I will break down this question in to sub questions. I am confused if I should ask them separately or in one question. So I will just stick to one SO question.
What are generally the steps to analyze and improve performance of C applications?
Do these steps change if I am developing for an embedded system?
What tools are out there which can help me?
Recently I have been given a task to improve the performance of our product on ARM11 platform. I am relatively new to this field of embedded systems and need gurus here on SO to help me out.
simply changing compilers can improve your C performance for the same source code by many times over. GCC has not necessarily gotten better for performance over the years, for some programs gcc 3.x produces much tighter code than 4.x. Back when I had access to the tools, ARMs compiler produced significantly better code than gcc. As much as 3 or 4 times faster. LLVM has caught up to GCC 4.x and I suspect will pass gcc by in terms of performance and overall use for cross compiling embedded code. Try different versions of gcc, 3.x and 4.x if you are using gcc. Metaware's compiler and arms adt ran circles around gcc3.x, gcc3.x will give gcc4.x a run for its money with arm code, for thumb code gcc4.x is better and for thumb2 (which doesnt apply to you) gcc4.x also better. Remember I have not said a word about changing a single line of code (yet).
LLVM is capable of full program optimization in addition to infinitely more tuning knobs than gcc. Despite that the code generated (ver 27) is only just catching up to the current gcc 4.x in terms of performance for the few programs I tried. And I didnt try the n factoral number of optimization combinations (optimize on the compile step, different options for each file, or combine two files or three files or all files and optimize those bundles, my theory is do no optimization on the C to bc steps, link all the bc together then do a single optimization pass on the whole program, the allow the default optimization when llc takes it to the target).
By the same token simply knowing your compiler and the optimizations can greatly improve the performance of the code without having to change any of it. You have an ARM11 arr you compiling for arm11 or generic arm? You can gain a few to a dozen percent by telling the compiler specifically which architecture/family (armv6 for example) over the generic armv4 (ARM7) that is often chosen as the default. Knowing to use -O2 or -O3 if you are brave.
It is often not the case but switching to thumb mode can improve performance for specific platforms. Doesnt apply to you but the gameboy advance is a perfect example, loaded with non-zero wait state 16 bit busses. Thumb has a handful of a percent overhead because it takes more instructions to do the same thing, but by increasing the fetch times, and taking advantage of some of the sequential read features of the gba thumb code can run significantly faster than arm code for the same source code.
having an arm11 you probably have an L1 and maybe L2 cache, are they on? Are they configured? Do you have an mmu and is your heavy use memory cached? or are you running zero wait state memory and dont need a cache and should turn it off? In addition to not realizing that you can take the same source code and make it run many times faster by changing compilers or options, folks often dont realize that when you use a cache simply adding a single up to a few nops in your startup code (as a trick to adjust where code lands in memory by one, two, a few words) you can change your codes execution speed by as much as 10 to 20 percent. Where those cache line reads hit in heavily used functions/loops makes a big difference. Even saving one cache line read by adjusting where the code lands is noticeable (cutting it from 3 to 2 or 2 to 1 for example).
Knowing your architecture, both the processor and your memory environment is where the tuning if any would start. Most C libraries if you are high level enough to use one (I often dont use a C library as I run without an operating system and with very limited resources) both in their C code and sometimes add some assembler to make bottleneck routines like memcpy, much faster. If your programs are operating on aligned 32 or even better 64 bit addresses, and you adjust even if it means using a handful of bytes more memory for every structure/array/memcpy to be an integral multiple of 32 bits or 64 bits you will see noticeable improvements (if your code uses structs or copies data in other ways). In addition to getting your structures (if you use them, I certainly dont with embedded code) size aligned, even if you waste memory, getting elements aligned, consider using 32 bit integers for every element instead of bytes or halfwords. Depending on your memory system this can help (it can hurt too btw). As with the GBA example above looking at specific functions that either by profiling or intuition you know are not being implemented in a manner that takes advantage of your processor or platform or libraries you may want to turn to assembler either from scratch or compiling from C initially then disassembling and hand tuning. Memcpy is a good example you may know your systems memory performance and may chose to create your own memcpy specifically for aligned data, copying 64 or 128 or more bits per instruction.
Likewise mixing global and local variables can make a noticeable performance difference. Traditionally folks are told never to use globals, but in embedded this isnt necessarily true, depends on how deeply embedded and how much tuning and speed and other factors you are interested in. This is a touchy subject and I may get flamed for it, so I will leave it at that.
The compiler has to burn and evict registers in order to make function calls, plus if you use local variables a stack frame may be required, so function calls are expensive, but at the same time, depending on the code within a function that has now grown in size by avoiding functions, you may create the problem you were trying to avoid, evicting registers to re-use them. Even a single line of C code can make the difference between all the variables in a function fits in registers to having to start evicting a bunch of registers. For functions or segments of code where you know you need some performance gain compile and disassemble (and look at register usage, how often it fetches memory or writes to memory). You can and will find places where you need to take a well used loop and make it its own function even though the function call has a penalty because by doing that the compiler can better optimize the loop and not evict/reuse registers and you get an overall net gain. Even a single extra instruction in a loop that goes around hundreds of times is a measurable performance hit.
Hopefully you already know to absolutely not compile for debug, turn all of the compile for debug options off. You may already know that code compile for debug that runs without bugs doesnt mean it is debugged, compiling for debug and using debuggers hide bugs leaving them as time bombs in your code for your final compile for release. Learn to always compile for release and test with the release version both for performance and finding bugs in your code.
Most instruction sets do not have a divide function. Avoid using divides or modulo in your code as much as humanly possible they are performance killers. Naturally this is not the case for powers of two, to save the compiler and to mentally avoid divides and modulos try to use shifts and ands. Multplies are easier and more often found in instruction sets, but are still costly. This is a good case to write assembler to do your multiplies instead of letting the C copiler do it. The arm multiply is a 32bit * 32bit = 32 bit so to do accurate math without overflowing there has to be extra C code wrapped around the multiply, if you already know you wont overflow, burn the registers for a function call and do the multiply in assembler (for the arm).
Likewise most instruction sets do not have a floating point unit, with yours you might, even so avoid float if at all possible. If you have to use float that is a whole other pandora's box of performance issues. Most folks dont see the performance problems with code as simple as this:
float a,b;
...
a = b * 7.0;
The rest of the problem is not understanding floating point accuracy and how good or bad the C libraries are just trying to get your constants into floating point form. Again float is a whole other long discussion on performance problems.
