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I'm studying llvm recently.
I have a C code name cal.c. Now, I apply two different optimization passes on this code and generate two different IR codes - cal1.ll and cal2.ll.
How could I compare the performance between them?
I tried compare instruction counts and instruction cost but those of them are not good features. I think there are no relations between instruction counts and performance, instruction costs and performance.
So, how could I compare the performance between two IR?
I don't need to know the run time. I just want to know which is the faster.
This is a hard problem, often much harder than just running you code on the actual hardware and measure which is faster. It more or less boils down to simulate the hardware using "pen and paper". You will need a detailed model of the target system including things like pipeline and cache behavior and then use this model to calculate the cost of each executed instruction.
llvm-mca tries to statically estimate performance of assembly code by reusing LLVM compiler's CPU pipeline model:
$ llvm-mca -mcpu=skylake foo.s
Iterations: 300
Instructions: 900
Total Cycles: 610
Total uOps: 900
As mentioned by others, the estimates would be imprecise (often very imprecise) due to lack of cache and branch predictor models, imprecision of CPU pipeline model, etc.
Currently I am doing a performance comparison on two 32bit microcontrollers. I used Dhrystone benchmark to run on both microcontrollers. One microcontroller has 4KB I-cache while second coontroller has 8KB of I-cache. Both microcontrollers are using same tool chain. As much as possible I kept same static and run-time settings onboth microcontrollers. But microcontroller with 4KB cache are faster than 8KB cache microcontroller. Both microcontroller are from same vendor and based on same CPU.
Could anyone provide some information why microcontroller with 4KB cache is faster than other?
Benchmarks are in general useless. dhrystone being one of the oldest ones and it may have had a little bit of value back then, before pipelines and too much compiler optimization. I think I gave up on dhrystone 15 years ago roughly about the time I started using it.
It is trivial to demonstrate that this code
.globl ASMDELAY
ASMDELAY:
sub r0,r0,#1
bne ASMDELAY
bx lr
Which is primarily two INSTRUCTIONS, can vary WIDELY in execution time on the same chip if you understand how modern processors work. The simple trick to seeing this is turn off the caches and prefetchers and such, and place this code at offset 0x0000, call it with some value. place it at 0x0004 repeat, then at 0x0008, repeat. keep doing this. You can put one, two, etc nops between the subtract and branch. try it at various offsets.
THEN, turn on and of caches for each of these alignments, if you have a prefetch outside the processor for the flash, turn that on and off.
THEN, vary your clocks, esp for those MCUs where you have to adjust the wait states based on clock rate.
On a SINGLE MCU, you are going to see those essentially two instructions vary in execution time by a very large amount. Lets just say 20 times longer in some cases than others.
Now take a small program or a small fraction of the dhrystone program. Compile that for your mcu, how many instructions do you see? Make minor to major optimization and other variations on the compile command line, how much does the code change. If two instructions can vary by lets call it 20 times in execution time, how bad can it get for 200 instructions or 2000 instructions? It can get pretty bad.
If you take the dhrystone programs you have right now with the compiler options you have right now, go into your bootstrap, add one nop (causing the entire binary to shift by one instruction in flash) run again. Add two, three, four. You are still not comparing different mcus just running your benchmark on one system.
Run with and without d cache, with and without i cache if you have each of those. turn on and off the flash prefetch if you have one and if you have a write buffer you can turn on and of try that. Still remaining on the same compiler same options same mcu.
Take the different functions in the dhrystone source code, and re-arrange them in the source code. instead of Proc_1, Proc_2, Proc_3 make it Proc_1, Proc_3, Proc_2. Do all of the above again. Re-arrange again, repeat.
Before leaving this mcu you should now see that the execution time of the same source code which is completely unmodified (other than perhaps re-arranging functions) can and will have vastly different execution times.
if you then start changing compiler options or keep the same source and change compilers, you will see even more of a difference in execution time.
How is it possible that dhrystone benchmarks today or from way back had a single result for each platform? Simple, that result was just one of a wide range, not really representing the platform.
