I successfully implemented a solver that fits my needs. However, I need to run the solver on 1500+ different "problems" at 0:00 precisely, everyday. Because my web-app is in ruby, I built a quarkus "micro-service" that takes the data, calculate a solution and return it to my main app.
In my application.properties, I set:
quarkus.optaplanner.solver.termination.spent-limit=5s
which means each request take ~5s to solve. But sending 1500 requests at once will saturate the CPU on my machine.
Is there a way to tell OptaPlanner to stop when the solution is good enough ? ( for example if the score is stable ... ). That way I can maybe reduce the time from 5s to 1-2s depending on the problem?
What are your recommandations for my specific scenario?
The SolverManager will automatically queue solver jobs if too many come in, based on its parallelSolverCount configuration:
quarkus.optaplanner.solver-manager.parallel-solver-count=3
In this case, it will run 3 solvers in parallel. So if 7 datasets come in, it will solve 3 of them and the other 4 later, as the earlier solvers terminate. However if you use moveThreadCount=2, then each solver uses at least 2 cpu cores, so you're using at least 6 CPU cores.
By default parallelSolverCount is currently set to half your CPU cores (it currently ignores moveThreadCount). In containers, it's important to use JDK 11+: the CPU count of the container is often different than from the bare metal machine.
You can indeed tell the OptaPlanner Solvers to stop when the solution is good enough, for example when a certain score is attained or the score hasn't improved in an amount of time, or combinations thereof. See these OptaPlanner docs. Quarkus exposes some of these already (the rest currently still need a solverConfig.xml file), some Quarkus examples:
quarkus.optaplanner.solver.termination.spent-limit=5s
quarkus.optaplanner.solver.termination.unimproved-spent-limit=2s
quarkus.optaplanner.solver.termination.best-score-limit=0hard/-1000soft
We are noticing occasional periods of high CPU on a web server that happens to use ImageResizer. Here are the surprising results of a trace performed with NewRelic's thread profiler during such a spike:
It would appear that the cleanup routine associated with ImageResizer's DiskCache plugin is responsible for a significant percentage of the high CPU consumption associated with this application. We have autoClean on, but otherwise we're configured to use the defaults, which I understand are optimal for most typical situations:
<diskCache autoClean="true" />
Armed with this information, is there anything I can do to relieve the CPU spikes? I'm open to disabling autoClean and setting up a simple nightly cleanup routine, but my understanding is that this plugin is built to be smart about how it uses resources. Has anyone experienced this and had any luck simply changing the default configuration?
This is an ASP.NET MVC application running on Windows Server 2008 R2 with ImageResizer.Plugins.DiskCache 3.4.3.
Sampling, or why the profiling is unhelpful
New Relic's thread profiler uses a technique called sampling - it does not instrument the calls - and therefore cannot know if CPU usage is actually occurring.
Looking at the provided screenshot, we can see that the backtrace of the cleanup thread (there is only ever one) is frequently found at the WaitHandle.WaitAny and WaitHandle.WaitOne calls. These methods are low-level synchronization constructs that do not spin or consume CPU resources, but rather efficiently return CPU time back to other threads, and resume on a signal.
Correct profilers should be able to detect idle or waiting threads and eliminate them from their statistical analysis. Because New Relic's profiler failed to do that, there is no useful way to interpret the data it's giving you.
If you have more than 7,000 files in /imagecache, here is one way to improve performance
By default, in V3, DiskCache uses 32 subfolders with 400 items per folder (1000 hard limit). Due to imperfect hash distribution, this means that you may start seeing cleanup occur at as few as 7,000 images, and you will start thrashing the disk at ~12,000 active cache files.
This is explained in the DiskCache documentation - see subfolders section.
I would suggest setting subfolders="8192" if you have a larger volume of images. A higher subfolder count increases overhead slightly, but also increases scalability.
We are facing an issue with VB.NET listeners that utilizes high CPU (50% to 70%) in the server machine where it is running. Listeners are using a threading concept and also we used FileSystemWatcher class to keep monitoring the file renaming pointing to one common location. Both are console applications and scheduled jobs running all the day.
How can I control the CPU utilization with this FileSystemWatcher class?
This could all depend on the code you are running.
For instance if you have a timer with an interval of 10ms but only do work every two minutes and on each timer interval you do a lot of checking this will take a lot of CPU to do nothing.
If you are using multiple threads and one is looping waiting for the second to release a lock (Monitor.TryEnter()) then again this may be taking up extra CPU. You can avoid this by putting the waiting thread into Monitor.Wait() and then when the busy thread is finished do Monitor.Pulse().
Apart for the very general advice above, if you post the key parts of your code or profile results then we may be able to help more.
If you are looking for a profiler we use RedGates ANTS Profiler (costs but with a free trial) and it give good results, I haven't used any other to compare (and I am in no way affiliated with RedGate) so others may be better.
