I am writing a video player using ffmpeg (Windows only, Visual Studio 2015, 64 bit compile).
With common videos (up to 4K # 30FPS), it works pretty good. But with my maximum target - 4K # 60FPS, it fails. Decoding still is fast enough, but when it comes to YUV/BGRA conversion it is simply not fast enough, even though it's done in 16 threads (one thread per frame on a 16/32 core machine).
So as a first countermeasure I skipped the conversion of some frames and got a stable frame rate of ~40 that way. Comparing the two versions in Concurrency Visualizer, I found a strange issue I don't know the reason of.
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Here's an image of the frameskip version:
You see that the conversion is pretty quick (average roughly ~35ms)
Thus, as multiple threads are used, it also should be quick enough for 60FPS, but it isn't!
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The image of the non-frameskip version shows why:
The conversion of a single frame has become ten times slower than before (average roughly ~350ms). Now a heavy workload on many cores would of course cause a minor slowdown per core due to reduced turbo - let's say 10 or 20%. But never an extreme slowdown of ~1000%.
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Interesting detail is, that the stack trace of the non-frameskip version shows some system activity I don't really understand - beginning with ntoskrnl.exe!KiPageFault+0x373. There are no exceptions, other error messages or such - it just becomes extremely slow.
Edit: A colleague just told me that this looks like a memory problem with paged-out memory at first glance - but my memory utilization is low (below 1GB, and more than 20GB free)
Can anyone tell me what could be causing this?
This is probably too old to be useful, but just for the record:
What's probably happening is that you're allocating 4k frames over and over again in multiple threads. The windows allocator really doesn't like that access pattern.
The malloc itself will not show up in the profiler, since only when the memory is actually accessed, will the OS fetch the pages. This shows up as ntoskrnl.exe!KiPageFault and gets attributed to the function first accessing the new memory.
Solutions include:
Using a different allocator (e.g. tbb_malloc, mimalloc, etc.)
Using your own per-thread or per process frame pool. ffmpeg does something similar internally, maybe you can just use that.
Related
We've been using (lib)gstreamer to do some RTSP streaming stuff. So far, so good. It works and we got it all up an running. However, I noticed that after gst_init being called, memory usage increases a lot. I reproduced this by making a very simple program that does nothing else.
So, before the call to gst_init, the memory usage is around 6 MB, and then right after it, it's like 53 MB.
Does anyone know what is causing this large memory usage increase and how we might prevent it?
I've checked which extra modules (libraries) are being loaded from gst_init and that sums up to like 5 MB, so that can't be the issue. I also checked the gstreamer source code, but couldn't really find what was causing the issue.
The memory usage is just too much.
EDIT:
Because someone asked it in the questions. It's going to run on a security system. The hardware is usually old and slow. With slow I mean, usually still running XP, 2-4 GB memory, 32 bit and not even an i3. It runs 24h a day and there are more applications running on the same system that are using the limited amount of memory. The less memory an application uses, the more we have for others.
I've been investigating an issue in my DirectX 11 C++ application for over a week now, and so I'm turning to the good people on StackOverflow for any insight that may help me track this one down.
My application will run mostly at 60-90 frames per second, but every few seconds I'll get a frame that takes around a third of a second to finish. After much investigation, debugging, and using various code profilers, I have narrowed it down to calls to the DirectX API. However, from one slow frame to the next, it is not always the same API call that causes the slowdown. In my latest run, the calls that stall (always for about a fifth of a second) are
ID3D11DeviceContext:UpdateSubresource
ID3D11DeviceContext:DrawIndexed
IDXGISwapChain:Present
Not only is it not the same function that stalls, but each of these functions (mainly the first two) the slow call may be from various places in my code from one to the next.
According to multiple profiling tools and my own high resolution timers I placed in my code to help measure things, I found that this "hiccup" would occur at consistent intervals of just under 3 seconds (~2.95).
