For the function in c, system(), would it affect the hardware counters if you are trying to see how that command you ran performed
For example lets say im using the Performance API(PAPI) and the program is a precompiled matrix multiplication application
PAPI_start_counters();
system("./matmul");
PAPI_read_counters();
//Print out values
PAPI_stop_counters();
I am obviously missing a bit but what I am trying to find out is it is possible, through the use of said counters to get the performance of a program im running.
from my tests I would get wild numbers like the ones below. they are obviously wrong, just want to find out why
Total Cycles =========== 140733358872510
Instructions Completed =========== 4203968
Floating Point Instructions =========== 0
Floating Point Operations =========== 4196867
Loads =========== 140733358872804
Stores =========== 4204037
Branches Taken =========== 15774436
system() is a very slow function in general. On Linux, it spawns /bin/sh (forking and executing a full shell process), which parses your command, and spawns the second program. Loading these two programs requires loading the code to memory, initializing all their libraries, executing startup code, etc. Only then will the program code actually start executing.
Because of the unpredictability of disk access and Linux process scheduling, timing system() calls has a very high inherent variability. Therefore, you won't get accurate results even if you use a high-performance counter.
The better solution would be to compile the target program as a library instead. Load it before initializing your counters, then just execute the main function from the library. That way, all the code executes in your process, and you have negligible startup time. Your performance numbers will be much more precise this way.
Do you have access to the code of matmul? If so, it's much more precise to instrument and measure only the code you're interested in. That means you wrap only those instructions (or C statements) in counters that you want to measure.
For more information see:
Related discussion here
Intel® Performance Counter Monitor here
Performance measurements with x86 RDTSC instruction here
As stated above, measuring using PAPI to wrap system() invocations carries way too much process overhead to give you any idea of how fast your math code is actually running.
The numbers you are getting are odd, but not necessarily wrong. The huge disparity between the instructions completed and the cycles probably indicate that the executable "matmul" is doing a lot of waiting for external processes (e.g. disk I/O) to complete. I do not know the specifics of the msg FP Instructions and FP ops, but if they are displaying those values differently PAPI has a reason.
What is interesting is that the loads and cycles are obviously connected as well as instructions/fp ops and stores.
I would have to know about the internals of "matmul" in order to give you a better description.
Related
I am wondering if it is possible to force a cache flush within c using linux x86. I have read several answers answering how to do this within the shell or using asm/cache.h (requiring me to write a linux module...)
I am using the PAPI library which allows me to get very close to the exact number of clock cycles that a given block of code takes to execute. However, since I want to time some extremely short functions I need to run the functions many times for accurate statistics (the timing function call takes longer than the code within the blocks takes to execute). By running the code multiple times the cache is speeding up the execution of successive calls of the same block of code and I would like to prevent this!
I don't Know any standard way to do this other than loading other thing to the cache. My usual workaround is simply process something large enough to "cool down" the cache, say a matrix multiplication.
I have an assignment where I am analyzing the runtime of various sorting algorithms. I have written the code but I think it's an unfair comparison.
My code basically grabs the the clock time before and after the sorting is finished to compute the elapsed time. However, what if the OS decides to interrupt more frequently during the runtime of a specific sorting algorithm, or if it rather decides that some other background application should be given more of the time domain when it's thread comes back up?
I am not a CS major so I may not be entirely correct here, but from what I've read previously I was concerned this might have an impact on the results.
I also realize that if OS scheduling is suspended and the program hangs then there might be a serious problem; I am just wondering if it possible.
Normally, there's no real reason for it. The scheduler will slightly increase the execution time, but if the code runs for a few seconds, the change will be tiny.
So unless you're running heavy applications on the same computer, the amount of noise this will add to your tests is negligible.
In Linux, you can use isolcpus parameter to mark CPUs that won't be used by the scheduler. You can find information here. I'm not sure what's the minimal kernel version.
If you use it, you'll need to use sched_setaffinity, to put your theread on an isolated CPU, because the scheduler won't put it there.
It is not possible, not in user space code. Otherwise, any malicious process could steal the CPU from others.