I am somewhat familiar with the CUDA visual profiler and the occupancy spreadsheet, although I am probably not leveraging them as well as I could. Profiling & optimizing CUDA code is not like profiling & optimizing code that runs on a CPU. So I am hoping to learn from your experiences about how to get the most out of my code.
There was a post recently looking for the fastest possible code to identify self numbers, and I provided a CUDA implementation. I'm not satisfied that this code is as fast as it can be, but I'm at a loss as to figure out both what the right questions are and what tool I can get the answers from.
How do you identify ways to make your CUDA kernels perform faster?
If you're developing on Linux then the CUDA Visual Profiler gives you a whole load of information, knowing what to do with it can be a little tricky. On Windows you can also use the CUDA Visual Profiler, or (on Vista/7/2008) you can use Nexus which integrates nicely with Visual Studio and gives you combined host and GPU profile information.
Once you've got the data, you need to know how to interpret it. The Advanced CUDA C presentation from GTC has some useful tips. The main things to look out for are:
Optimal memory accesses: you need to know what you expect your code to do and then look for exceptions. So if you are always loading floats, and each thread loads a different float from an array, then you would expect to see only 64-byte loads (on current h/w). Any other loads are inefficient. The profiling information will probably improve in future h/w.
Minimise serialization: the "warp serialize" counter indicates that you have shared memory bank conflicts or constant serialization, the presentation goes into more detail and what to do about this as does the SDK (e.g. the reduction sample)
Overlap I/O and compute: this is where Nexus really shines (you can get the same info manually using cudaEvents), if you have a large amount of data transfer you want to overlap the compute and the I/O
Execution configuration: the occupancy calculator can help with this, but simple methods like commenting the compute to measure expected vs. measured bandwidth is really useful (and vice versa for compute throughput)
This is just a start, check out the GTC presentation and the other webinars on the NVIDIA website.
If you are using Windows... Check Nexus:
http://developer.nvidia.com/object/nexus.html
The CUDA profiler is rather crude and doesn't provide a lot of useful information. The only way to seriously micro-optimize your code (assuming you have already chosen the best possible algorithm) is to have a deep understanding of the GPU architecture, particularly with regard to using shared memory, external memory access patterns, register usage, thread occupancy, warps, etc.
Maybe you could post your kernel code here and get some feedback ?
The nVidia CUDA developer forum forum is also a good place to go for help with this kind of problem.
I hung back because I'm no CUDA expert, and the other answers are pretty good IF the code is already pretty near optimal. In my experience, that's a big IF, and there's no harm in verifying it.
To verify it, you need to find out if the code is for sure not doing anything it doesn't really have to do. Here are ways I can see to verify that:
Run the same code on the vanilla processor, and either take stackshots of it, or use a profiler such as Oprofile or RotateRight/Zoom that can give you equivalent information.
Running it on a CUDA processor, and doing the same thing, if possible.
What you're looking for are lines of code that have high occupancy on the call stack, as shown by the fraction of stack samples containing them. Those are your "bottlenecks". It does not take a very large number of samples to locate them.
We have some users which are using lower-CPU powered machines and they're encountering slow response times using our web application. Is there any way for me to do testing so that I can simulate lower CPU rates?
For example, I have 2.3 Ghz computing power, can I lower it to 1.6 Ghz or lower so that I may be able to test it?
BTW, our customers are using Windows. I have to simulate low computing power on Internet Explorer as browser.
Most new CPUs multiplier can easily be lowered (Intel: Speedstep, AMD: PowerNow!). This is used to save power. With RMclock you can manually adjust your multiplier and thus lower your frequency and make your pc slower. I use this tool myself so I can tell you that it works.
http://cpu.rightmark.org/products/rmclock.shtml
The virtual machine Bochs(pronounced boxes) allows you to set a instructions per second directive. It's probably the slowest emulator out there as it is though...
Create some virtual machines.
You can use VirtualPC or VirtualBox both are free.
I would recommend to start something on the background which eats up all your processor cycles.
A program which finds primenumbers or something similar.
Another slight option in addition to those above is to boot windows in a lower resource config. Go to the start menu,, select run and type MSCONFIG. You can go to the boot tab, click on advanced options and limit the memory and number of of processsors. It's not as robust as the above, but it does give you another option.
Lowering the CPU clock doesn't always give expected results.
Newer CPUs feature architecture improvements which make them more efficient on an equvialent clock basis than older chips. Incidentally, because of this virtual machines are a bad way of testing performance for "older" tech as well.
Your best bet is to simply buy a couple of older machines. Using similar RAM (types and amounts), processor, motherboard chipsets, hard drives, and video cards. All of which feed into the total performance of the machine itself.