I am a product of Michael Abrash (I actually have a print copy of zen of assembly language) and the bottom line is time your code. Come up with an accurate way to time the code, you may think you know where the bottlenecks are and you may think you know your architecture but trying different things even if you think they are wrong, and timing them you may find and eventually have to figure out the error in your thinking. Adding nops to start.S as a final tuning step is a good example of this, all the other work you have done for performance can be instantly erased by not having a good alignment with the cache, this also means re-arranging functions within your source code so that they land in different places in the binary image. I have seen 10 to 20 percent swings of speed increase and decrease as a result of cache line alignments.
Code Review:
What are good code review techniques ?
Static and dynamic analysis of the code.
Tools for static analysis: Sparrow, Prevent, Klockworks
Tools for dynamic analysis : Valgrind, purify
Gprof allows you to learn where your program spent its time and which functions called which other functions while it was executing.
Steps are same
Apart from what is listed is point 1, there are tools like memcheck etc.
There is a big list here based on platform
Phew!! Quite a big question!
What are generally the steps to
analyze and improve performance of C
applications?
As well as other static code analysers mentioned here there is a fairly cheap version called PC-Lint which has been around for ages. Sometimes throws up lots of errors and warnings for one error but by the end of it you'll be happy and know waaaaay more about C/C++ because of it.
With all code analysers some of the issues may be more structural to the code so best to start analysing it from day 1 of coding; running analysis on old software may swamp you with issues which may take a while to untangle, best to keep it clean from the beginning.
But code analysers will not catch all logical errors, i.e. it doesn't do what you want it to do! These are best done by code reviews first, then testing. Performance is often improved by by trying to keep the algorithms as simple as possible, keeping instructions in loops tight, possibly unrolling loops (your compiler optimisations may do this), use of fast caches when accessing data which is slow to get.
Code reviews can raise a lot of issues from lots of other peoples eyes looking at it. Don't get too many people, try to get 3 other people if possible, sometimes junior developers ask the most insightful questions like, "why are we doing this?".
Testing can be roughly split into two sections, automated and manual. Automated testing requires effort producing test handlers for functions/units but once run can be run again and again very quickly. Manual testing requires planning, self-discipline to perform them all to the required, imagination to think up of scenarios that may impair performance and you have to be observant (you may have passed the test but the 'scope trace has a bit of an anomaly before/after the test).
"Do these steps change if I am
developing for an embedded system?"
Performance ananlysis can be different on embedded systems to applications systems; with the very broad brush that "embedded" now covers it depends how hardware-centric you are. It can be done using profilers, if you want a more cheap and chearful method then use test output pins to measure sections of code, or measure them with breakpoints on simulators that come with the development environment.
Make sure that not just a typical length of task is measured but also a maximum, as that is where one task may start impeding on other tasks and your scheduled tasks are not completed in time.
What tools are out there which can
help me?
Simulators on the IDEs, static analysis tools, dynamic analysis tools, but most of all you and other humans getting the requirements right, decent reviewing (of code and testing) and thorough testing (automated and manual).
Good luck!
My experiences.
Function calls are slow, eliminate with macros or inlined methods. Look at the disassembler listing to see.
If using GCC, mark optimized sections with #pragma GCC optimize("O3") or compile them separately.
Play with different combinations of applying the inline attribute (basically find a balance between size and speed).
It is a difficult question to be answered shortly since various techniques have been proposed such as flowchart and state diagram,so you can take a look at some titles:
ARM System-on-Chip Architecture, 2nd Edition -- Steve Furber
ARM System Developer's Guide - Designing and Optimizing System Software -- Andrew N. Sloss, Dominic Symes, Chris Wright & John Rayfield
The Definitive Guide to the ARM Cortex-M3 --Joseph Yiu
C Programming for Embedded Systems --Kirk Zurell
Embedded C -- Michael J. Pont
Programming Embedded Systems in C and C++ --Michael Barr
An Embedded Software Primer --David E, Simon
Embedded Microprocessor Systems 3rd Edition --Stuart Ball
Global Specification and Validation of Embedded Systems - Integrating Heterogeneous Components --G. Nicolescu & A.A Jerraya
Embedded Systems: Modeling, Technology and Applications --Gunter Hommel & Sheng Huanye
Embedded Systems and Computer Architecture --Graham Wilson
Designing Embedded Hardware --John Catsoulis
You have to use a profiler. It will help you identify your application's bottleneck(s). Then focus on improving the functions you spend the most time in and the ones you call the most. Repeat this procedure until you're satisfied with your application performance.
No they don't.
Depending on the platform you're developing onto :
Windows : AMD Code Analyst, VTune, Sleepy
Linux : valgrind / callgrind / cachegrind
Mac : the Xcode profiler is quite good.
Try to find a profiler for the architecture you actually work on.
Related
I need a better way of profiling numerical code. Assume that I'm using GCC in Cygwin on 64 bit x86 and that I'm not going to purchase a commercial tool.
The situation is this. I have a single function running in one thread. There are no code dependencies or I/O beyond memory accesses, with the possible exception of some math libraries linked in. But for the most part, it's all table look-ups, index calculations, and numerical processing. I've cache aligned all arrays on the heap and stack. Due to the complexity of the algorithm(s), loop unrolling, and long macros, the assembly listing can become quite lengthy -- thousands of instructions.
I have been resorting to using either, the tic/toc timer in Matlab, the time utility in the bash shell, or using the time stamp counter (rdtsc) directly around the function. The problem is this: the variance (which might be as much as 20% of the runtime) of the timing is larger than the size of the improvements I'm making, so I have no way of knowing if the code is better or worse after a change. You might think then it's time to give up. But I would disagree. If you are persistent, many incremental improvements can lead to a two or three times performance increase.
One problem I have had multiple times that is particularly maddening is that I make a change and the performance seems to improve consistently by say 20%. The next day, the gain is lost. Now it's possible I made what I thought was an innocuous change to the code and then completely forgot about it. But I'm wondering if it's possible something else is going on. Like maybe GCC doesn't yield a 100% deterministic output as I believe it does. Or maybe it's something simpler, like the OS moved my process to a busier core.
I have considered the following, but I don't know if any of these ideas are feasible or make any sense. If yes, I would like explicit instructions on how to implement a solution. The goal is to minimize the variance of the runtime so I can meaningfully compare different versions of optimized code.
Dedicate a core of my processor to run only my routine.
Direct control over the cache(s) (load it up or clear it out).
