlyness. I remember once compiling Gnome for my Gentoo box, it took a day or two! (But it must have been so much faster ;-) )
On the other hand, there are occassions where you want to get the best performance possible and it makes sense to build and optimize for specific architctures.
GCC uses a three step bootstraping when building from source. Basically it compiles the source three times to ensure build tools and compiler is build successfully. This bootstraping is used for validation purpose. However it is possible to use the stage 1 as a benchmark for optimizing later stages. You should build GCC with make profiledbootstrap to use this profile based optimization.
This profile based build process increases the performance of "GCC", but not the software compiled with it, as other answers point out.
Is it possible to bypass loop vectorization in FORTRAN? I'm writing to F77 standards for a particular project, but the GNU gfortran compiles up through modern FORTRANs, such as F95. Does anyone know if certain FORTRAN standards avoided loop vectorization or if there are any flags/options in gfortran to turn this off?
UPDATE: So, I think the final solution to my specific problem has to "DO" with the FORTRAN DO loops not allowing the updating of the iteration variable. Mention of this can be found in #High Performance Mark's reply on this related thread... Loop vectorization and how to avoid it
[Into the FORT, RAN the noobs for shelter.]
The Fortran standards are generally silent on how the language is to be implemented, leaving that to the compiler writers who are in a better position to determine the best, or good (and bad) options for implementation of the language's various features on whatever chip architecture(s) they are writing for.
What do you mean when you write that you want to bypass loop vectorisation ? And in the next sentence suggest that this would be unavailable to FORTRAN77 programs ? It is perfectly normal for a compiler for a modern CPU to generate vector instructions if the CPU is capable of obeying them. This is true whatever version of the language the program is written in.
If you really don't want to generate vector instructions then you'll have to examine the gfortran documentation carefully -- it's not a compiler I use so I can't point you to specific options or flags. You might want to look at its capabilities for architecture-specific code generation, paying particular attention to SSE level.
You might be able to coerce the compiler into not vectorising loops if all your loops are explicit (so no whole-array operations) and if you make your code hard to vectorise in other ways (dependencies between loop iterations for example). But a good modern compiler, without interference, is going to try its damndest to vectorise loops for your own good.
It seems rather perverse to me to try to force the compiler to go against its nature, perhaps you could explain why you want to do that in more detail.
As High Performance Mark wrote, the compiler is free to select machine instructions to implement your source code as long as the results follow the rules of the language. You should not be able to observe any difference in the output values as a result of loop vectorization ... you code should run faster. So why do you care?
Sometimes differences can be observed across optimization levels, e.g., on some architectures registers have extra precision.
The place to look for these sorts of compiler optimizations is the gcc manual. They are located there since they are common across the gcc compiler suite.
With most modern compilers, the command-line option -O0 should turn off all optimisations, including loop vectorisation.
I have sometimes found that this causes bugs to apparently disappear. However usually this means that there is something wrong with my code so if this sort of thing is happening to you then you have almost certainly written a buggy program.
It is theoretically possible but much less likely that there is a bug in the compiler, you can easily check this by compiling your code in another fortran compiler. (e.g. gfortran or g95).
gfortran doesn't auto-vectorize unless you have set -O3 or -ftree-vectorize. So it's easy to avoid vectorization. You will probably need to read (skim) the gcc manual as well as the gfortran one.
Auto-vectorization has been a well-known feature of Fortran compilers for over 35 years, and even the Fortran 77 definition of DO loops was set with this in mind (and also in view of some known non-portable abuses of F66 standard). You could not count on turning off vectorization as a way of making incorrect code work, although it might expose symptoms of incorrect code.