How do I programatically find the maximum number of concurrent cuda threads or streaming multiprocessors on a device / nvidia graphics card? I know about warpSize, but there is no warpCount.
most answers on the internet concern themselves with looking up things from pdfs.
Have you tried checking their SDK samples , i think this sample is the one you want
Device Query
This does not only depend on the device but also on your code - e.g. things like the number of registers each thread uses or the amount of shared memory your block needs. I would suggest reading about occupancy.
Another thing I would note is that if your code relies on having a certain number of threads resident on the device (e.g. if you wait for several threads to reach some execution point) you are bound to face some race conditions and see your code hanging.
Related
Hi I am a newbie learning Direct 3D 12.
So far, I understood that Direct 3D 12 is designed for multithreading and I'm trying to make my own simple multithread demo by following the tutorial by braynzarsoft.
https://www.braynzarsoft.net/viewtutorial/q16390-03-initializing-directx-12
Environment is windows, using C++, Visual Studio.
As far as I understand, multithreading in Direct 3D 12 seems, in a nutshell, populating command lists in multiple threads.
If it is right, it seems
1 Swap Chain
1 Command Queue
N Command Lists (N corresponds to number of threads)
N Command Allocators (N corresponds to number of threads)
1 Fence
is enough for a single window program.
I wonder
Q1. When do we need multiple command queues?
Q2. Why do we need multiple fences?
Q3. When do we submit commands multiple times?
Q4. Does GetCPUDescriptorHandleForHeapStart() return value changes?
Q3 comes from here.
https://developer.nvidia.com/sites/default/files/akamai/gameworks/blog/GDC16/GDC16_gthomas_adunn_Practical_DX12.pdf
Purpose of Q4 is I thought of calling the function once and store the value for reuse, it didn't change when I debugged.
Rendering loop in my mind is (based on Game Loop pattern), for example,
Thread waits for fence value (eg. Main thread).
Begin multiple threads to populate command lists.
Wait all threads done with population.
ExecuteCommandLists.
Swap chain present.
Return to 1 in the next loop.
If I am totally misunderstanding, please help.
Q1. When do we need multiple command queues?
Read this https://learn.microsoft.com/en-us/windows/win32/direct3d12/user-mode-heap-synchronization:
Asynchronous and low priority GPU work. This enables concurrent execution of low priority GPU work and atomic operations that enable one GPU thread to consume the results of another unsynchronized thread without blocking.
High priority compute work. With background compute it is possible to interrupt 3D rendering to do a small amount of high priority compute work. The results of this work can be obtained early for additional processing on the CPU.
Background compute work. A separate low priority queue for compute workloads allows an application to utilize spare GPU cycles to perform background computation without negative impact on the primary rendering (or other) tasks.
Streaming and uploading data. A separate copy queue replaces the D3D11 concepts of initial data and updating resources. Although the application is responsible for more details in the Direct3D 12 model, this responsibility comes with power. The application can control how much system memory is devoted to buffering upload data. The app can choose when and how (CPU vs GPU, blocking vs non-blocking) to synchronize, and can track progress and control the amount of queued work.
Increased parallelism. Applications can use deeper queues for background workloads (e.g. video decode) when they have separate queues for foreground work.
Q2. Why do we need multiple fences?
All gpu work is asynchronous. So you can think of fences as low level tools to achieve the same result as futures/coroutines. You can check if the work has been completed, wait for work to complete or set an event on completion. You need a fence whenever you need to guarantee a resource holds the output of work (when resource barriers are insufficient).
Q4. Does GetCPUDescriptorHandleForHeapStart() return value changes?
No it doesn't.
store the value for reuse, it didn't change when I debugged.
The direct3d12 samples do this, you should know them intimately if you want to become proficient.
Rendering loop in my mind is (based on Game Loop pattern), for example,
That sounds okay, but I urge you to look at the direct3d12 samples and steal the patterns (and the code) they use there.