Ensuring my dll or executable always loads to the same place in memory. My thinking here is that maybe the set-associativity of the cache interacts with the code/data location in RAM to alter performance on each run.
Some kind of cycle accurate emulator tool (not commercial).
Is it possible to have a degree of control over context switches? Or does it even matter? My thinking is the timing of the context switches is causing variability, maybe by causing the pipeline to be flushed at an inopportune time.
In the past I have had success on RISC architectures by counting instructions in the assembly listing. This only works, of course, if the number of instructions is small. Some compilers (like TI's Code Composer for the C67x) will give you a detailed analysis of how it's keeping the ALU busy.
I haven't found the assembly listings produced by GCC/GAS to be particularly informative. With full optimization on, code is moved all over the place. There can be multiple location directives for a single block of code dispersed about the assembly listing. Further, even if I could understand how the assembly maps back into my original code, I'm not sure there's much correlation between instruction count and performance on a modern x86 machine anyway.
I made a weak attempt at using gcov for line-by-line profiling, but due to an incompatibility between the version of GCC I built and the MinGW compiler, it wouldn't work.
One last thing you can do is average over many, many trial runs, but that takes forever.
EDIT (RE: Call Stack Sampling)
The first question I have is, practically, how do I do this? In one of your power point slides, you showed using Visual Studio to pause the program. What I have is a DLL compiled by GCC with full optimizations in Cygwin. This is then called by a mex DLL compiled by Matlab using the VS2013 compiler.
The reason I use Matlab is because I can easily experiment with different parameters and visualize the results without having to write or compile any low level code. Further, I can compare my optimized DLL to the high level Matlab code to ensure my optimizations have not broken anything.
The reason I use GCC is that I have a lot more experience with it than with Microsoft's compiler. I'm familiar with many flags and extensions. Further, Microsoft has been reluctant, at least in the past, to maintain and update the native C compiler (C99). Finally, I've seen GCC kick the pants off commercial compilers, and I've looked at the assembly listing to see how it's actually done. So I have some intuition of how the compiler actually thinks.
Now, with regards to making guesses about what to fix. This isn't really the issue; it's more like making guesses about how to fix it. In this example, as is often the case in numerical algorithms, there is really no I/O (excluding memory). There are no function calls. There's virtually no abstraction at all. It's like I'm sitting on top of a piece of saran wrap. I can see the computer architecture below, and there's really nothing in-between. If I re-rolled up all the loops, I could probably fit the code on about one page or so, and I could almost count the resultant assembly instructions. Then I could do a rough comparison to the theoretical number of operations a single core is capable of doing to see how close to optimal I am. The trouble then is I lose the auto-vectorization and instruction level parallelization I got from unrolling. Unrolled, the assembly listing is too long to analyze in this way.
The point is that there really isn't much to this code. However, due to the incredible complexity of the compiler and modern computer architecture, there is quite a bit of optimization to be had even at this level. But I don't know how small changes are going to affect the output of the compiled code. Let me give a couple of examples.
This first one is somewhat vague, but I'm sure I've seen it happen a few times. You make a small change and get a 10% improvement. You make another small change and get another 10% improvement. You undo the first change and get another 10% improvement. Huh? Compiler optimizations are neither linear, nor monotonic. It's possible, the second change required an additional register, which broke the first change by forcing the compiler to alter its register allocation algorithm. Maybe, the second optimization somehow occluded the compiler's ability to do optimizations which was fixed by undoing the first optimization. Who knows. Unless the compiler is introspective enough to dump its full analysis at every level of abstraction, you'll never really know how you ended up with the final assembly.
Here is a more specific example which happened to me recently. I was hand coding AVX intrinsics to speed up a filter operation. I thought I could unroll the outer loop to increase instruction level parallelism. So I did, and the result was that the code was twice as slow. What happened was there were not enough 256 bit registers to go around. So the compiler was temporarily saving results on the stack, which killed performance.
As I was alluding to in this post, which you commented on, it's best to tell the compiler what you want, but unfortunately, you often have no choice and are forced to hand tweak optimizations, usually via guess and check.
So I guess my question would be, in these scenarios (the code is effectively small until unrolled, each incremental performance change is small, and you're working at a very low level of abstraction), would it be better to have "precision of timing" or is call stack sampling better at telling me which code is superior?
I've faced a similar problem some time ago but that was on Linux which made it easier to tweak. Basically the noise introduced by OS (called "OS jitter") was as big as 5-10% in SPEC2000 tests (I can imagine it's much higher on Windows due to much bigger amount of bloatware).
I was able to bring deviation to below 1% by combination of the following:
disable dynamic frequency scaling (better do this both in BIOS and in Linux kernel as not all kernel versions do this reliably)
disable memory prefetching and other fancy settings like "Turbo boost", etc. (BIOS, again)
disable hyperthreading
enable high-performance process scheduler in kernel
bind process to core to prevent thread migration (use core 0 - for some reason it was more reliable on my kernel, go figure)
boot to single-user mode (in which no services are running) - this isn't as easy in modern systemd-based distros
disable ASLR
disable network
drop OS pagecache
There may be more to it but 1% noise was good enough for me.
I might put detailed instructions to github later today if you need them.
-- EDIT --
I've published my benchmarking script and instructions here.
Am I right that what you're doing is making an educated guess of what to fix, fixing it, and then trying to measure to see if it made any difference?
I do it a different way, which works especially well as the code gets large.
Rather than guess (which I certainly can) I let the program tell me how the time is spent, by using this method.
If the method tells me that roughly 30% is spent doing such-and-so, I can concentrate on finding a better way to do that.
Then I can run it and just time it.
I don't need a lot of precision.
If it's better, that's great.
If it's worse, I can undo the change.
If it's about the same, I can say "Oh well, maybe it didn't save much, but let's do it all again to find another problem,"
I need not worry.
If there's a way to speed up the program, this will pinpoint it.
And often the problem is not just a simple statement like "line or routine X spends Y% of the time", but "the reason it's doing that is Z in certain cases" and the actual fix may be elsewhere.
After fixing it, the process can be done again, because a different problem, which was small before, is now larger (as a percent, because the total has been reduced by fixing the first problem).
Repetition is the key, because each speedup factor multiplies all the previous, like compound interest.
When the program no longer points out things I can fix, I can be sure it is nearly optimal, or at least nobody else is likely to beat it.
And at no point in this process did I need to measure the time with much precision.
Afterwards, if I want to brag about it in a powerpoint, maybe I'll do multiple timings to get smaller standard error, but even then, what people really care about is the overall speedup factor, not the precision.
