> On Feb 5, 2024, at 14:55, Gang Li <gang.li@xxxxxxxxx> wrote:
>
>
> On 2024/2/4 15:48, Gang Li wrote:
>> On 2024/2/4 15:44, Muchun Song wrote:
>>> I don't think it is a clear way to fix this. If someone want to
>>> use PADATA in a non-SMP system, he should be carefully to handle
>>> the non-SMP case himself. I think the better way is to make PADATA
>>> handle the non-SMP case, I think it should be easy for it, which
>>> could just call ->thread_fn() many times instead of creating many
>>> threads in the non-SMP case.
>>>
>>> Thanks.
>>>
>> Sounds good, I'll take a look at padata and send a new patch.
>
> 1. delete the dependency on SMP
>
> PADATA only depends on workqueue and completion. It works well with !SMP
> currently but has no performance benefits. What we can do is make PADATA
> handle the non-SMP case more elegantly.
>
> PADATA has two parts: "Running Multithreaded Jobs" and "Running
> Serialized Jobs".
>
> "Running Multithreaded Jobs", which hugetlb parallelization relies on
> can be easily deparallelize through this patch:
>
> ```
> @@ -495,7 +495,7 @@ void __init padata_do_multithreaded(struct padata_mt_job *job)
> nworks = max(job->size / max(job->min_chunk, job->align), 1ul);
> nworks = min(nworks, job->max_threads);
>
> - if (nworks == 1) {
> + if (nworks == 1 || !IS_ENABLED(CONFIG_SMP)) {
> /* Single thread, no coordination needed, cut to the chase. */
> job->thread_fn(job->start, job->start + job->size, job->fn_arg);
> return;
> ```
>
> However, "Running Serialized Jobs" is more challenging due to its
> various workers queuing each other, making it more complex than "Running
> Multithreaded Jobs." I am currently in the process of deciphering the
> code.
Actually, I did not get it. Why the above code cannot work? The above
code already make it serialized in one call, right? What do I miss here?
Thanks.
>
> To eliminate kconfig warnings, other methods could be considered:
>
> 2. Split hugetlb parallelization into a separate kconfig.
> 3. Wrap hugetlb parallelization with SMP or PADATA macros (already ruled out).
> 4. Split PADATA into PADATA_SERIALIZED and PADATA_MULTITHREADED (too heavy).
>
> Anyway, this is only FYI. I will continue exploring how to deparallelize
> "Running Serialized Jobs."