This application collects data from external hardware and uses DirectX to visualize that data in real time. While the application is running, the hardware may be idle or running at various speeds. The faster the hardware goes the more data is collected and must be visualized. I point this out because it may be useful when considering some of the characteristics of this bug:
The long frames don't occur while the hardware is idle. This makes sense to me because the software just has to redraw data it already has and doesn't have to transfer new data over to the GPU.
However, the long frames occur at these consistent 3 second intervals regardless of the speed the hardware is running. So even if my application is collecting twice the amount of data per second, the frequency of the long frames doesn't change.
The duration of these long frames is very consistent. Always between 0.25 and 0.3 seconds (I believe it is the slow call to the DirectX API that is consistent, so any variation on the overall frame duration is external to that call).
While field testing last week (when I first discovered the issue), I noticed that on a couple runs of the application, after a long time (probably 20 minutes or more) of continuous testing without interacting much with the program aside from watching it, the hiccup would go away. The hiccup would come back if we interacted with some features of the application or restarted the program. Doesn't make sense to me, but almost like the GPU "figured out" and fixed the issue but then reverted back when we changed up the pattern of work it had been doing previously. Unfortunately the nature of our hardware makes it difficult for me to replicate this in a lab environment.
This bug is occurring consistently on two different machines with very similar hardware (dual GTX580 cards). However, in recent versions of the application, this issue did not occur. Unfortunately the code has undergone many changes since then so it would be difficult to pinpoint what specific change is causing the issue.
I considered the graphics driver, and so updated to the latest version, but that didn't make a difference. I also considered the possibility that some other change was made to both computers, or possibly an update to software running on both of them, could be causing issues with the GPU. But I can't think of anything other than Microsoft Security Essentials that is running on both machines while the application runs, and I've already tried disabling it's Real-Time Protection feature to no avail.
While I would love for the cause to be an external program that I can just turn off, ultimately I worry that I must be doing something incorrectly/improperly with the DirectX API that is causing the GPU to have to make adjustments every few seconds. Maybe I am doing something wrong in the way I update data on the GPU (since the lag only happens when I'm collecting data to display). Then the GPU stalls every few seconds and whatever API function that happens to get called during a stall can't return as fast as it normally would?
Any suggestions would be greatly appreciated!
Thanks,
Tim
UPDATE (2013.01.21):
I finally gave in and went searching back through previous revisions of my application until I found a point where this bug wasn't occurring. Then I went revision by revision until I found exactly when the bug started happening and managed to pinpoint the source of my issue. The problem started occurring after I added an 'unsigned integer' field to a vertex type, of which I allocate a large vertex buffer. Because of the size of the vertex buffer, this change increased the size 184.65 MB (1107.87 MB to 1292.52). Because I do in fact need this extra field in my vertex structure, I found other ways to cut back on overall vertex buffer size, and got it down to 704.26 MB.
My best guess is that the addition of that field and the extra memory it required caused me to exceed some threshold/limit on the GPU. I'm not sure if it was an excess of total memory allocation, or an excess of some limit to a single vertex buffer. Either way, it seems that this excess caused the GPU to have to do some extra work every few seconds (maybe communicating with the CPU) every few seconds, and so my calls to the API had to wait on this. If anyone has any information that would clarify the implications of large vertex buffers, I'd love to hear it!
Thanks to everyone who gave me their time and suggestions.
1) Try turning of VSYNC
2) Are you allocating/deallocating large chunks of memory? Try to alloc memory at beginning of program and don't dealloc it, simply overwrite it (which is probably what you're doing with updatesubresource)
3) Put the interaction with the hardware device on a separate thread. After the device has completely finished passing data to your application, load it into the GPU. Do not let the device take control of the main thread. I suspect the device is blocking the main thread every so often, and I'm completely speculating but if you're you are copying data from the device to the GPU directly, the device is blocking occassionally and that causes the slowdown.
I just made some benchmarks for this super question/answer Why is my program slow when looping over exactly 8192 elements?
I want to do benchmark on one core so the program is single threaded. But it doesn't reach 100% usage of one core, it uses 60% at most. So my tests are not acurate.