This is an unusual question, but I do hope there's a definitive answer.
There's a longstanding debate in our office about how efficiently compilers generate code, specifically number of instructions. We write code for low power embedded systems with virtually no loops. Therefore, the number of instructions emitted is directly proportional to power consumed.
Much of our code looks like this (notice, no dynamic memory allocation, no system calls, very few function calls, very few loops).
foo += 3 * (77 + bar);
if (baz > 18 - qux)
bar -= 19 + 7 >> spam;
I can compile the above snippet with -O3 and read the assembly, but I couldn't write it myself.
The claim I would like to prove or disprove is that compilers generate code that is 2-4X "fatter" (and therefore consume 2-4X times as much power) compared with hand written assembly code.
I'm interested in any compiler with which you have experience.
From this answer I know that GCC and clang can emit assembly interleaved with the C code with
gcc -g -c -Wa,-alh foo.cc
These answers provide solid basis:
When is assembly faster?
Why do you program in assembly?
How can I measure the efficiency with which a compiler generates code?
Hand assembly can always at least match if not beat the compiler, because at the very least, you can start with the compiler generated assembly code and tweak it to make it better. To really do a good job, you need to understand the CPU architecture (pipeline, functional units, memory hierarchy, out-of-order dispatch units, etc.) so that you can schedule each instruction for maximum efficiency.
Another thing to consider is that the number of instructions is not necessarily directly proportional to performance, whether it is speed or power (see Hennessey and Patterson's Computer Architecture: A Quantitative Approach). Basically, you have to look at how many clock cycles each instruction takes, in addition to the number of instructions (and clock rate) to know how long it will take. To know how much energy will be consumed, you also need to know how much energy each instruction takes.
How the CPU implements each instruction affects how many cycles it takes to execute. As an example, your code sequence has a >> operator. The compiler might translate that to a single ASR instruction, but without knowing the architecture, there is no telling how many clock cycles it might take -- some architectures can do an arbitrary shift in a single cycle, while others need one cycle for each bit shift.
Memory access contributes to the number of cycles and power consumption, too. When there are too many variables to store in registers some of them will have to be stored in memory. If you are accessing off chip memory and have a fairly high CPU clock rate, the memory bus can be pretty power hungry. A longer sequence of instructions that avoids reading from and writing to memory (e.g., by computing the same result twice) can be less expensive.
As several others have suggested, there is no substitute for benchmarking. Assuming you are using a microcontroller-based system with a constant input voltage, your best bet is to measure the current draw of your system with each alternative set of code and see which does best (one way would be with a current probe and a digital storage oscilloscope).
Even if you can always write better assembler than the compiler, there is a cost in development time and maintainability. In The Mythical Man Month Brooks estimated 3-5x more effort at time when many, if not most, programmers wrote code in assembler. Unless your code is really tiny, you are probably best off only coding the most critical parts in assembly. Even so, the person writing the assembly should be able to prove that their (more expensive) code is worth the cost by comparing running code vs. running code.
If the question is "how can I measure the efficiency with which a compiler generates code" (your actual question), the answer is "that depends". It depends on how you define "efficiency". Mostly, compilers are designed to optimize for speed. As you change the optimization level (-O1, -O2, -O3), the compiler will spend more time looking for "clever things to do to make it just a bit faster". This can involve loop unrolling, order of execution, use of registers, and many other things.
It seems that your "efficiency" criterion is not one that compilers are designed for: you say you want "fewest cycles" because you think that == lowest power. However I would argue that "fastest execution" == "shortest time before processor can go into standby mode again". Unless you believe that the power consumption of the processor in "awake" mode changes significantly with instructions executed, I think that it is safe to say that fastest execution == shortest time awake == lowest power consumption.
In which case "fat code" doesn't matter - it's back to speed only. Note also that not all instructions take the same number of clock cycles (although to be fair, that depends on the processor).
EDIT, okay that was fun...
Folks that make the blanket statement that compilers outperform humans, are the ones that have not actually checked. Anything a compiler can create a human can create. But a compiler cannot always create the code a human can create. It is that simple. For projects anywhere from a few lines to a few dozen lines or larger, it becomes easier and easier to hand fix the optimizations made by a compiler. Compiler and target help close that gap but there will always be the educated someone that will be able to meet or exceed the compilers output.
The claim I would like to prove or disprove is that compilers generate
code that is 2-4X "fatter" (and therefore consume 2-4X times as much
power) compared with hand written assembly code.
Unless you are defining "fatter" to mean uses that much power. Size of a binary and power consumption are not related. If this whole question/project is related to power consumption, the compiler wont take into account the bios settings you have chosen (assuming you are talking about pcs), the video card, hard disk, monitor, mouse, keyboard, etc, etc. In addition to the processor which is only one (relatively small) part of the equation. And even if it did would someone make a compiler that only makes your code efficient, they cant and wont tune the compiler for every system on the planet. Aint gonna happen.
If you are talking a mobile phone which is a very controlled environment the app may get tuned to save power, but the compiler is not the master of that, it is the user, the compiler does part of it the rest is hand tuned by the programmer.
I can compile the above snippet with -O3 and read the assembly, but I couldn't write it myself.
If you go into this with that kind of attitude then you have automatically failed. Yes you can meet or beat the compiler, period. It is a matter of confidence and will power and time/effort. That statement means you have not really studied the problem, which is why you are asking the question you are asking. Take some time, do some more research, ask detailed questions at stackoverflow (not open ended ones like this one), and with time you will understand what compilers do and dont do and why, in particular why they are not perfect (for any one or many rulers by which that opinion is defined). This question is wholly about opinion and will spark flame wars, and such and will get closed and eventually removed from this site. Instead write and compile and publish code segments and ask questions about "why did the compiler produce this output, why didnt it to [this] instead?" Those kinds of questions have a better chance at real answers and of staying here for others to learn from.
Is there an easy way to count the number of multiplications actually executed by a piece of standard C code? The code I have in mind basically just does additions and multiplications, and it's the multiplications that are of primary interest, but it wouldn't hurt to get counts of the other operations as well.
If it were an option, I suppose I could go around replacing 'a * b' with 'multiply(a, b)' and write a cover function for the native * operator, b/c I really don't care about time performance during this test, but the primary objection to doing that is having to re-work a pile of source code just to run the test.
I have no objection to re-compiling the source, perhaps against some library or with obscure (afaik) options. Valgrind came to mind, but if I understand valgrind's purpose, that's more about tracing values than counting operations.