I am considering a programming project. Will run under Ubuntu or other Linux OS on a small board. Quad core x86 - N-Series Pentium. The software generates 8 fast signals; square wave pulse trains for stepper motor motion control of 4 axes. Step signals being 50-100 KHz maximum, but usually slower. Want to avoid jitter in these stepping signals (call it good fidelity), so that around 1-2us for each thread loop cycle would be a nice target. The program does other kinds of tasks, like read/write hard drive, Ethernet, continues update on the graphics display, keyboard. The existing Single core programs just can not process motion signals with this kind of timing and require external hardware/techniques to achieve this.
I have been reading other posts here, like on a thread running selected core, continuously. The exact meaning in these posts is "lose", not sure really what is meant. Continuous might mean testing every minute or ?????
So, I might be wordy, but it will clear I hope. The considered program has all the threads, routines, memory, shared memory all included. I am not considering that this program launches another program or service. Other threads are written in this program and launched when the program starts up. I will call this signal generating thread the FAST THREAD.
The FAST THREAD is to be launched to an otherwise "free" core. It needs to be the only thread that runs on the core. Hopefully, the OS thread scheduler component on that core can be "turned off", so that it does not even interrupt on that core to decide what thread runs next. In looking at the processor manual, Each core has a counter timer chip. Is it possible then that I can use it to provide a continuous train of interrupts then into my "locked in" FAST THREAD for timing purposes? This is the range of about 1-2 us. If not, then just reading one channel on that CTC to provide software sync. This fast thread will, therefore, see (experience) no delays from the interrupts issued in the other cores and associated multicore fabric. This FAST THREAD, when running, will continue to run until the program closes. This could be hours.
Input data to drive this FAST THREAD will be common shared memory defined in the program. There are also hardware signals for motion limits (From GPIOs or SDI port). If any go TRUE, that forces a programmed halt all motion. It does not need a 1~2us response. It could go to a slower Motion loop.
Ah, the output:
Some motion data is written back to the shared memory (assigned for this purpose). Like current location, and current loop number,
Some signals need to be output (the 8 outputs). There are numerous free GPIOs. Not sure of the path taken to get the signaled GPIO pin to change the output. The system call to Linux initiates the pin change event. There is also an SDI port available, running up to the 25Mhz clock. It seems these ports (GPIO, UART, USB, SDI) exist in the fabric that is not on any specific core. I am not sure of the latency from the issuance of these signals in the program until the associated external pin actually presents that signal. In the fast thread, even 10us would be OK, if it was always the same latency! I know that will not be so, there will jitter. I need to think on this spec.
There will possibly be a second dedicated core (similar to above) for slower motion planning. That leaves two cores for everything thing else. Since then everything else items (sata, video screen, keyboard ...) are already able to work in a single core, then the remaining two cores should be great.
At close of program, the FAST THREAD returns the CTC and any other device on its core back to "as it was", re-enables the OS components in this core to their more normal operation. End of thread.
Concluding: I have described the overall program, so as for you to understand what I want to do with this FAST THREAD running, how responsive it needs to be, and that it needs to be undisturbed!! This processor runs in the 1.5 ~ 2.0 GHz range. It certainly can do the repeated calculations in the required time frame.
DESIRED: I do not know the system calls that would allow me to use a selected x86 core in this way. Any pointers would be helpful. Any manual or document that described these calls/procedures.
Can this use of a core also be done in windows 7,10)?
Thanks for reading and any pointers you have.
Stan
I want to see programmatically how much GPU time a part of my application consumes on macOS and iOS. On OpenGL and D3D I can use GPU timer query objects. I searched and couldn't find anything similar for Metal. How do I measure GPU time on Metal without using Instruments etc. I'm using Objective-C.
There are a couple of problems with this method:
1) You really want to know what is the GPU side latency within a command buffer most of the time, not round trip to CPU. This is better measured as the time difference between running 20 instances of the shader and 10 instances of the shader. However, that approach can add noise since the error is the sum of the errors associated with the two measurements.
2) Waiting for completion causes the GPU to clock down when it stops executing. When it starts back up again, the clock is in a low power state and may take quite a while to come up again, skewing your results. This can be a serious problem and may understate your performance in benchmark vs. actual by a factor of two or more.