I'm using Qt Creator, compiling using MinGW release mode.
Are there any parameters to setup for better performance ? Is it normal that I can't leverage CPU power ? Is it Qt related ? Is there some interruptions or something preventing code to run at 100%...
Here is the main loop
// horizontal sums for first two lines
for(i=1;i<SIZE*2;i++){
hsumPointer[i]=imgPointer[i-1]+imgPointer[i]+imgPointer[i+1];
}
// rest of the computation
for(;i<totalSize;i++){
// compute horizontal sum for next line
hsumPointer[i]=imgPointer[i-1]+imgPointer[i]+imgPointer[i+1];
// final result
resPointer[i-SIZE]=(hsumPointer[i-SIZE-SIZE]+hsumPointer[i-SIZE]+hsumPointer[i])/9;
}
This is run 10 times on an array of SIZE*SIZE float with SIZE=8193, the array is on the heap.
There could be several reasons why Task Manager isn't showing 100% CPU usage on 1 core:
You have a multiprocessor system and the load is getting spread across multiple CPUs (most OSes will do this unless you specify a more restrictive CPU affinity);
The run isn't long enough to span a complete Task Manager sampling period;
You have run out of RAM and are swapping heavily, meaning lots of time is spent waiting for disk I/O when reading/writing memory.
Or it could be a combination of all three.
Also Let_Me_Be's comment on your question is right -- nothing here is QT's fault, since no QT functions are being called (assuming that the objects being read and written to are just simple numeric data types, not fancy C++ objects with overloaded operator=() or something). The only activities taking place in this region of the code are purely CPU-based (well, the CPU will spend some time waiting for data to be sent to/from RAM, but that is counted as CPU-in-use time), so you would expect to see 100% CPU utilisation except under the conditions given above.
I am running some CPU-intensive Clojure code from within Intellij Idea (I don't think that's important - it seems to just spawn a process). According to both htop and top, it is using all 4 cores (well, 2 + hyperthreading) on my laptop. This is despite me not having any explicit parallelism in the code.
A little more detail: top shows a single process with ~380% CPU use, while htop shows a "parent" process and then 4 "children", each with 1/4 the time and ~100% CPU.
Is this normal? Or does it mean I have got something very wrong somewhere? The code involves many lazy sequences, but at its core modifies a mutable data structure (a mutable - not a Clojure data structure - hash that accumulates results). I am not using any explicit parallelism.
A significant amount of time is likely (I haven't profiled) spent in JCA/JCE (crypto lib) - I am using multiple AES ciphers in CTR mode, each as a stream of secure random bytes (code here), implemented as lazy seqs. Perhaps that is parallelized?
More random ideas: Could this be related to IO? I'm running on an encrypted SSD and this program is processing data from disk, so does a lot of reading. But htop shows system time as red, and these are green.
Sorry for such a vague question. I can post more info if required. This is Clojure 1.4 on 64bit Linux (JDK 1.7.0_05). The code being executed is here but it's pretty messy (more apologies) and spread across various files (most CPU time is spent in nearest-in-dump in the code there). Note - please don't waste time trying to run code to reproduce, as it expects a pre-existing data-dump to be on disk (which isn't in git).
debugger Running in the debugger (thanks, A-M) shows four threads (if I understand the debugger correctly), but only one is executing the program. They are labelled finalizer, main (the program), reference handler, and signal dispatcher. Finalizer + ref handler are in wait state; signal dispatcher has no frames available. I tentatively think this means the parallelism is at a lower level, perhaps in the crypto implementation?
Aha I think it's parallel GC (Java now has a concurrent collector). At the start, CPU use jumps way up when the actual process pauses (it prints out a regular tick). And since it's churning through lots of data it's generating a lot of short-lived objects (confirmed by using -XX:+UseSerialGC which reduces CPU use to 100%)
OK, I feel a bit dumb posting this as it now looks pretty obvious, but it seems to be parallel GC. I am processing a lot of data (sucking it in from an SSD) and generating lots of short-lived objects. And it appears that the JVM has parallel GC. See http://blog.ragozin.info/2011/12/garbage-collection-in-hotspot-jvm.html
It may also be a sign of a problem - What is going on with java GC? PermGen space is filling up? - which I will investigate tomorrow (I didn't mention it - although in retrospect I should have - but this is borderline running out of memory).