Compile the source code into assembly language and then search for the multiply instructions.
Note that the optimization level can greatly affect the number that appear. For loops, you would have to determine the scope of multiplies within a loop and factor that into the result, but if the code is fairly constrained or limited in extent, that should be straightforward.
Note: a shameless extrapolation of my comment for as much rep as I can skim.
PAPI has two high-level API functions called PAPI_flips and PAPI_flops which can be used to record the FLOPS as well as the number of floating point operations. Additionally, PAPI offers lots of other performance counter monitoring capability, depending on your processor architecture... cache, bus, memory, branches, etc. I think there is support or support is emerging for graphics accelerators and CUDA/GPGPU.
PAPI will need to be installed on your system, but I think it's widespread enough that installation wouldn't be too painful, if you know what you're doing.
The nice thing about PAPI is that you don't need to know anything about the code; just instrument it (the interface is the same as a stopwatch for FLOPS) and run it. It's based on the actual dynamic execution of your program, so it takes into account things that are hard to account for analytically, such as (pseudo-)random behavior, user/variable input, and related branches.
If your compiler supports soft-float (i.e. using functions with integer implementations to emulate floating-point), you could compiler your program in that mode (-msoft-float in GCC), and use your favorite profiling tool to measure how many times they are invoked.
Many processors also have performance counters that can count the number of floating-point operations that have been retired. Depending on the hardware and OS, you may or may not need some amount of kernel support to take advantage of them.
The best that I can think of is (assuming you're running gdb):
If you could identify the points were multiplications are occurring, you could then set tracepoints just prior to the multiplication (or perhaps just after them depending on the details), then run the program and count the number of tracepoint dumps.
Yes, it is very crude. Certainly there are other solutions; however, I would hesitate to trash my stack for something as simple as a count.
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I have a question for all the hardcore low level hackers out there. I ran across this sentence in a blog. I don't really think the source matters (it's Haack if you really care) because it seems to be a common statement.
For example, many modern 3-D Games have their high performance core engine written in C++ and Assembly.
As far as the assembly goes - is the code written in assembly because you don't want a compiler emitting extra instructions or using excessive bytes, or are you using better algorithms that you can't express in C (or can't express without the compiler mussing them up)?
I completely get that it's important to understand the low-level stuff. I just want to understand the why program in assembly after you do understand it.
I think you're misreading this statement:
For example, many modern 3-D Games have their high performance core engine written in C++ and Assembly.
Games (and most programs these days) aren't "written in assembly" the same way they're "written in C++". That blog isn't saying that a significant fraction of the game is designed in assembly, or that a team of programmers sit around and develop in assembly as their primary language.
What this really means is that developers first write the game and get it working in C++. Then they profile it, figure out what the bottlenecks are, and if it's worthwhile they optimize the heck out of them in assembly. Or, if they're already experienced, they know which parts are going to be bottlenecks, and they've got optimized pieces sitting around from other games they've built.
The point of programming in assembly is the same as it always has been: speed. It would be ridiculous to write a lot of code in assembler, but there are some optimizations the compiler isn't aware of, and for a small enough window of code, a human is going to do better.
For example, for floating point, compilers tend to be pretty conservative and may not be aware of some of the more advanced features of your architecture. If you're willing to accept some error, you can usually do better than the compiler, and it's worth writing that little bit of code in assembly if you find that lots of time is spent on it.
Here are some more relevant examples:
Examples from Games
Article from Intel about optimizing a game engine using SSE intrinsics. The final code uses intrinsics (not inline assembler), so the amount of pure assembly is very small. But they look at the assembler output by the compiler to figure out exactly what to optimize.
Quake's fast inverse square root. Again, the routine doesn't have assembler in it, but you need to know something about architecture to do this kind of optimization. The authors know what operations are fast (multiply, shift) and which are slow (divide, sqrt). So they come up with a very tricky implementation of square root that avoids the slow operations entirely.
High-Performance Computing
Outside the domain of games, people in scientific computing frequently optimize the crap out of things to get them to run fast on the latest hardware. Think of this as games where you can't cheat on the physics.
A great recent example of this is Lattice Quantum Chromodynamics (Lattice QCD). This paper describes how the problem pretty much boils down to one very small computational kernel, which was optimized heavily for PowerPC 440's on an IBM Blue Gene/L. Each 440 has two FPUs, and they support some special ternary operations that are tricky for compilers to exploit. Without these optimizations, Lattice QCD would've run much slower, which is costly when your problem requires millions of CPU hours on expensive machines.
If you are wondering why this is important, check out the article in Science that came out of this work. Using Lattice QCD, these guys calculated the mass of a proton from first principles, and showed last year that 90% of the mass comes from strong force binding energy, and the rest from quarks. That's E=mc2 in action. Here's a summary.
For all of the above, the applications are not designed or written 100% in assembly -- not even close. But when people really need speed, they focus on writing the key parts of their code to fly on specific hardware.
I have not coded in assembly language for many years, but I can give several reasons that I frequently saw:
Not all compilers can make use of certain CPU optimizations and instruction set (e.g., the new instruction sets that Intel adds once in a while). Waiting for compiler writers to catch up means losing a competitive advantage.
Easier to match actual code to known CPU architecture and optimization. For example, things you know about the fetching mechanism, caching, etc. This is supposed to be transparent to the developer, but the fact is that it is not, that's why compiler writers can optimize.
Certain hardware level accesses are only possible/practical via assembly language (e.g., when writing device driver).
Formal reasoning is sometimes actually easier for the assembly language than for the high-level language since you already know what the final or almost final layout of the code is.
Programming certain 3D graphic cards (circa late 1990s) in the absence of APIs was often more practical and efficient in assembly language, and sometimes not possible in other languages. But again, this involved really expert-level games based on the accelerator architecture like manually moving data in and out in certain order.
I doubt many people use assembly language when a higher-level language would do, especially when that language is C. Hand-optimizing large amounts of general-purpose code is impractical.
There is one aspect of assembler programming which others have not mentioned - the feeling of satisfaction you get knowing that every single byte in an application is the result of your own effort, not the compiler's. I wouldn't for a second want to go back to writing whole apps in assembler as I used to do in the early 80s, but I do miss that feeling sometimes...
Usually, a layman's assembly is slower than C (due to C's optimization) but many games (I distinctly remember Doom) had to have specific sections of the game in Assembly so it would run smoothly on normal machines.
Here's the example to which I am referring.