If you want precise time counting for your process only, I suggest using time command. You can read about it here: What do 'real', 'user' and 'sys' mean in the output of time(1)?
Quick answer: you are most likely interested in user time, assuming your code doesn't make a heavy use of syscalls (which would be rather strange for a sorting algorithm)
On an up-to-date POSIX system (basically Linux) you can use clock_gettime with CLOCK_PROCESS_CPUTIME_ID or CLOCK_THREAD_CPUTIME_ID if you make sure the process doesn't migrate between CPUs (you can set its affinity for example).
The difference in times returned by clock_gettime with those arguments results in exact time the process/thread spent executing. Only pitfall as I mentioned is process migration as the man page says:
The CLOCK_PROCESS_CPUTIME_ID and CLOCK_THREAD_CPUTIME_ID clocks are realized on many platforms using timers from the CPUs (TSC on i386, AR.ITC on Itanium). These registers may differ between CPUs and as a consequence these clocks may return bogus results if a process is migrated to another CPU.
This means that you don't really need to suspend all other processes just to measure the execution time of your program.
I've been searching for a Linux sampling profiler, and callgrind has come the closest to showing useful results. However the overhead is estimated at 20--100x slower than normal. Additionally, I'm only interested in time spent per function (with particular emphasis on blocking calls such as read() and write(), which no other profiler will faithfully display).
Is there a way to turn off excess options, so that just the minimum data is recorded for generating times spent in various call stacks?
Does callgrind's cachegrind heritage imply that excess stuff is being done with regards to cache profiling etc?
I assume callgrind operates like a debugger. Can this be adjusted to sample the process at intervals, rather than every single instruction?
3) Callgrind is working like dynamic translator, which instruments orginal code with counting instrument code. Instrumenting is done for each memory access instruction in the code (for cache simulation), and (i suggest) for each jmp-like instruction to track exec. count of every basic block.
I have a small sampling profiler, which acts just like debugger; It does inject a setitimer() profiling counter into the application and then it does intercept all SIGALRM and prints current $eip value.
There were some sampling profilers with setitimer approach earlier, also there is a profil()for something like. This is used by glibc/gmon/gmon.c and gprof -p (to be exact, by gcc -pg). profil() function is able to profile single contonous code fragment with sampling a virtual cpu time each 1 or 10 millisecond. There is also sprofil() function.
Check also LD_PRELOAD=/lib/libpcprofile.so PCPROFILE_OUTPUT=output.file - but I don't know does it work or how it work
For numbered questions:
2) "Callgrind is an extension to Cachegrind. It provides all the information that Cachegrind does, plus extra information about callgraphs." - So it can provide any stuff that is in cachegrind, but also it allow user to turn off cache simulation: --simulate-cache=no (it is the default value)
For speed: According to http://www.valgrind.org/docs/manual/nl-manual.html - manual of Nul valgrind tool (aka nulgrind), which does no additional instrumentation, slowdown is 5 times. It is because program is dynamically translated by valgrind itself. So, there can be no tool for valgrind, which can work faster then nulgrind.
Have you tried gprof ? It does not have the big overhead as valgrind do.
Try using Zoom from RotateRight. It has a "Thread Time" configuration that samples all threads in a single process whether they are running or blocked.
I have written a program in C. Its a program created as result of a research. I want to compute exact CPU cycles which program consumes. Exact number of cycles.
Any idea how can I find that?
The valgrind tool cachegrind (valgrind --tool=cachegrind) will give you a detailed output including the number of instructions executed, cache misses and branch prediction misses. These can be accounted down to individual lines of assembler, so in principle (with knowledge of your exact architecture) you could derive precise cycle counts from this output.
Know that it will change from execution to execution, due to cache effects.
The documentation for the cachegrind tool is here.
No you can't. The concept of a 'CPU cycle' is not well defined. Modern chips can run at multiple clock rates, and different parts of them can be doing different things at different times.
The question of 'how many total pipeline steps' might in some cases be meaningful, but there is not likely to be a way to get it.
Try OProfile. It use various hardware counters on the CPU to measure the number of instructions executed and how many cycles have passed. You can see an example of it's use in the article, Memory part 7: Memory performance tools.
