I have deployed Rhino compute on my EC2 instance. I receive multiple concurrent web requests to run compute. What is the multi-threading behavior by compute. If I increase the childcount to a high number, the system becomes very slow. Aren’t the child processes spawned based on the number of requests? Since it is a web application, the traffic is even. I want compute to spawn the child processes based on the incoming requests.
The current behavior is that rhino.compute launches all of the child processes (based on the web.config file) whenever it gets its first authenticated request. These children will stay active until the idle timeout value is met, I don’t think we have a method for selectively spawning additional children via requests. I’m also not sure that would give you the desired outcome. I realize that spawning a lot of children can be slow but once they’re loaded, the response time should be relatively quick. I think if you waited to launch children later when multiple requests are received, the response times would be slower because it’s still spawning a few children (which takes time). Is it possible to hit the /activechildren endpoint (which is one method which starts the spawning process) before you expect your first valid request?
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Hi Andy and Aditi,
I have a similar question regarding the child count. If I send the requests to rhino.compute one at a time so that I wait for the response of the first request before I create the next, will a higher child count increase the performance of the computation (given that the machine I’m running it on has the adequate specs).
Right now I’m running compute on a VM with a 64gb vRAM and 16 cores I believe, and I’m using a child count of 8. All the compute.geometry processes only takes up about 10% of memory and CPU at its peak and I’m wondering how I can get more bang for the buck. Should I:
- Keep sending the requests 1 by 1 and increase the child count or
- throwing multiple requests at the machine at once (they’re stored in a queue and are being processed sequentially)?
Thank you so much!
Best,
Erik
If you’re sending requests 1 at a time and waiting for a response before sending another one, then there’s no sense in spawning multiple children as only one will ever be used. However, you could see better performance by spinning up multiple children and then sending multiple requests in rapid succession. This will allow the rhino.compute.exe parent layer to determine which child process gets which request… but theoretically you should see significant performance increase by having multiple worker threads (ie. the children) working on your requests and speeding up the time it takes to get the response. Does that help?
Hello Andy,
thanks for you quick response. Yes that is really helpful! Is there a good rule of thumb for the ideal child process count for a specific number of cores on the VM? If I have 8 cores, is 8 a good number for the child count parameter as well then or should it be kept a bit lower would you say?
Thanks again!
Best,
Erik
No, there’s no great “rule-of-thumb” here because the number of children is highly dependent on each project’s use case. Some times, it could be beneficial to only use one or two children if you don’t think you’ll ever be sending many concurrent requests. Using less children means that lag time upon startup (when you send your first request) will be shorter. However, other use cases would benefit from having as many children instances working as possible. So, it’s entirely up to the user to determine their own requirements. I hope that helps.
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May i ask a question? I’m running rhino compute locally on my PC by starting the visual studio project. How can i increase the child count to speed effenciency?
In the Solution Explorer, right click on the rhino.compute project and click on Properties. On the left-hand menu, click on the Debug menu item. This will load the general debug settings for this project. Under the General section, you should see a link that says Open debug launch profiles UI. Click on that link, which will open a modal dialog (like the one below). Simply change the number after --childcount to the number of children that you want to run. Close the dialog and rebuild your project solution. Then start the debugger. You should see multiple child processes starting up when the Rhino.Compute console launches.
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Thanks！I have another question. I want to call some gh files to run by python like this.
Does this multiprocessing conflict with the child process in rhino compute?
Another question, when i only run one gh file, the time spent when the number of child processes is 1 is even shorter when the number of child processes is 5, why?
I don’t think we have enough experience with the multiprocessing library under this scenario to really give any sort of decent answer