I started professional programming in assembly language in my very first job (80's). For embedded systems the memory demands - RAM and EPROM - were low. You could write tight code that was easy on resources.
By the late 80's I had switched to C. The code was easier to write, debug and maintain. Very small snippets of code were written in assembler - for me it was when I was writing the context switching in an roll-your-own RTOS. (Something you shouldn't do anymore unless it is a "science project".)
You will see assembler snippets in some Linux kernel code. Most recently I've browsed it in spinlocks and other synchronization code. These pieces of code need to gain access to atomic test-and-set operations, manipulating caches, etc.
I think you would be hard pressed to out-optimize modern C compilers for most general programming.
I agree with #altCognito that your time is probably better spent thinking harder about the problem and doing things better. For some reason programmers often focus on micro-efficiencies and neglect the macro-efficiencies. Assembly language to improve performance is a micro-efficiency. Stepping back for a wider view of the system can expose the macro problems in a system. Solving the macro problems can often yield better performance gains.
Once the macro problems are solved then collapse to the micro level.
I guess micro problems are within the control of a single programmer and in a smaller domain. Altering behavior at the macro level requires communication with more people - a thing some programmers avoid. That whole cowboy vs the team thing.
"Yes". But, understand that for the most part the benefits of writing code in assembler are not worth the effort. The return received for writing it in assembly tends to be smaller than the simply focusing on thinking harder about the problem and spending your time thinking of a better way of doing thigns.
John Carmack and Michael Abrash who were largely responsible for writing Quake and all of the high performance code that went into IDs gaming engines go into this in length detail in this book.
I would also agree with Ólafur Waage that today, compilers are pretty smart and often employ many techniques which take advantage of hidden architectural boosts.
These days, for sequential codes at least, a decent compiler almost always beats even a highly seasoned assembly-language programmer. But for vector codes it's another story. Widely deployed compilers don't do such a great job exploiting the vector-parallel capabilities of the x86 SSE unit, for example. I'm a compiler writer, and exploiting SSE tops my list of reasons to go on your own instead of trusting the compiler.
SSE code works better in assembly than compiler intrinsics, at least in MSVC. (i.e. does not create extra copies of data )
I've three or four assembler routines (in about 20 MB source) in my sources at work. All of them are SSE(2), and are related to operations on (fairly large - think 2400x2048 and bigger) images.
For hobby, I work on a compiler, and there you have more assembler. Runtime libraries are quite often full of them, most of them have to do with stuff that defies the normal procedural regime (like helpers for exceptions etc.)
I don't have any assembler for my microcontroller. Most modern microcontrollers have so much peripheral hardware (interrupt controled counters, even entire quadrature encoders and serial building blocks) that using assembler to optimize the loops is often not needed anymore. With current flash prices, the same goes for code memory. Also there are often ranges of pin-compatible devices, so upscaling if you systematically run out of cpu power or flash space is often not a problem
Unless you really ship 100000 devices and programming assembler makes it possible to really make major savings by just fitting in a flash chip a category smaller. But I'm not in that category.
A lot of people think embedded is an excuse for assembler, but their controllers have more CPU power than the machines Unix was developed on. (Microchip coming
with 40 and 60 MIPS microcontrollers for under USD 10).
However a lot people are stuck with legacy, since changing microchip architecture is not easy. Also the HLL code is very architecture dependent (because it uses the hardware periphery, registers to control I/O, etc). So there are sometimes good reasons to keep maintaining a project in assembler (I was lucky to be able to setup affairs on a new architecture from scratch). But often people kid themselves that they really need the assembler.
I still like the answer a professor gave when we asked if we could use GOTO (but you could read that as ASSEMBLER too): "if you think it is worth writing a 3 page essay on why you need the feature, you can use it. Please submit the essay with your results. "
I've used that as a guiding principle for lowlevel features. Don't be too cramped to use it, but make sure you motivate it properly. Even throw up an artificial barrier or two (like the essay) to avoid convoluted reasoning as justification.
Some instructions/flags/control simply aren't there at the C level.
For example, checking for overflow on x86 is the simple overflow flag. This option is not available in C.
Defects tend to run per-line (statement, code point, etc.); while it's true that for most problems, assembly would use far more lines than higher level languages, there are occasionally cases where it's the best (most concise, fewest lines) map to the problem at hand. Most of these cases involve the usual suspects, such as drivers and bit-banging in embedded systems.
If you were around for all the Y2K remediation efforts, you could have made a lot of money if you knew Assembly. There's still plenty of legacy code around that was written in it, and that code occasionally needs maintenance.
Another reason could be when the available compiler just isn't good enough for an architecture and the amount of code needed in the program is not that long or complex as for the programmer to get lost in it. Try programming a microcontroller for an embedded system, usually assembly will be much easier.
Beside other mentioned things, all higher languages have certain limitations. Thats why some people choose to programm in ASM, to have full control over their code.
Others enjoy very small executables, in the range of 20-60KB, for instance check HiEditor, which is implemented by author of the HiEdit control, superb powerfull edit control for Windows with syntax highlighting and tabs in only ~50kb). In my collection I have more then 20 such gold controls from Excell like ssheets to html renders.
I think a lot of game developers would be surprised at this bit of information.
Most games I know of use as little assembly as at all possible. In some cases none at all, and at worst, one or two loops or functions.
That quote is over-generalized, and nowhere near as true as it was a decade ago.
But hey, mere facts shouldn't hinder a true hacker's crusade in favor of assembly. ;)
If you are programming a low end 8 bit microcontroller with 128 bytes of RAM and 4K of program memory you don't have much choice about using assembly. Sometimes though when using a more powerful microcontroller you need a certain action to take place at an exact time. Assembly language comes in useful then as you can count the instructions and so measure the clock cycles used by your code.
Games are pretty performance hungry and although in the meantime the optimizers are pretty good a "master programmer" is still able to squeeze out some more performance by hand coding the right parts in assembly.
Never ever start optimizing your program without profiling it first. After profiling should be able to identify bottlenecks and if finding better algorithms and the like don't cut it anymore you can try to hand code some stuff in assembly.
Aside from very small projects on very small CPUs, I would not set out to ever program an entire project in assembly. However, it is common to find that a performance bottleneck can be relieved with the strategic hand coding of some inner loops.
In some cases, all that is really required is to replace some language construct with an instruction that the optimizer cannot be expected to figure out how to use. A typical example is in DSP applications where vector operations and multiply-accumulate operations are difficult for an optimizer to discover, but easy to hand code.