So then if you try to compare two different hardware platforms be it the same arm core inside a different mcu from the same vendor or different vendors. the arm core, assuming (which is not a safe assumption) it is the same source with the same compile/build options, even assuming the same verilog compile and synthesis was used. you can have that same core change based on arm provided options. Anyway, how the vendor be it the same vendor in two instances or two different vendors wraps that same core, you will see variations. Then take a completely different core be it another arm or a mips, etc. How could you gain any value comparing those using a program like this that itself varies widely on each platform?
You cant. What you can do is use benchmarks to give the illusion of one thing being better than another, one computer is faster than another, one compiler is faster than another. In order to sell computers or compilers. Sprints coverage is within one percent of Verizons...does that tell us anything useful? Nope.
If you were to eliminate the compiler from the equation, and if these are truly the same "CPU", same rev of source from ARM, built the same way, then they should fetch the same, but the size of the cache is part of that so it may already be a different cpu implementation as the width or depth of the cache can affect things. In software it is like needing a 32 bit pointer rather than a 16 bit pointer (17 bit instead of 16, but you cant have a 17 bit generally in logic you can).
Anyway, if you compile the code under test one time for an address space that is common to both platforms, use that same binary exactly for that space, can attach different bootstrap code as needed, note the C library calls strcpy, etc also have to be the same in the same space between platforms to eliminate the compiler and alignment from messing you up. this may or may not level the playing field.
If you want to believe these are the same cpu, then turn the caches off, eliminate the compiler variations by doing the above. See if they execute the same. Copy the program to ram and run in ram, eliminate the flash issues. I assume you have them both clocked the same with the same wait states in the flash?
if they are the same cpu and the chip vendor has with these two chips made the memory system take the same number of clocks say for ram accesses, and it is really the same cpu, you should be able to get the same time by eliminating optimizations (caching, flash prefetching, alignment).
what you are probably seeing is some form of alignment with how the code lies in memory from the compiler vs cache lines, or it could be much much simpler it could be just the differences in the caches, how the hits and misses work and the 4KB is just more lucky than the 8KB for this particular program compiled a certain way, aligned in memory a certain way, etc.
With the simple two instruction loop above it is easy to see some of the reasons why performance varies on the same system, if your modern cpu fetches 8 instructions at a time and your loop gets too close to the tail end of that fetch, the prefetch may think it needs to fetch another 8 beyond that costing you those clock cycles. Certainly as you exactly straddle two "fetch lines" as I call them with those two instructions it is going to cost you a lot more cycles per loop even with a cache. Same problem happens when those two instructions approach a cache line (as you vary their alignment per test) eventually it takes two cache line reads instead of one to fetch those two instructions. At least the first time through there is an extra cache line read. The extra clocks for that first time through is something you can see using a simple benchmark like that while playing with alignment.
Michael Abrash, Zen of Assembly Language. There is an epub/etc you can build from github of this book. the 8088 was obsolete when this book came out if that is all you see 8088 stuff, then you are completely missing the point. It applies to the most modern processors today, how to view the problem, how to test, how to time the test, how to interpret the results. All the stuff I have mentioned so far, and all the things I know about this that I have not mentioned, all came from that books knowledge applied for however many decades I have been doing this.
So again if you have truly eliminated the compiler, alignment, the cpu, the memory system tied to that cpu, etc and it is down to only the size of the cache varies. Then it is probably related to how the cache line fetches hit and miss differently based on alignment of the code relative to the cache lines for the two caches. One is hitting more and missing less and/or evicting better for this particular binary. You can try rearranging the functions, can add nops, or if you cant get at the bootstrap then add whole functions or more code (another printf, etc) at a lower address in the binary causing the linker to slide the code under test through to different addresses changing how the program lines up with the cache lines. Since the functions in the code under test are so big (more than a few instructions to implement) you would have to start modifying the program in order to get a finer grained adjustment of binary relative to cache lines.
