HugePage by default

[Xin Tong]

just to clarify. I am doing this for the possibility of a research project.
the feeling is that maybe 4KB is no longer the best page size. here is what
i wrote sometime ago.

"Memory size has increased significantly since the introduction of the X86
virtual memory system in 1985. However, the size of a page has stayed at
4KB. Most virtual memory systems make use of Translation Look-aside Buffer
to reduce the cost of translation.  Due to the fact that TLB sits in the
critical path of every memory access, its size is limited by its strict
latency requirement. Over the years, the size of the L1 TLB has stayed well
below 256 entries in most commercial processors."​


On Wed, Jul 30, 2014 at 7:49 PM, Xin Tong <trent.tong at gmail.com> wrote:

> ​​
> How bad is the internal fragmentation going to be if 2M pages are used ?
> some of the small vmas are stack, shared libraries and user mmapped files.
> I assume heap is going to be 2M at least, which is somewhat reasonable.
>
> shared library vmas can be merged to form large vmas as they have the same
> permission mostly. only one stack is needed per thread. I think the big
> culprit for internal fragmentation here is the user mmaped files.
>
> Am i right to think as above ?
>
> Xin
> On Wed, Jul 30, 2014 at 7:26 PM, <Valdis.Kletnieks at vt.edu> wrote:
>
>> On Wed, 30 Jul 2014 18:26:39 -0500, Xin Tong said:
>>
>> > I am planning to use this only for workloads with very large memory
>> > footprints, e.g. hadoop, tpcc, etc.
>>
>> You might want to look at how your system gets booted.  I think you'll
>> find
>> that you burn through 800 to 2000 or so processes, all of which are
>> currently
>> tiny, but if you make every 4K allocation grab 2M instead, you're quite
>> likely
>> to find yourself tripping the OOM before hadoop ever gets launched.
>>
>> You're probably *much* better off letting the current code do its work,
>> since you'll only pay the coalesce cost once for each 2M that hadoop uses.
>> And let's face it, that's only going to sum up to fractions of a second,
>> and
>> then hadoop is going to be banging on the TLB for hours or days.
>>
>> Don't spend time optimizing the wrong thing....
>>
>
>
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