A computer has 2 physical cores, and 4 logical cores (For example, a computer with an i5-3210M processor).

When a program A runs, htop shows that it uses 100% of 1 core, and other 3 cores are nearly idle. The throughput in this case is X.

My question is, if I run 4 instances of A on 4 logical cores, then the total throughput is 4X, or 2X? What if I run only two instances?

3 Answers 3


The concept of cores is not that simple. Logical cores are the number of Physical cores times the number of threads that can run on each cores. This is known as HyperThreading. If I have a computer that has a 4-core processor, runs two threads per core, then I have a 8 logical processors. You can see your computers core capabilities by running lscpu command.

If a processor has 4 cores, but it can run 8 threads in parallel, means that it only has 4 physical cores (processing units). But its hardware can support up to 8 threads in parallel. Clearly maximum of 4 jobs can run in the cores. One job running in the core, if by any means stalls for memory or I/O operation then another thread can use that free core.

You should now understand that if your computer has 2 physical cores, and can run 2 threads per core, then you have 4 logical processors. So you can run only 2 instances as you have 2 physical cores, that means you're using the full capabilities of single physical cores (2 threads at a time). So the throughput will be 50%. But if anytime one thread goes idle, then the core can load up one thread on that core.

You can turn off the HyperThreading in BIOS(something like "Intel ht technology") and see the difference between normal and HyperThreading capabilities as now the throughput will be 100%.

  • 1
    lscpu is not working on Windows 10. Commented Jan 19, 2019 at 11:30
  • 1
    @Chamindabandra perform an update and upgrade then try again. This time should work. Commented Feb 5, 2019 at 17:33
  • 2
    @ChamindaBandara lscpu works even through WSL
    – KhoPhi
    Commented Oct 30, 2019 at 2:48
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    I got a bit confused when you say that a 4-physical-core process with 8 logical cores can run 8 threads but only 4 jobs. I thought that each logical core can run a separate process (e.g. see en.wikipedia.org/wiki/Hyper-threading). Is there a difference between a job and process here?
    – Marses
    Commented Jun 16, 2021 at 7:14

Even with many more cores than tasks, they won’t scale perfectly. That’s because some state is almost always shared. Not necessarily in the task, but the kernel, for example. Or they may access the same resource, like the network or a disk or whatever.

SMT (ie. Hyper-Threading) may rely on the fact that different tasks use different CPU execution units. As such, so-called “Instruction-level parallelism” can be achieved on superscalar CPUs. Virtually any modern x86 processor is superscalar.

Assuming you have two tasks that only consists of adding numbers with no other CPU instructions, then yes, they will conflict when running on the same physical core, possible leading to significant performance degradation.

However, most of the time, this isn’t the case and a variety of stuff happens. As long as the same command doesn’t appear on both instruction streams at (roughly) the same time, CPU execution unit utilization can be improved.


If the program has no way to coordinate separate instances you will almost certainly get no improvement.


If I have a single threaded program that calculates primes from 2-10, a single instance running it would calculate if each number from 2-10 was prime, and find that 2,3,5,7 are prime.

If I add a second instance without any modification to the code The first instance would calculate if each number from 2-10 are prime, and find that 2,3,5,7 are prime, while the second instance would calculate if each number from 2-10 are prime, and find that 2,3,5,7 are prime.

doing this would result in the same work being done twice leading to no improvement.

  • This doesn't really address the question at all. You make some good points but they're asking about core utilization, not how to create a multi-threaded program. Commented Jun 20, 2019 at 1:21

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