I am not entirely sure that I know exactly what you're trying to do, but what can be done on modern x86 processors is to read the time stamp counter (TSC) before and after the block of code you're interested in. On the assembly level, this is done using the RDTSC instruction, which gives you the value of the TSC in the edx:eax register pair.
Note however that there are certain caveats to this approach, e.g. if your process starts out on CPU0 and ends up on CPU1, the result you get from RDTSC will refer to the specific processor core that executed the instruction and hence may not be comparable. (There's also the lack of instruction serialisation with RDTSC, but in this context here, I don't think that's so much of an issue.)
Sorry, but no, at least not for most practical purposes -- it's simply not possible with most normal OSes. Just for example, quite a few OSes don't do a full context switch to handle an interrupt, so the time spent servicing a interrupt can and often will appear to be time spent in whatever process was executing when the interrupt occurred.
The "not for practical purposes" would indicate the possibility of running your program under a cycle accurate simulator. These are available, but mostly for CPUs used primarily in real-time embedded systems, NOT for anything like a full-blown PC. Worse, they (generally) aren't for running anything like a full-blown OS, but for code that runs on the "bare metal."
In theory, you might be able to do something with a virtual machine running something like Windows or Linux -- but I don't know of any existing virtual machine that attempts to, and it would be decidedly non-trivial and probably have pretty serious consequences in performance as well (to put it mildly).
I am trying to understand how the linux syscall sched_setaffinity() works. This is a follow-on from my question here.
I have this guide, which explains how to use the syscall and has a pretty neat (working!) example.
So I downloaded the Linux 2.6.27.19 kernel sources.
I did a 'grep' for lines containing that syscall, and I got 91 results. Not promising.
Ultimately, I'm trying to understand how the kernel is able to set the instruction pointer for a specific core (or processor.)
I am familiar with how single-core-single-thread programs work. One might issue a 'jmp foo' instruction, and this basically sets the IP to the memory address of the 'foo' label. But when one has multiple cores, one has to say "fetch the next instruction at memory address foo, and set the instruction pointer for core number 2 to begin execution there."
Where, in the assembly code, are we specifying which core performs that operation?
Back to the kernel code: what is important here? The file 'kernel/sched.c' has a function called sched_setaffinity(), but returns type "long" - which is inconsistent with its manual page. So what is important here? Which of these modules shows the assembly instructions issued? What module is reading the 'task_struct', looking at the 'cpus_allowed' member, and then translating that into an instruction? (I've also thumbed through the glibc source - but I think it just makes a call to the kernel code to accomplish this task.)
sched_setaffinity() simply tells the scheduler which CPUs is that process/thread allowed to run on, then calls for a re-schedule.
The scheduler actually runs on each one of the CPUs, so it gets a chance to decide what task to execute next on that particular CPU.
If you're interested in how you can actually call some code on other CPUs, I suggest you take a look at smp_call_function_single(). In case we want to call something on another CPU, this calls generic_exec_single(). The latter simply adds the function to the target CPU's call queue and forces a reschedule through some IPI stuff (if the queue was empty).
Bottom line is: there no actual SMP variant of the _jmp_ instruction. Instead, code running on other CPUs cooperates in order to accomplish the task.
I think the thing you are not understanding is that the kernel is running on all the CPU cores. At every timer interrupt (~1000 per second), the scheduler runs on each CPU and chooses a process to run. There is no one CPU that somehow tells the others to start running a process. sched_setaffinity() works by just setting flags on the process. The scheduler reads these flags and will not run that process on its CPU if it is set not to.
Where, in the assembly code, are we specifying which core performs that operation?
There is no assembly involved here. Every task (thread) is assigned to a single CPU (or core in your terms) at a time. To stop running on a given CPU and resume on another, the task has to "migrate" (also this). When a task migrates from one CPU to another, the scheduler picks the CPU which is more idle among the CPUs allowed by sched_setaffinity().
There is no magic assembly instructions issued. The kernel has a more low-level view of the hardware, each CPU is a separate object, very different than how it looks like for user-space processes (in user-space, CPUs are almost invisible).
Check this out: B Operating System Programming Guidelines