Re: [PATCH v4 6/7] hugetlb: parallelize 2M hugetlb allocation and initialization

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> On Jan 22, 2024, at 18:12, Gang Li <gang.li@xxxxxxxxx> wrote:
> 
> On 2024/1/22 15:10, Muchun Song wrote:> On 2024/1/18 20:39, Gang Li wrote:
>>> +static void __init hugetlb_alloc_node(unsigned long start, unsigned long end, void *arg)
>>>   {
>>> -    unsigned long i;
>>> +    struct hstate *h = (struct hstate *)arg;
>>> +    int i, num = end - start;
>>> +    nodemask_t node_alloc_noretry;
>>> +    unsigned long flags;
>>> +    int next_node = 0;
>> This should be first_online_node which may be not zero.
> 
> That's right. Thanks!
> 
>>> -    for (i = 0; i < h->max_huge_pages; ++i) {
>>> -        if (!alloc_bootmem_huge_page(h, NUMA_NO_NODE))
>>> +    /* Bit mask controlling how hard we retry per-node allocations.*/
>>> +    nodes_clear(node_alloc_noretry);
>>> +
>>> +    for (i = 0; i < num; ++i) {
>>> +        struct folio *folio = alloc_pool_huge_folio(h, &node_states[N_MEMORY],
>>> +                        &node_alloc_noretry, &next_node);
>>> +        if (!folio)
>>>               break;
>>> +        spin_lock_irqsave(&hugetlb_lock, flags);
>> > I suspect there will more contention on this lock when parallelizing.
> 
> In the worst case, there are only 'numa node number' of threads in
> contention. And in my testing, it doesn't degrade performance, but
> rather improves performance due to the reduced granularity.

So, the performance does not change if you move the lock out of
loop?

> 
>> I want to know why you chose to drop prep_and_add_allocated_folios()
>> call in the original hugetlb_pages_alloc_boot()?
> 
> Splitting him to parallelize hugetlb_vmemmap_optimize_folios.

Unfortunately, HVO should be enabled before pages go to the pool list.

> 
>>> +static unsigned long __init hugetlb_pages_alloc_boot(struct hstate *h)
>>> +{
>>> +    struct padata_mt_job job = {
>>> +        .fn_arg        = h,
>>> +        .align        = 1,
>>> +        .numa_aware    = true
>>> +    };
>>> +
>>> +    job.thread_fn    = hugetlb_alloc_node;
>>> +    job.start    = 0;
>>> +    job.size    = h->max_huge_pages;
>>> +    job.min_chunk    = h->max_huge_pages / num_node_state(N_MEMORY) / 2;
>>> +    job.max_threads    = num_node_state(N_MEMORY) * 2;
>> I am curious the magic number of 2 used in assignments of ->min_chunk
>> and ->max_threads, does it from your experiment? I thinke it should
>> be a comment here.
> 
> This is tested and I can perform more detailed tests and provide data.
> 
>> And I am also sceptical about the optimization for a small amount of
>> allocation of hugepages. Given 4 hugepags needed to be allocated on UMA
>> system, job.min_chunk will be 2, job.max_threads will be 2. Then, 2
>> workers will be scheduled, however each worker will just allocate 2 pages,
>> how much the cost of scheduling? What if allocate 4 pages in single
>> worker? Do you have any numbers on parallelism vs non-parallelism in
>> a small allocation case? If we cannot gain from this case, I think we shold
>> assign a reasonable value to ->min_chunk based on experiment.
>> Thanks.
>> 
> 
> That's a good suggestion, I'll run some tests and choose the best
> values.
> 
> 






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