You most definitely should see execution time differences on the two platforms if you adjust alignment and or wholesale re-arrange the binary based on functions being re-arranged.
Bottom line benchmarks dont really tell you much, the results have more of a negative stink to them than a positive joy. Without a re-write a particular benchmark or application may just do better on one platform (be it everything is the same but the size of the cache or two completely different architectures) even when you try to vary the results due to alignment, turning on and off prefetching, write buffering, branch prediction, etc. Pulling out all the tricks you can come up with one may vary from x to y the other from n to m and maybe there is some overlap in the ranges. For these two platforms that you say are similiar except for cache size I would hope you could find a combination where sometimes A is faster than B and at least one combination where B is faster than A, with the same features turned on and off for both in that comparision. If/when you switch to some other application/benchmark this all starts over again, no reason to assume dhrystone results predict any other code under test. The only program that matters, esp on an MCU is the final build of your application. Just remember changing a single line of code, or even adding a single nop in the bootstrap can have dramatic results in performance sometimes several TIMES slower or faster from a single nop.
LOOP (Intel ref manual entry)
decrements ecx / rcx, and then jumps if non-zero. It's slow, but couldn't Intel have cheaply made it fast? dec/jnz already macro-fuses into a single uop on Sandybridge-family; the only difference being that that sets flags.
loop on various microarchitectures, from Agner Fog's instruction tables:
K8/K10: 7 m-ops
Bulldozer-family/Ryzen: 1 m-op (same cost as macro-fused test-and-branch, or jecxz)
P4: 4 uops (same as jecxz)
P6 (PII/PIII): 8 uops
Pentium M, Core2: 11 uops
Nehalem: 6 uops. (11 for loope / loopne). Throughput = 4c (loop) or 7c (loope/ne).
SnB-family: 7 uops. (11 for loope / loopne). Throughput = one per 5 cycles, as much of a bottleneck as keeping your loop counter in memory! jecxz is only 2 uops with same throughput as regular jcc
Silvermont: 7 uops
AMD Jaguar (low-power): 8 uops, 5c throughput
Via Nano3000: 2 uops
Couldn't the decoders just decode the same as lea rcx, [rcx-1] / jrcxz? That would be 3 uops. At least that would be the case with no address-size prefix, otherwise it has to use ecx and truncate RIP to EIP if the jump is taken; maybe the odd choice of address-size controlling the width of the decrement explains the many uops? (Fun fact: rep-string instructions have the same behaviour with using ecx with 32-bit address-size.)
Or better, just decode it as a fused dec-and-branch that doesn't set flags? dec ecx / jnz on SnB decodes to a single uop (which does set flags).
I know that real code doesn't use it (because it's been slow since at least P5 or something), but AMD decided it was worth it to make it fast for Bulldozer. Probably because it was easy.
Would it be easy for SnB-family uarch to have fast loop? If so, why don't they? If not, why is it hard? A lot of decoder transistors? Or extra bits in a fused dec&branch uop to record that it doesn't set flags? What could those 7 uops be doing? It's a really simple instruction.
What's special about Bulldozer that made a fast loop easy / worth it? Or did AMD waste a bunch of transistors on making loop fast? If so, presumably someone thought it was a good idea.
If loop was fast, it would be perfect for BigInteger arbitrary-precision adc loops, to avoid partial-flag stalls / slowdowns (see my comments on my answer), or any other case where you want to loop without touching flags. It also has a minor code-size advantage over dec/jnz. (And dec/jnz only macro-fuses on SnB-family).
On modern CPUs where dec/jnz is ok in an ADC loop, loop would still be nice for ADCX / ADOX loops (to preserve OF).
If loop had been fast, compilers would already be using it as a peephole optimization for code-size + speed on CPUs without macro-fusion.
It wouldn't stop me from getting annoyed at all the questions with bad 16bit code that uses loop for every loop, even when they also need another counter inside the loop. But at least it wouldn't be as bad.