For example certain models of the SH4 contain 4x4 matrix and 4 vector instructions. I saw a huge performance improvement in a color correction algorithm by replacing equivalent C operations on a 3x3 matrix with the appropriate instructions, at the tiny cost of enlarging the correction matrix to 4x4 to match the hardware assumption. That was achieved by writing no more than a dozen lines of assembly, and carrying matching adjustments to the related data types and storage into a handful of places in the surrounding C code.
It doesn't seem to be mentioned, so I thought I'd add it: in modern games development, I think at least some of the assembly being written isn't for the CPU at all. It's for the GPU, in the form of shader programs.
This might be needed for all sorts of reasons, sometimes simply because whatever higher-level shading language used doesn't allow the exact operation to be expressed in the exact number of instructions wanted, to fit some size-constraint, speed, or any combination. Just as usual with assembly-language programming, I guess.
Almost every medium-to-large game engine or library I've seen to date has some hand-optimized assembly versions available for matrix operations like 4x4 matrix concatenation. It seems that compilers inevitably miss some of the clever optimizations (reusing registers, unrolling loops in a maximally efficient way, taking advantage of machine-specific instructions, etc) when working with large matrices. These matrix manipulation functions are almost always "hotspots" on the profile, too.
I've also seen hand-coded assembly used a lot for custom dispatch -- things like FastDelegate, but compiler and machine specific.
Finally, if you have Interrupt Service Routines, asm can make all the difference in the world -- there are certain operations you just don't want occurring under interrupt, and you want your interrupt handlers to "get in and get out fast"... you know almost exactly what's going to happen in your ISR if it's in asm, and it encourages you to keep the bloody things short (which is good practice anyway).
I have only personally talked to one developer about his use of assembly.
He was working on the firmware that dealt with the controls for a portable mp3 player.
Doing the work in assembly had 2 purposes:
Speed: delays needed to be minimal.
Cost: by being minimal with the code, the hardware needed to run it could be slightly less powerful. When mass-producing millions of units, this can add up.
The only assembler coding I continue to do is for embedded hardware with scant resources. As leander mentions, assembly is still well suited to ISRs where the code needs to be fast and well understood.
A secondary reason for me is to keep my knowledge of assembly functional. Being able to examine and understand the steps which the CPU is taking to do my bidding just feels good.
Last time I wrote in assembler was when I could not convince the compiler to generate libc-free, position independent code.
Next time will probably be for the same reason.
Of course, I used to have other reasons.
A lot of people love to denigrate assembly language because they've never learned to code with it and have only vaguely encountered it and it has left them either aghast or somewhat intimidated. True talented programmers will understand that it is senseless to bash C or Assembly because they are complimentary. in fact the advantage of one is the disadvantage of the other. The organized syntaxic rules of C improves clarity but at the same gives up all the power assembly has from being free of any structural rules ! C code instruction are made to create non-blocking code which could be argued forces clarity of programming intent but this is a power loss. In C the compiler will not allow a jump inside an if/elseif/else/end. Or you are not allowed to write two for/end loops on diferent variables that overlap each other, you cannot write self modifying code (or cannot in an seamless easy way), etc.. conventional programmers are spooked by the above, and would have no idea how to even use the power of these approaches as they have been raised to follow conventional rules.
Here is the truth : Today we have machine with the computing power to do much more that the application we use them for but the human brain is too incapable to code them in a rule free coding environment (= assembly) and needs restrictive rules that greatly reduce the spectrum and simplifies coding.
I have myself written code that cannot be written in C code without becoming hugely inefficient because of the above mentionned limitations. And i have not yet talked about speed which most people think is the main reason for writting in assembly, well it is if you mind is limited to thinking in C then you are the slave of you compiler forever. I always thought chess players masters would be ideal assembly programmers while the C programmers just play "Dames".
No longer speed, but Control. Speed will sometimes come from control, but it is the only reason to code in assembly. Every other reason boils down to control (i.e. SSE and other hand optimization, device drivers and device dependent code, etc.).
If I am able to outperform GCC and Visual C++ 2008 (known also as Visual C++ 9.0) then people will be interested in interviewing me about how it is possible.
This is why for the moment I just read things in assembly and just write __asm int 3 when required.
I hope this help...
I've not written in assembly for a few years, but the two reasons I used to were:
The challenge of the thing! I went through a several-month period years
ago when I'd write everything in x86 assembly (the days of DOS and Windows
3.1). It basically taught me a chunk of low level operations, hardware I/O, etc.
For some things it kept size small (again DOS and Windows 3.1 when writing TSRs)
I keep looking at coding assembly again, and it's nothing more than the challenge and joy of the thing. I have no other reason to do so :-)
I once took over a DSP project which the previous programmer had written mostly in assembly code, except for the tone-detection logic which had been written in C, using floating-point (on a fixed-point DSP!). The tone detection logic ran at about 1/20 of real time.
I ended up rewriting almost everything from scratch. Almost everything was in C except for some small interrupt handlers and a few dozen lines of code related to interrupt handling and low-level frequency detection, which runs more than 100x as fast as the old code.
An important thing to bear in mind, I think, is that in many cases, there will be much greater opportunities for speed enhancement with small routines than large ones, especially if hand-written assembler can fit everything in registers but a compiler wouldn't quite manage. If a loop is large enough that it can't keep everything in registers anyway, there's far less opportunity for improvement.
The Dalvik VM that interprets the bytecode for Java applications on Android phones uses assembler for the dispatcher. This movie (about 31 minutes in, but its worth watching the whole movie!) explains how
"there are still cases where a human can do better than a compiler".
I don't, but I've made it a point to at least try, and try hard at some point in the furture (soon hopefully). It can't be a bad thing to get to know more of the low level stuff and how things work behind the scenes when I'm programming in a high level language. Unfortunately time is hard to come by with a full time job as a developer/consultant and a parent. But I will give at go in due time, that's for sure.
I am a firm believer in the idea that one of the most important things you get from learning a new language is not how to use a new language, but the knowledge of concepts that you get from it. I am not asking how important or useful you think Assembly is, nor do I care if I never use it in any of my real projects.
What I want to know is what concepts of Assembly do you think are most important for any general programmer to know? It doesn't have to be directly related to Assembly - it can also be something that you feel the typical programmer who spends all their time in higher-level languages would not understand or takes for granted, such as the CPU cache.