Update: Running with -XX:+UseSerialGC reduces the total CPU use to 100% (ie 1 core). But I didn't really mean that the two explanations above were exclusive, only that with better configuration and/or code I could reduce the amount of GC.
I have a program that loads a file (anywhere from 10MB to 5GB) a chunk at a time (ReadFile), and for each chunk performs a set of mathematical operations (basically calculates the hash).
After calculating the hash, it stores info about the chunk in an STL map (basically <chunkID, hash>) and then writes the chunk itself to another file (WriteFile).
That's all it does. This program will cause certain PCs to choke and die. The mouse begins to stutter, the task manager takes > 2 min to show, ctrl+alt+del is unresponsive, running programs are slow.... the works.
I've done literally everything I can think of to optimize the program, and have triple-checked all objects.
What I've done:
Tried different (less intensive) hashing algorithms.
Switched all allocations to nedmalloc instead of the default new operator
Switched from stl::map to unordered_set, found the performance to still be abysmal, so I switched again to Google's dense_hash_map.
Converted all objects to store pointers to objects instead of the objects themselves.
Caching all Read and Write operations. Instead of reading a 16k chunk of the file and performing the math on it, I read 4MB into a buffer and read 16k chunks from there instead. Same for all write operations - they are coalesced into 4MB blocks before being written to disk.
Run extensive profiling with Visual Studio 2010, AMD Code Analyst, and perfmon.
Set the thread priority to THREAD_MODE_BACKGROUND_BEGIN
Set the thread priority to THREAD_PRIORITY_IDLE
Added a Sleep(100) call after every loop.
Even after all this, the application still results in a system-wide hang on certain machines under certain circumstances.
Perfmon and Process Explorer show minimal CPU usage (with the sleep), no constant reads/writes from disk, few hard pagefaults (and only ~30k pagefaults in the lifetime of the application on a 5GB input file), little virtual memory (never more than 150MB), no leaked handles, no memory leaks.
The machines I've tested it on run Windows XP - Windows 7, x86 and x64 versions included. None have less than 2GB RAM, though the problem is always exacerbated under lower memory conditions.
I'm at a loss as to what to do next. I don't know what's causing it - I'm torn between CPU or Memory as the culprit. CPU because without the sleep and under different thread priorities the system performances changes noticeably. Memory because there's a huge difference in how often the issue occurs when using unordered_set vs Google's dense_hash_map.
What's really weird? Obviously, the NT kernel design is supposed to prevent this sort of behavior from ever occurring (a user-mode application driving the system to this sort of extreme poor performance!?)..... but when I compile the code and run it on OS X or Linux (it's fairly standard C++ throughout) it performs excellently even on poor machines with little RAM and weaker CPUs.
What am I supposed to do next? How do I know what the hell it is that Windows is doing behind the scenes that's killing system performance, when all the indicators are that the application itself isn't doing anything extreme?
Any advice would be most welcome.
I know you said you had monitored memory usage and that it seems minimal here, but the symptoms sound very much like the OS thrashing like crazy, which would definitely cause general loss of OS responsiveness like you're seeing.
When you run the application on a file say 1/4 to 1/2 the size of available physical memory, does it seem to work better?
What I suspect may be happening is that Windows is "helpfully" caching your disk reads into memory and not giving up that cache memory to your application for use, forcing it to go to swap. Thus, even though swap use is minimal (150MB), it's going in and out constantly as you calculate the hash. This then brings the system to its knees.
Some things to check:
Antivirus software. These often scan files as they're opened to check for viruses. Is your delay occuring before any data is read by the application?
General system performance. Does copying the file using Explorer also show this problem?