In 1988, IBM fellow Glenn Henry had just come on board at Dell, which had a few hundred employees at the time, and in his first month he gave a tech talk about 386 internals. A bunch of us BIOS programmers had been wondering why LOOP was slower than DEC/JNZ so during the question/answer section somebody posed the question.
His answer made sense. It had to do with paging.
LOOP consists of two parts: decrementing CX, then jumping if CX is not zero. The first part cannot cause a processor exception, whereas the jump part can. For one, you could jump (or fall through) to an address outside segment boundaries, causing a SEGFAULT. For two, you could jump to a page that is swapped out.
A SEGFAULT usually spells the end for a process, but page faults are different. When a page fault occurs, the processor throws an exception, and the OS does the housekeeping to swap in the page from disk into RAM. After that, it restarts the instruction that caused the fault.
Restarting means restoring the state of the process to what it was just before the offending instruction. In the case of the LOOP instruction in particular, it meant restoring the value of the CX register. One might think you could just add 1 to CX, since we know CX got decremented, but apparently, it's not that simple. For example, check out this erratum from Intel:
The protection violations involved usually indicate a probable
software bug and restart is not desired if one of these violations
occurs. In a Protected Mode 80286 system with wait states during any
bus cycles, when certain protection violations are detected by the
80286 component, and the component transfers control to the exception
handling routine, the contents of the CX register may be unreliable.
(Whether CX contents are changed is a function of bus activity at the
time internal microcode detects the protection violation.)
To be safe, they needed to save the value of CX on every iteration of a LOOP instruction, in order to reliably restore it if needed.
It's this extra burden of saving CX that made LOOP so slow.
Intel, like everyone else at the time, was getting more and more RISC. The old CISC instructions (LOOP, ENTER, LEAVE, BOUND) were being phased out. We still used them in hand-coded assembly, but compilers ignored them completely.
Now that I googled after writing my question, it turns out to be an exact duplicate of one on comp.arch, which came up right away. I expected it to be hard to google (lots of "why is my loop slow" hits), but my first try (why is the x86 loop instruction slow) got results.
This is not a good or complete answer.
It might be the best we'll get, and will have to suffice unless someone can shed some more light on it. I didn't set out to write this as an answer-my-own-question post.
Good posts with different theories in that thread:
Robert
LOOP became slow on some of the earliest machines (circa 486) when
significant pipelining started to happen, and running any but the
simplest instruction down the pipeline efficiently was technologically
impractical. So LOOP was slow for a number of generations. So nobody
used it. So when it became possible to speed it up, there was no real
incentive to do so, since nobody was actually using it.
Anton Ertl:
IIRC LOOP was used in some software for timing loops; there was
(important) software that did not work on CPUs where LOOP was too fast
(this was in the early 90s or so). So CPU makers learned to make LOOP
slow.
(Paul, and anyone else: You're welcome to re-post your own writing as your own answer. I'll remove it from my answer and up-vote yours.)
#Paul A. Clayton (occasional SO poster and CPU architecture guy) took a guess at how you could use that many uops. (This looks like loope/ne which checks both the counter and ZF):
I could imagine a possibly sensible 6-µop version:
virtual_cc = cc;
temp = test (cc);
rCX = rCX - temp; // also setting cc
cc = temp & cc; // assumes branch handling is not
// substantially changed for the sake of LOOP
branch
cc = virtual_cc
(Note that this is 6 uops, not SnB's 11 for LOOPE/LOOPNE, and is a total guess not even trying to take into account anything known from SnB perf counters.)
Then Paul said:
I agree that a shorter sequence should be possible, but I was trying
to think of a bloated sequence that might make sense if minimal
microarchitectural adjustments were permitted.
summary: The designers wanted loop to be supported only via microcode, with no adjustments whatsoever to the hardware proper.
If a useless, compatibility-only instruction is handed to the
microcode developers, they might reasonably not be able or willing to
suggest minor changes to the internal microarchitecture to improve
such an instruction. Not only would they rather use their "change
suggestion capital" more productively but the suggestion of a change
for a useless case would reduce the credibility of other suggestions.
