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Final Edit: I just realized that when use the word "parallelism", it's almost parallelism==ILP, I originally thought even a single instruction could be divided into several phrases, and at that level there would be some parallelism, but then I realized this has no meaning. Both my title and my example didn't mentioned anything about more than one threads' parallelism as done by HyperThreading, so @user110971's is the correct answer, without doubt anymore. (In the philosophical level, I just need a base-case condition to return my recursiveness of finding the deepest part of parallelism)

Edit3: I made a graph for my Edit2, and I found this video on YouTube about HyperThreading useful. enter image description here

Edit2: In short, for my question I adopt the definitions on Wikipedia, and for the definition of the terms:

  • Parallel: Two threads, run independently, at any physical instant. So one thread won't interrupt the other, at any instant.
  • Concurrent: Two threads, run independently, interleavedly is allowed, i.e. not restricted to parallel, and one can interrupt the other.
  • In short, for me and Wikipedia writers, Concurrent includes Parallel. Thanks.

Edit: Just to be clear, for me parallelism means true parallelism, I add a "true" for it because people I talked to tend to think parallel==concurrent. (See my second link)

Is it true that on modern processor, "true" parallelism is possible on a single core? I asked elsewhere but didn't get a confirming answer. What I want to know is e.g. whether at t=0, two instructions are fetched and executed. At the same physical instant.

My question came from here:

parallel computing is impossible on a (one-core) single processor, as only one computation can occur at any instant (during any single clock cycle).

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    \$\begingroup\$ Aside from HyperThreading? \$\endgroup\$ – cHao Dec 7 '18 at 22:38
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    \$\begingroup\$ It's the only way to achieve true parallelism with a single core, yes. Superscalar processing can do several things at once, but it can still only run one thread at a time. \$\endgroup\$ – cHao Dec 7 '18 at 22:50
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    \$\begingroup\$ Because it's a kind of parallelism, and thus is worth bringing up. It's an example of the processor executing two or more instructions in a single clock cycle, just like you asked for. It's just not the kind of parallelism most people are talking about when they use the word. \$\endgroup\$ – cHao Dec 7 '18 at 22:53
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    \$\begingroup\$ I don't get it - What does it mean "true" or "false" or "untrue" parallelism? \$\endgroup\$ – Al Kepp Dec 7 '18 at 23:21
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    \$\begingroup\$ @ptr_user7813604 I looked at the first link, that one is "true parallelism". But this suspicious pseudo-term is not defined there. So maybe you could write the basic terms in your question, instead of providing just links. \$\endgroup\$ – Al Kepp Dec 7 '18 at 23:34
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It is indeed possible to have parallelism on a superscalar processor. A superscalar processor can execute multiple instructions at the same time by using multiple execution units. pipeline There are certain limitations depending on the architecture. It is not true parallelism. If you have to calculate $$A = B + C,$$ $$D = A + 3,$$ you cannot execute both instructions at the same time. However you can execute $$A = B + C,$$ $$D = D + 3,$$ simultaneously by utilizing two ALUs.

So as an answer to your question, you can have a certain level of parallelism on a single core, as long as your instructions do not use the same hardware resources.

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    \$\begingroup\$ And then many DSP architectures are explicitly MIMD (like SIMD, but the instructions to the different execution units are different). Unlike "implicit superscalar execution", this VLIW and "Explicitly parallel instruction computing" is scheduled by the linker, not discovered by the CPU logic. \$\endgroup\$ – Ben Voigt Dec 7 '18 at 22:51
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    \$\begingroup\$ @BenVoigt not only DSP, there's also Itanium featuring VLIW. \$\endgroup\$ – Ruslan Dec 8 '18 at 8:48
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On some processors this is (sometimes) possible. Since different instructions use different processor resources (ALU, floating point, load, store, etc), it's sometimes possible to parallelize some of them. For example, see here for details on how that works on an Ivy Bridge (x86) CPU: https://dendibakh.github.io/blog/2018/03/21/port-contention

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There are lots of different types of parallelism.

Instruction level parallelism is a feature of any superscalar processor. Multiple instructions are in progress at any point in time. However, those instructions are from the same thread of control.

Thread level parallelism within a single core is possible with hyperthreading -- two separate threads using different core resources at the same time. One thread can use the integer ALU while another is executing a load or store.

Data level parallelism is also a type of parallelism. SIMD units can execute the same instructions on multiple registers at the same time. For instance, if you need to apply the same blur transformation to every pixel in an image, you might be able to do that 8 pixels in parallel, but within the same thread of control.

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  • \$\begingroup\$ Great, and apologies that I think my "e.g. whether at t=0, two instructions are fetched and executed" is a wrong example, it's not the same as I thought it should be.... \$\endgroup\$ – ptr_user7813604 Dec 8 '18 at 0:47
  • \$\begingroup\$ So is that for hyperthreading there is nothing duplicate in a single core, but using different core resources at the same time? \$\endgroup\$ – ptr_user7813604 Dec 8 '18 at 0:50
  • \$\begingroup\$ A single core may just as well contain multiple copies of the same unit. For example, it is typical to have two or more integer units and one floating point unit. Or, two full integer units, one integer unit with restricted capabilities, and one floating point unit. Or, … (you get the idea). \$\endgroup\$ – Jörg W Mittag Dec 8 '18 at 8:09
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    \$\begingroup\$ What Jorg W Mittag said. You have multiple schedulers. So if the primary scheduler isn't using all the INTEGER or FLOAT units, than a secondary scheduler could run another thread using those unused units. This is also key why some workloads get faster and some get way slower. If the primary workload is using almost every unit, the secondary "hyperthread" can't actually get anything done without waiting for those units. They also compete for other shared things like cache and memory traffic. So if they're not producing enough useful work to justify the new cache contention, it's slower. \$\endgroup\$ – Katastic Voyage Dec 8 '18 at 10:21
  • \$\begingroup\$ @JörgWMittag: You mean Architectural_state? \$\endgroup\$ – ptr_user7813604 Dec 8 '18 at 12:41

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