I bring the other components up because changing just one of them can have an impact on even browser performance. A prime example is memory. If your clients are constrained to something like 512MB of RAM, the machines could be performing a lot of hard drive access for VM swaps, even for just running the browser. In this situation downgrading the clock speed on your processor while still retaining your 2GB (assuming) of RAM would still not perform anywhere near the same even if everything else was equal.
Isak Savo'sanswer works, but can be a bit finicky, as the modern tpl is going to try and limit cpu load as much as possible. When I tested it out, It was hard (though possible with some testing) to consistently get the types of cpu usages I wanted.
Then I remembered, http://www.cpukiller.com/, which does this already. Highly recommended. As an aside, I found this util from playing old 90s games on modern machines, back when frame rate was pegged to cpu clock time, making playing them on modern computers way too fast. Great utility.
Another big difference between high-performance and low-performance CPUs is the number of cores available. This can realistically differ by a factor of 4, way more than the difference in clock frequency you're likely to encounter.
You can solve this by setting the thread affinity. Even IE6 will use 13 threads just to show google.com. That means it will benefit from a multi-core CPU. But if you set the thread affinity to one core only, all 13 IE threads will have to share that one core.
I understand that this question is pretty old, but here are some receipts I personally use (not only for Web development):
BES. I'm getting some weird results while using it.
Go to Control Panel\All Control Panel Items\Power Options\Edit Plan Settings\Change Advanced Power Settings, then go to the "Processor" section and set it's maximum state to 5% (or something else). It works only if your processor supports dynamic multiplier change and ACPI driver is installed correctly.
Run Task Manager and set processor affinity to a single core (or whatever number of cores you want) for your browser's (or any other's) process. Not a best practice for browsers, because JavaScript implementations are usually single-threaded, but, as far as I see, modern browsers actually DO use multiple cores.
There are a few different methods to accomplish this.
If you're using VirtualBox, go into the Settings for the VM you want to slow the CPU speed for. Go to System > Processor, then set the Execution Cap. The percentage controls how slow it will go: lower values are slower relative to the regular speed. In practice, I've noticed the results to be choppy, although it does technically work.
It is also possible to set the CPU speed for the whole system. In the Windows 10 Settings app, go to System > Power & Sleep. Then click Additional Power Settings on the right hand side. Go to Change Plan Settings for the currently selected plan, then click Change Advanced Power Plan Settings. Scroll down to Processor Power Management and set the Maximum Processor State. Again, this is a percentage. Although this does work, I find that in practice, it doesn't have a big impact even when the percentage is set very low.
If you're dealing with a videogame that uses DirectX or OpenGL and doesn't have a framerate cap, another common method is to force Vsync on in your graphics driver settings. This will usually slow the rendering to about 60 FPS which may be enough to play at a reasonable rate. However, it will only work for applications using 3D hardware rendering specifically.
Finally: if you'd rather not use a VM, and don't want to change a system global setting, but would rather simulate an old CPU for one specific process only, then I have my own program to do that called Old CPU Simulator.
The main brain of the operation is a command line tool written in C++, but there is also a GUI wrapper written in C#. The GUI requires .NET Framework 4.0. The default settings should be fine in most cases - just select the CPU you'd like to simulate under Target Rate, then hit New and browse for the program you'd like to run.
https://github.com/tomysshadow/OldCPUSimulator (click the Releases tab on the right for binaries.)
The concept is to suspend and resume the process at a precise rate, and because it happens so quickly the process will appear to just be running slowly. For example, by suspending a process for 3 milliseconds, then resuming it for 1 millisecond, it will appear to be running at 25% speed. By controlling the ratio of time suspended vs. time resumed, it is possible to simulate different speeds. This is completely API agnostic (it doesn't hook DirectX, OpenGL, etc. it'll work with a command line program if you want.)
Old CPU Simulator does not ask for a percentage, but rather, the clock speed to simulate (which it calls the Target Rate.) It then automatically determines, based on your CPU's real clock speed, the percentage to use. Although clock speed is not the only factor that has improved computer performance over time (there are also SSDs, faster GPUs, more RAM, multithreaded performance, etc.) it's a good enough approximation to get fairly consistent results across machines given the same Target Rate. It also supports other options that may help with consistency, such as setting the process affinity to one.
It implements three different methods of suspending and resuming a process and will use the best available: NtSuspendProcess, NtQuerySystemInformation, or Toolhelp Snapshots. It also uses timeBeginPeriod and timeEndPeriod to achieve high precision timing without busy looping. Note that this is not an emulator; the binary still runs natively. If you like, you can view the source to see how it's implemented - it's not a large project. On my machine, Old CPU Simulator uses less than 1% CPU and less than 1 MB of memory, so the program itself is quite efficient (unlike running intensive programs to intentionally slow the CPU.)