3) if you start the clock on scheduled and stop on completed, but the GPU is busy running other work, then your elapsed time includes time spent on the other workload. If the GPU is not busy, then you get the clock down problems described in (2).
This problem is considerably harder to do right than most benchmarking cases I've worked with, and I have done a lot of performance measurement.
The best way to measure these things is to use on device performance monitor counters, as it is a direct measure of what is going on, using the machine's own notion of time. I favor ones that report cycles over wall clock time because that tends to weed out clock slewing, but there is not universal agreement about that. (Not all parts of the hardware run at the same frequency, etc.) I would look to the developer tools for methods to measure based on PMCs and if you don't find them, ask for them.
You can add scheduled and completed handler blocks to a command buffer. You can take timestamps in each and compare. There's some latency, since the blocks are executed on the CPU, but it should get you close.
With Metal 2.1, Metal now provides "events", which are more like fences in other APIs. (The name MTLFence was already used for synchronizing shared heap stuff.) In particular, with MTLSharedEvent, you can encode commands to modify the event's value at particular points in the command buffer(s). Then, you can either way for the event to have that value or ask for a block to be executed asynchronously when the event reaches a target value.
That still has problems with latency, etc. (as Ian Ollmann described), but is more fine grained than command buffer scheduling and completion. In particular, as Klaas mentions in a comment, a command buffer being scheduled does not indicate that it has started executing. You could put commands to set an event's value at the beginning and (with a different value) at the end of a sequence of commands, and those would only notify at actual execution time.
Finally, on iOS 10.3+ but not macOS, MTLCommandBuffer has two properties, GPUStartTime and GPUEndTime, with which you can determine how much time a command buffer took to execute on the GPU. This should not be subject to latency in the same way as the other techniques.
As an addition to Ken's comment above, GPUStartTime and GPUEndTime is now available on macOS too (10.15+):
https://developer.apple.com/documentation/metal/mtlcommandbuffer/1639926-gpuendtime?language=objc
New description of the problem:
I currently run our new data acquisition software in a test environment. The software has two main threads. One contains a fast loop which communicates with the hardware and pushes the data into a dual buffer. Every few seconds, this loop freezes for 200 ms. I did several tests but none of them let me figure out what the software is waiting for. Since the software is rather complex and the test environment could interfere too with the software, I need a tool/technique to test what the recorder thread is waiting for while it is blocked for 200 ms. What tool would be useful to achieve this?
Original question:
In our data acquisition software, we have two threads that provide the main functionality. One thread is responsible for collecting the data from the different sensors and a second thread saves the data to disc in big blocks. The data is collected in a double buffer. It typically contains 100000 bytes per item and collects up to 300 items per second. One buffer is used to write to in the data collection thread and one buffer is used to read the data and save it to disc in the second thread. If all the data has been read, the buffers are switched. The switch of the buffers seems to be a major performance problem. Each time the buffer switches, the data collection thread blocks for about 200 ms, which is far too long. However, it happens once in a while, that the switching is much faster, taking nearly no time at all. (Test PC: Windows 7 64 bit, i5-4570 CPU #3.2 GHz (4 cores), 16 GB DDR3 (800 MHz)).
My guess is, that the performance problem is linked to the data being exchanged between cores. Only if the threads run on the same core by chance, the exchange would be much faster. I thought about setting the thread affinity mask in a way to force both threads to run on the same core, but this also means, that I lose real parallelism. Another idea was to let the buffers collect more data before switching, but this dramatically reduces the update frequency of the data display, since it has to wait for the buffer to switch before it can access the new data.
My question is: Is there a technique to move data from one thread to another which does not disturb the collection thread?
Edit: The double buffer is implemented as two std::vectors which are used as ring buffers. A bool (int) variable is used to tell which buffer is the active write buffer. Each time the double buffer is accessed, the bool value is checked to know which vector should be used. Switching the buffers in the double buffer just means toggling this bool value. Of course during the toggling all reading and writing is blocked by a mutex. I don't think that this mutex could possibly be blocking for 200 ms. By the way, the 200 ms are very reproducible for each switch event.
Locking and releasing a mutex just to switch one bool variable will not take 200ms.