Register allocation and management
Assembly gives you a very good idea of how many variables (machine-word-sized integers) the CPU can juggle simultaneously. If you can break your loops down so that they involve only a few temporary variables, they'll all fit in registers. If not, your loop will run slowly as things get swapped out to memory.
This has really helped me with my C coding. I try to make all loops tight and simple, with as little spaghetti as possible.
x86 is dumb
Learning several assembly languages has made me realize how lame the x86 instruction set is. Variable-length instructions? Hard-to-predict timing? Non-orthogonal addressing modes? Ugh.
The world would be better if we all ran MIPS, I think, or even ARM or PowerPC :-) Or rather, if Intel/AMD took their semiconductor expertise and used it to make multi-core, ultra-fast, ultra-cheap MIPS processors instead of x86 processors with all of those redeeming qualities.
I think assembly language can teach you lots of little things, as well as a few big concepts.
I'll list a few things I can think of here, but there is no substitute for going and learning and using both x86 and a RISC instruction set.
You probably think that integer operations are fastest. If you want to find an integer square root of an integer (i.e. floor(sqrt(i))) it's best to use an integer-only approximation routine, right?
Nah. The math coprocessor (on x86 that is) has a fsqrt instruction. Converting to float, taking the square root, and converting to int again is faster than an all-integers algorithm.
Then there are things like accessing memory that you can follow, but not properly apprecatiate, until you've delved into assembly. Say you had a linked list, and the first element in the list contains a variable that you will need to access frequently. The list is reordered rarely. Well, each time you need to access that variable, you need to load the pointer to the first element in the list, then using that, load the variable (assuming you can't keep the address of the variable in a register between uses). If you instead stored the variable outside of the list, you only need a single load operation.
Of course saving a couple of cycles here and there is usually not important these days. But if you plan on writing code that needs to be fast, this kind of knowledge can be applied both with inline assembly and generally in other languages.
How about calling conventions? (Some assemblers take care of this for you - Real Programmers don't use those.) Does the caller or callee clean up the stack? Do you even use the stack? You can pass values in registers - but due to the funny x86 instruction set, it's better to pass certain things in certain registers. And which registers will be preserved? One thing C compilers can't really optimise by themselves is calls.
There are little tricks like PUSHing a return address and then JMPing into a procedure; when the procedure returns it will go to the PUSHed address. This departure from the usual way of thinking about function calls is another one of those "states of enlightenment". If you were ever to design a programming language with innovative features, you ought to know about funny things that the hardware is capable of.
A knowledge of assembly language teaches you architecture-specific things about computer security. How you might exploit buffer overflows, or break into kernel mode, and how to prevent such attacks.
Then there's the ubercoolness of self-modifying code, and as a related issue, mechanisms for things such as relocations and applying patches to code (this needs investigation of machine code as well).
But all these things need the right sort of mind. If you're the sort of person who can put
while(x--)
{
...
}
to good use once you learn what it does, but would find it difficult to work out what it does by yourself, then assembly language is probably a waste of your time.
It's good to know assembly language in order to gain a better appreciation for how the computer works "under the hood," and it helps when you are debugging something and all the debugger can give you is an assembly code listing, which at least gives you fighting chance of figuring out what the problem might be. However, trying to apply low-level knowledge to high-level programming languages, such as trying to take advantage of how the CPU caches instructions and then writing wonky high-level code to force the compiler to produce super-efficient machine code, is probably a sign that you are trying to micro-optimize. In most cases, it's usually better not to try to outsmart the compiler, unless you need the performance gain, in which case, you might as well write those bits in assembly anyway.
So, it's good to know assembly for the sake of better understanding of how things work, but the knowledge gained is not necessarily directly applicable to how you write code in high-level languages. On that note, however, I found that learning how function calls work at the assembly-code level (learning about the stack and related registers, learning about how parameters are passed on the stack, learning how automatic storage works, etc.) made it a lot easier to understand problems I had in higher-level code, such as "out of stack space" errors and "invalid calling convention" errors.
The most important concept is SIMD, and creative use of it. Proper use of SIMD can give enormous performance benefits in a massive variety of applications ranging from everything from string processing to video manipulation to matrix math. This is where you can get over 10x performance boosts over pure C code--this is why assembly is still useful beyond mere debugging.
Some examples from the project I work on (all numbers are clock cycle counts on a Core 2):
Inverse 8x8 H.264 DCT (frequency transform):
c: 1332
mmx: 187
sse2: 127
8x8 Chroma motion compensation (bilinear interpolation filter):
c: 639
mmx: 144
sse2: 110
ssse3: 79
4 16x16 Sum of Absolute Difference operations (motion search):
c: 3948
mmx: 278
sse2: 231
ssse3: 215
(yes, that's right--over 18x faster than C!)
Mean squared error of a 16x16 block:
c: 1013
mmx: 193
sse2: 131
Variance of a 16x16 block:
c: 783
mmx: 171
sse2: 106
Memory, registers, jumps, loops, shifts and the various operations one can perform in assembler. I don't miss the days of debugging my assembly language class programs - they were painful! - but it certainly gave me a good foundation.
We forget (or never knew, perhaps) that all this fancy-pants stuff that we use today (and that I love!) boils down to all this stuff in the end.
Now, we can certainly have a productive and lucrative career without knowing assembler, but I think these concepts are good to know.
I would say that learning recursion and loops in assembly has taught me alot. It made me understand the underlying concept of how the compiler/interpreter of the language i'm using pushes things onto a stack, and pops them off as it needs them. I also learned how to exploit the infamous stack overflow. (which is still surprisingly easy in C with some get- and put- commands).
Other than using asm in every-day situations, i don't think that i would use any of the concepts assembly taught me.
I would say that addressing modes are extremely important.
My alma mater took that to an extreme, and because x86 didn't have enough of them, we studied everything on a simulator of PDP11 that must have had at least 7 of them that I remember. In retrospect, that was a good choice.
timing
fast execution:
parallel processing
simple instructions
lookup tables
branch prediction, pipelining
fast to slow access to storage:
registers
cache, and various levels of cache
memory heap and stack
virtual memory
external I/O
Nowadays, x86 asm is not a direct line to the guts of the CPU, but more of an API. The assembler opcodes you write are themselves are compiled into a completely different instruction-set, rearranged, rewritten, fixed-up and generally mangled beyond recognition.
So it's not like learning assembler gives you a fundamental insight into what's going on inside the CPU. IMHO, more important than learning assembler is to get a good understanding of how the target CPU and the memory hierarchy works.
This series of articles covers the latter topic pretty thoroughly.