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Home/ Questions/Q 3243878
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Editorial Team
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Editorial Team
Asked: May 17, 20262026-05-17T18:29:06+00:00 2026-05-17T18:29:06+00:00

We have to make our system highly scalable and it has been developed for

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We have to make our system highly scalable and it has been developed for windows platform using VC++. Say initially, we would like to process 100 requests(from msmq) simultaneously. What would be the best approach? Single process with 100 threads or 2 processes with 50-50 threads? What is the gain apart from process memory in case of second approach. does in windows first CPU time is allocated to process and then split between threads for that process, or OS counts the number of threads for each process and allocate CPU on the basis of threads rather than process. We notice that in first case, CPU utilization is 15-25% and we want to consume more CPU. Remember that we would like to get optimal performance thus 100 requests are just for example. We have also noticed that if we increase number of threads of the process above 120, performance degrades due to context switches.

One more point; our product already supports clustering, but we want to utilize more CPU on the single node.

Any suggestions will be highly appreciated.

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  1. Editorial Team
    Editorial Team
    2026-05-17T18:29:06+00:00Added an answer on May 17, 2026 at 6:29 pm

    The standard approach on windows is multiple threads. Not saying that is always your best solution but there is a price to be paid for each thread or process and on windows a process is more expensive. As for scheduler i’m not sure but you can set the priory of the process and threads. The real benefit to threads is their shared address space and the ability to communicate without IPC, however synchronization must be careful maintained.

    If you system is already developed, which it appears to be, it is likely to be easier to implement a multiple process solution especially if there is a chance that latter more then one machine may be utilized. As your IPC from 2 process on one machine can scale to multiple machines in the general case. Most attempts at massive parallelization fail because the entire system is not evaluated for bottle necks. for example if you implement a 100 threads that all write to the same database you may gain little in actual performance and just wait on your database.

    just my .02

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