(My opinion: Intel is probably still making it slow on purpose, and hasn't bothered to rewrite their microcode for it for a long time. Modern CPUs are probably too fast for anything using loop in a naive way to work correctly.)
... Paul continues:
The architects behind Nano may have found avoiding the special casing
of LOOP simplified their design in terms of area or power. Or they
may have had incentives from embedded users to provide a fast
implementation (for code density benefits). Those are just WILD
guesses.
If optimization of LOOP fell out of other optimizations (like fusion
of compare and branch), it might be easier to tweak LOOP into a fast
path instruction than to handle it in microcode even if the
performance of LOOP was unimportant.
I suspect that such decisions are based on specific details of the
implementation. Information about such details does not seem to be
generally available and interpreting such information would be
beyond the skill level of most people. (I am not a hardware
designer--and have never played one on television or stayed at a
Holiday Inn Express. :-)
The thread then went off-topic into the realm of AMD blowing our one chance to clean up the cruft in x86 instruction encoding. It's hard to blame them, since every change is a case where the decoders can't share transistors. And before Intel adopted x86-64, it wasn't even clear that it would catch on. AMD didn't want to burden their CPUs with hardware nobody used if AMD64 didn't catch on.
But still, there are so many small things: setcc could have changed to 32bits. (Usually you have to use xor-zero / test / setcc to avoid false dependencies, or because you need a zero-extended reg). Shift could have unconditionally written flags, even with zero shift count (removing the input data dependency on eflags for variable-count shift for OOO execution). Last time I typed this list of pet peeves, I think there was a third one... Oh yeah, bt / bts etc. with memory operands has the address dependent on the upper bits of the index (bit string, not just bit within a machine word).
bts instructions are very useful for bit-field stuff, and are slower than they need to be so you almost always want to load into a register and then use that. (It's usually faster to shift/mask to get an address yourself, instead of using 10 uop bts [mem], reg on Skylake, but it does take extra instructions. So it made sense on 386, but not on K8). Atomic bit-manipulation has to use the memory-dest form, but the locked version needs lots of uops anyway. It's still slower than if it couldn't access outside the dword it's operating on.
Please see the nice article by Abrash, Michael, published in Dr. Dobb's Journal March 1991 v16 n3 p16(8): http://archive.gamedev.net/archive/reference/articles/article369.html
The summary of the article is the following:
Optimizing code for 8088, 80286, 80386 and 80486 microprocessors is
difficult because the chips use significantly different memory
architectures and instruction execution times. Code cannot be
optimized for the 80x86 family; rather, code must be designed to
produce good performance on a range of systems or optimized for
particular combinations of processors and memory. Programmers must
avoid the unusual instructions supported by the 8088, which have lost
their performance edge in subsequent chips. String instructions
should be used but not relied upon. Registers should be used rather
than memory operations. Branching is also slow for all four
processors. Memory accesses should be aligned to improve
performance. Generally, optimizing an 80486 requires exactly the
opposite steps as optimizing an 8088.
By "unusual instructions supported by the 8088" the author also means "loop":
Any 8088 programmer would instinctively replace: DEC CX JNZ LOOPTOP
with: LOOP LOOPTOP because LOOP is significantly faster on the 8088.
LOOP is also faster on the 286. On the 386, however, LOOP is actually
two cycles slower than DEC/JNZ. The pendulum swings still further on
the 486, where LOOP is about twice as slow as DEC/JNZ--and, mind you,
we're talking about what was originally perhaps the most obvious
optimization in the entire 80x86 instruction set.
This is a very good article, and I highly recommend it. Even though it was published in 1991, it is surprisingly highly relevant today.
But this article just gives advices, it encourages to test execution speed and choose faster variants. It doesn’t explain WHY some commands become very slow, so it doesn’t fully address your question.
The answer is that earlier processors, like 80386 (released in 1985) and before, executed instructions one-by-one, sequentially.