Main problem is probably that two threads are blocking each other in some way.
This kind of blocking is called lock contention. Basically this occurs whenever one process or thread attempts to acquire a lock held by another process or thread. Instead parallelism you have two thread waiting for each other to finish their part of work, having similar effect as in single threaded approach.
For further reading I recommend this article for a read, which describes lock contention with more detailed level.
Since you are running on windows maybe you use visual studio? if yes I would resort to VS profiler which is quite good (IMHO) in such cases, once you don't need to check data/instruction caches (then the Intel's vTune is a natural choice). From my experience VS is good enough to catch contention problems as well as CPU bottlenecks. you can run it directly from VS or as standalone tool. you don't need the VS installed on your test machine you can just copy the tool and run it locally.
VSPerfCmd.exe /start:SAMPLE /attach:12345 /output:samples - attach to process 12345 and gather CPU sampling info
VSPerfCmd.exe /detach:12345 - detach from process
VSPerfCmd.exe /shutdown - shutdown the profiler, the samples.vsp is written (see first line)
then you can open the file and inspect it in visual studio. if you don't see anything making your CPU busy switch to contention profiling - just change the "start" argument from "SAMPLE" to "CONCURRENCY"
The tool is located under %YourVSInstallDir%\Team Tools\Performance Tools\, AFAIR it is available from VS2010
Good luck
After discussing the problem in the chat, it turned out that the Windows Performance Analyser is a suitable tool to use. The software is part of the Windows SDK and can be opened using the command wprui in a command window. (Alois Kraus posted this useful link: http://geekswithblogs.net/akraus1/archive/2014/04/30/156156.aspx in the chat). The following steps revealed what the software had been waiting on:
Record information with the WPR using the default settings and load the saved file in the WPA.
Identify the relevant thread. In this case, the recording thread and the saving thread obviously had the highest CPU load. The saving thread could be easily identified. Since it saves data to disc, it is the one that with file access. (Look at Memory->Hard Faults)
Check out Computation->CPU usage (Precise) and select Utilization by Process, Thread. Select the process you are analysing. Best display the columns in the order: NewProcess, ReadyingProcess, ReadyingThreadId, NewThreadID, [yellow bar], Ready (µs) sum, Wait(µs) sum, Count...
Under ReadyingProcess, I looked for the process with the largest Wait (µs) since I expected this one to be responsible for the delays.
Under ReadyingThreadID I checked each line referring to the thread with the delays in the NewThreadId column. After a short search, I found a thread that showed frequent Waits of about 100 ms, which always showed up as a pair. In the column ReadyingThreadID, I was able to read the id of the thread the recording loop was waiting for.
According to its CPU usage, this thread did basically nothing. In our special case, this led me to the assumption that the serial port io command could cause this wait. After deactivating them, the delay was gone. The important discovery was that the 200 ms delay was in fact composed of two 100 ms delays.
Further analysis showed that the fetch data command via the virtual serial port pair gets sometimes lost. This might be linked to very high CPU load in the data saving and compression loop. If the fetch command gets lost, no data is received and the first as well as the second attempt to receive the data timed out with their 100 ms timeout time.
I have a time-critical application which processes a sequence of images coming from camera. It is written in C++ and it uses Qt, OpenCV and boost libraries. It is going to run on a dedicated PC.
Currently, the gui functions in main thread and i open a new thread for image processing. I didn't bother to divide the process section into threads because i think OpenCV is already doing that. However, i am having trouble maintaining the maximum tolerable delay.
My question is, how can i learn if my application using all the cores in the maximum level ?
When i look at the performance monitor, the pattern i see is really strange. The CPU usage is likely %35-40, all the cores are working but not at a full throttle.
Am i doing something wrong ?
You are not doing anything wrong, however you could change your code to take full use of the cpu cores by:
1 - setting the core affinity so that the thread does not change from one core to another, this could improve the cache usage (L1 and maybe L2)
2 - setting the scheduling of threads to FIFO so it does not get context-switched before finishing its processing
3 - run that thread on a higher priority process (this would require root privilege for the process)
Cheers