Your code. Break it down into the various stages. Write a program that just reads the file, then one that reads and writes the files, then one that just hashes random blocks of ram (i.e. remove the disk IO part) and see if any particular step is problematic. If you can get a profiler then use this as well to see if there any slow spots in your code.
EDIT
More ideas. Perhaps your program is holding on to the GDI lock too much. This would explain everything else being slow without high CPU usage. Only one app at a time can have the GDI lock. Is this a GUI app, or just a simple console app?
You also mentioned RtlEnterCriticalSection. This is a costly operation, and can hang the system quite easily, i.e. mismatched Enters and Leaves. Are you multi-threading at all? Is the slow down due to race conditions between threads?
XPerf is your guide here - watch the PDC Video about it, and then take a trace of the misbehaving app. It will tell you exactly what's happening throughout the system, it is extremely powerful.
I like the disk-caching/thrashing suggestions, but if that's not it, here are some scattershot suggestions:
What non-MSVC libraries, if any, are you linking to?
Can your program be modified (#ifdef'd) to run without a GUI? Does the problem occur?
You added ::Sleep(100) after each loop in each thread, right? How many threads are you talking about? A handful or hundreds? How long does each loop take, roughly? What happens if you make that ::Sleep(10000)?
Is your program perhaps doing something else that locks a limited resources (ProcExp can show you what handles are being acquired ... of course you might have difficulty with ProcExp not responding:-[)
Are you sure CriticalSections are userland-only? I recall that was so back when I worked on Windows (or so I believed), but Microsoft could have modified that. I don't see any guarantee in the MSDN article Critical Section Objects (http://msdn.microsoft.com/en-us/library/ms682530%28VS.85%29.aspx) ... and this leads me to wonder: Anti-convoy locks in Windows Server 2003 SP1 and Windows Vista
Hmmm... presumably we're all multi-processor now, so are you setting the spin count on the CS?
How about running a debugging version of one of these OSes and monitoring the kernel debugging output (using DbgView)... possibly using the kernel debugger from the Platform SDK ... if MS still calls it that?
I wonder whether VMMap (another SysInternal/MS utility) might help with the Disk caching hypothesis.
It turns out that this is a bug in the Visual Studio compiler. Using a different compiler resolves the issue entirely.
In my case, I installed and used the Intel C++ Compiler and even with all optimizations disabled I did not see the fully-system hang that I was experiencing w/ the Visual Studio 2005 - 2010 compilers on this library.
I'm not certain as to what is causing the compiler to generate such broken code, but it looks like we'll be buying a copy of the Intel compiler.
It sounds like you're poking around fixing things without knowing what the problem is. Take stackshots. They will tell you what your program is doing when the problem occurs. It might not be easy to get the stackshots if the problem occurs on other machines where you cannot use an IDE or a stack sampler. One possibility is to kill the app and get a stack dump when it's acting up. You need to reproduce the problem in an environment where you can get a stack dump.
Added: You say it performs well on OSX and Linux, and poorly on Windows. I assume the ratio of completion time is some fairly large number, like 10 or 100, if you've even had the patience to wait for it. I said this in the comment, but it is a key point. The program is waiting for something, and you need to find out what. It could be any of the things people mentioned, but it is not random.
Every program, all the time while it runs, has a call stack consisting of a hierarchy of call instructions at specific addresses. If at a point in time it is calculating, the last instruction on the stack is a non-call instruction. If it is in I/O the stack may reach into a few levels of library calls that you can't see into. That's OK. Every call instruction on the stack is waiting. It is waiting for the work it requested to finish. If you look at the call stack, and look at where the call instructions are in your code, you will know what your program is waiting for.
Your program, since it is taking so long to complete, is spending nearly all of its time waiting for something to finish, and as I said, that's what you need to find out. Get a stack dump while it's being slow, and it will give you the answer. The chance that it will miss it is 1/the-slowness-ratio.
Sorry to be so elemental about this, but lots of people (and profiler makers) don't get it. They think they have to measure.