Later processors have started to use instruction pipelining – initially, simple, for 804086, and, finally, Pentium Pro (released in 1995) introduced radically different internal pipeline, calling it the Out Of Order (OOO) core where instructions were transformed to small fragments of operations called micro-ops or µops, and then all micro-ops of different instructions were put to a large pool of micro-ops where they were supposed to execute simultaneously as long as they do not depend on one another. This OOO pipeline principle is still used, almost unchanged, on modern processors. You can find more information about instruction pipelining in this brilliant article: https://www.gamedev.net/resources/_/technical/general-programming/a-journey-through-the-cpu-pipeline-r3115
In order to simplify chip design, Intel decided to build processors in such a way that one instructions did transform to micro-ops in a very efficient way, while others are not.
Efficient conversion from instructions to micro-ops requires more transistors, so Intel have decided to save on transistors at a cost of slower decoding and execution of some “complex” or “rarely-used” instructions.
For example, the “Intel® Architecture Optimization Reference Manual” http://download.intel.com/design/PentiumII/manuals/24512701.pdf mentions the following: “Avoid using complex instructions (for example, enter, leave, or loop) that generally have more than four µops and require multiple cycles to decode. Use sequences of simple instructions instead.”
So, Intel somehow have decided that the “loop” instruction is “complex”, and, since then, it became very slow. However, there is no official Intel reference on instruction breakdown: how many micro-ops each instruction produces, and how many cycles are required to decode it.
You can also read about The Out-of-Order Execution Engine
in the "Intel® 64 and IA-32 Architectures Optimization Reference Manual"
http://www.intel.com/content/dam/www/public/us/en/documents/manuals/64-ia-32-architectures-optimization-manual.pdf section the 2.1.2.
Is there a script available for post processing some objdump --disassemble output to annotate with cycle counts? Especially for the ARM family. Most of the time this would only be a pattern match with a table lookup for the count. I guess annotations like +5M for five memory cycles might be needed. Perl, python, bash, C, etc are fine. I think this can be done generically, but I am interested in the ARM, which has an orthogonal instruction set. Here is a thread on the 68HC11 doing the same thing. The script would need an CPU model option to select the appropriate cycle counts; I think these counts already exist in the gcc machine description.
I don't think there is an objdump switch for this, but RTFM would be great.
Edit: To clarify, assumptions such as best case memory sub-system as will be the case when the code executes from cache are fine. The goal is not a 100% accurate cycle count as per some running machine. It is possible to get a reasonable estimate, otherwise compiler design would be impossible.
As DWelch points out, a simple running total is not possible with deep pipelined architecture, like more recent Cortex chips. The objdump post processing would have to look at surrounding opcodes. A gcc plug-in is more likely to be able to accomplish this and as that is new (4.5+), I don't think such a thing exists. A script for the ARM926 is certainly possible and fairly simple.
The memory latency doesn't matter. The memory controller is like another CPU. It is doing it's business while the CPU is doing arithmetic, etc. A good/well tuned algorithm will parallel the memory accesses with the computations. By counting loads/store and cycles you can determine how much parallelism is accomplished, when you actively profile with a timer. The pipeline is significant due to interlocks between registers, but a cycle count for basic blocks can reliably be calculated and used even on modern ARM processors; this is too complex for a simple script.
Cycle counts are not something that can be assessed by looking at the instruction alone on a modern high end ARM. There is a lot of runtime state that affects the real world retirement rate of an instruction. Does the data it needs exist in the cache? Does the instruction have any dependencies on previous instruction results? If so, what latencies does the forwarding unit remove? How full is the load/store buffer? What kind of memory mapping is it touching? How full are the processor pipelines that this instruction needs? Are there synchronizing instructions in the stream? Has speculation brought forward some data it depends on? What is the state of the register renamer? Have conditional instructions been filling the pipeline or was the decoder smart enough to skip them completely? What are the ratios between the core clock and the bus and memory clocks? What's the size of the branch prediction table?
Without a full processor simulation all you can get are guesses. Whether those numbers are meaningful to you depends on what you are trying to accomplish with them.
