automated assembly loop level profiling

Does anyone know any assembly loop level profiler?

I have been using gprof but gprof hides loops and it is function level profiling, yet to optimize my code i want something to go to the loop level. I want it to be automated and just give me the output like gprof. I was recommended to go to dtrace yet I have no idea were to start. anyone can direct me in anyway? for example

main:

pushl   %ebp     
movl    %esp, %ebp     
subl    $16, %esp     
movl    $5000000, -4(%ebp)     
movl    $0, -12(%ebp)     
movl    $0, -8(%ebp)    
jmp .L2 

.L3:   

 movl    -8(%ebp), %eax    
 addl    %eax, -12(%ebp)    
 addl    $1, -8(%ebp) 

.L2:    

movl    -8(%ebp), %eax    
cmpl    -4(%ebp), %eax   开发者_运维知识库 
jl  .L3     
movl    $0, %eax    
leave     ret 

for example in gprof it would say main executed 1 time and foo executed 100 times. yet I want to know if L2, or L3 executed 1M times then my concentration on optimizing would be here. if my question is vague please ask me to explain more Thanks

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It depends on what OS you are using, but for this kind of profiling you generally want to use a sampling profiler rather than an instrumented profiler, e.g.

• Linux: Zoom
• Mac OS X: Instruments
• Windows: VTune

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I suggest using Callgrind (one of the Valgrind tools, and usually installed with it). This can gather statistics on a much more fine-grained level, and the kcachegrind tool is very good for visualising the results.

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If you're on Linux, Zoom is an excellent choice.

If you're on Windows, LTProf might be able to do it.

On any platform, the low-tech method random-pausing can be relied on.

Don't look for how many times instructions are executed. Look for where the program counter is found a large fraction of the time. (They're not the same thing.) That will tell you where to concentrate your optimization efforts.

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KCachegrind gives profiling information for each line of source code (see this screenshot), and this includes CPU time, cache misses, etc... It saved my day a couple of times.

However running the code inside the profiler is extremely slow (tens of times slower than native).