There is an online tool which estimates cycle counts on Cortex-A8. However, this CPU is quite old, and programs optimized for it might be suboptimal on newer CPUs.
AFAIK ARM also provides Cortex-A9 and Cortex-A5 cycle-accurate emulators in their RVDS software, but it is quite expensive.
Assume I have two implementations of the same algorithm in assembly. I would like to know by examining the two snippets codes which one is faster.
The parameters I thought one might take into account are: number of op-codes, number of branches, number of function frames.
My questions are:
Can I assume each opcode execution is one cycle ?
What is the overhead of branch which break the pipeline ?
What are the effects and overhead of calling a function ?
Is there a difference in the analysis between ARM and x86 ?
The question is theoretical since I have two implementations; one 130 instructions long and one is 184 instructions long.
And I would like to know if it is definitely true to say the 130 instructions long snippet is faster than the 184 instructions long implementation?
"BETTER == FASTER"
Without wanting to be flippant, the answers are
no
that depends on your hardware
that depends on your hardware
yes
You would really need to test things on your target hardware, or have a simulator that understands your hardware fully, in order to answer your question the way you meant to...
For the last part of your question, you need to define "better"…better.
Since you asked about a Cortex A9, the data sheet has instruction cycle counts in appendix B. These counts generally assume that the memory bus is fast enough to keep the CPU busy. In reality this is rarely the case. Many video/audio algorithms will have a big win in how they access memory.
One cycle per op
Of course you can't assume this if you want an exact count. However, if you are deciding which algorithm to choose, you can get a feel for the best algorithm by looking at the instructions in the inner loop. Here, your cache should allow the code to execute as per the instruction counts in the data sheet. If the counts are close, then you probably need to look at each instruction. Load/stores are more expensive and usually multiples, etc. Some algorithms, especially crytographic, will have big wins by using assembler that doesn't map well to C. For example, clz, ror, using the carry for multi-word arithmetic, etc.
Branch overhead
Look in Appendix B, or whatever data sheet has cycle counts for your processor. For an ARM926 it is about 3 cycles. The compiler only generates two conditional opcodes in a row to avoid branching, otherwise, it branches. If the algorithm is large, the branch may disrupt the cache. A hard answer depends on your CPU, cache, and memory. According to the Cortex A9 datasheet (B.5), there is only one cycle overhead to a fixed branch.
Function overhead
This is much the same as the branch overhead. However, the compiler will also have an influence. noted by Jim Does it cache align functions. Does the compiler perform leaf function optimizations, etc. With modern gcc versions, if all the functions are static, the compiler will generally in-line when it is advantageous. If the algorithms are particularly large, a register spill may be advantageous. However, with your example of 130/184 instructions, this seems unlikely. The compiler options will obviously effect the overhead. You can use objdump -S to examine the prologue/epilogue and then determine the number of cycles for your hardware.
ARM verus x86
Of course there is a technical difference in the cycle counts. The CISC x86 also has variable instruction size. This complicates the analysis. It is slightly easier on the ARM.
Normally, you want to ball park things and then actually run them with a profiler. The estimates can help guide development of the algorithms. Loop/memory tuning, etc for your hardware. Something like instruction emulation, page or alignment faults, etc may be dominant and make all the cycle count analysis meaningless. If the algorithm is in user space, per-emption, may negate cache wins from run to run. It is possible that one algorithm will work better in a little loaded system and the other will work better under a higher load.
A note on cycle counts
See the post-process objdump for some complications in getting cycle counts. Basically a typical CPU is several phases (a pipe line) and different conditions can cause stalls. As CPU's become more complex, the pipe line typically gets longer, meaning there are more conditions or phases which can stall. However, cycle count estimates can be helpful in guiding development of an algorithm and evaluating them. Things like memory timing or branch prediction can be just as important, depending on the algorithm. Ie, cycle counts are not completely useless, but they are not complete either. Profiling should confirm actual algorithm times. If they diverge, instruction re-ordering, pre-fetching and other techniques may bring them closer. The fact that cycle counts and active profiling diverge can be helpful in itself.
It is definitely not true to say that the 130 instruction code is faster than the 184 instruction code. it is very easy to have 1000 instructions run faster than 100 and vice versa on either of these platforms.
1 Can I assume each opcode execution is one cycle ?
Start by looking at the advertised mips/mhz, although a marketing number it gives a rough idea of what is possible. If the number is greater than one then more than one instruction per clock is possible.
2 What is the overhead of branch which break the pipeline ?
Anywhere from absolutely no affect to a very dramatic affect, on either system. one clock to hundreds are the potential penalty.
3 What are the effects and overhead of calling a function ?
Depends heavily on the function, and the function calling the function. Depending on the calling convention you might have to save registers to the stack, or rearrange the contents of registers to prepare for the parameters for the function to be called. If passing a struct by value a copy of the struct may need to be made on the stack, the bigger the struct passed the bigger the copy. once in the function a stack frame may need to be prepared, etc, etc. There are many factors involved. This question and answer are also independent of platform.
4 Is there a difference in the analysis between ARM and x86 ?
yes and no, both systems use all the modern tricks of pipelining, branch prediction, etc to keep the mips/mhz up. ARM is going to give a better mips per mhz than x86, x86 being variable instruction length might give more instructions per unit cache. How you analyze the cache, and memory and peripheral systems in the systems side of the analysis is roughly the same. The comparison of the instructions and core are similar and different depending on what aspects you are analyzing. The arm is not microcoded, the x86 likely is so you dont really see how many registers there really are, things like that. at the same time the x86 you can get a better look at the memory system with the arm, since they are generally not system on a chip. Depending on what ARM chip you buy you may lose a lot of the visibility in the boundaries of the chip, might not see all the memory and peripheral busses, for example. (x86 is changing that by putting pcie on chip now for example) in the case of something in the cortex-a class you mentioned you would have similar edge of chip visibility as those would use larger/cheaper dram based memory off chip rather than microcontroller like on chip resources.
Bottom line your final question:
"And I would like to know if it is definitely true to say the 130 instructions long snippet is faster than the 184 instructions long implementation?"
It is definitely NOT TRUE to say the 130 instruction snippet is faster than the 184 instruction snippet. It might be faster it might be slower and it might be about the same. With a lot more information we might be able to make a pretty good statement or it may still be non-deterministic. it is easy to choose 100 instructions that execute faster than 1000 instructions and likewise easy to choose 1000 instructions that execute faster than 100 instructions (even if I were to add no branching and no loops, just linear execution)
Your question is almost entirely meaningless: It probably depends on your input.
Most CPUs have something resembling a branch misprediction penalty (e.g. traditional ARM which throws away an instruction fetch/decode on any taken branch, IIRC). ARM and x86 also allow conditional execution, which can be faster than branching. If either of these are dependent on input data, then different inputs will follow different code paths.
Perhaps one version heavily uses conditional execution, which is wasteful when the condition is false. Perhaps another was compiled using some profiling information that performs no branches (except the return at the end) for a specific case. There are many, many reason why a compiler can take the same source and produce an "optimized" output which is faster for one input and slower for another.
Many optimizations have this characteristic — for example, aligning the start of a loop to 16 bytes helps on some processors, but not when the loop is only executed once.
Some text book answer to this question from Cortex
™
-A Series Programmer’s Guide, chapter 17.
Although cycle timing information can be found in the Technical Reference Manual (TRM) for the processor that you are using, it is very difficult to work out how many cycles even a trivial piece of code will take to execute. The movement of instructions through the pipeline is dependent on the progress of the surrounding instructions and can be significantly affected by memory system
activity. Pending loads or instruction fetches which miss in the cache can stall code for tens of cycles. Standard data processing instructions (logical and arithmetic) will take only one or two cycles to execute, but this does not give the full picture. Instead, we must use profiling tools, or the system performance monitor built-in to the processor, to extract useful information about performance.
Also read under 17.4 Cortex-A9 micro-architecture optimizations which answers your question very very much.