Re: [RFC PATCH 0/3] Weight-balanced binary tree + KVM growable memoryslots using wbtree

[Avi Kivity]

On 03/01/2011 09:47 PM, Marcelo Tosatti wrote:
> On Sun, Feb 27, 2011 at 11:54:29AM +0200, Avi Kivity wrote:
> >  On 02/24/2011 07:35 PM, Alex Williamson wrote:
> >  >On Thu, 2011-02-24 at 12:06 +0200, Avi Kivity wrote:
> >  >>   On 02/23/2011 09:28 PM, Alex Williamson wrote:
> >  >>   >   I had forgotten about<1M mem, so actually the slot configuration was:
> >  >>   >
> >  >>   >   0:<1M
> >  >>   >   1: 1M - 3.5G
> >  >>   >   2: 4G+
> >  >>   >
> >  >>   >   I stacked the deck in favor of the static array (0: 4G+, 1: 1M-3.5G, 2:
> >  >>   >   <1M), and got these kernbench results:
> >  >>   >
> >  >>   >                base (stdev)    reorder (stdev)   wbtree (stdev)
> >  >>   >   --------+-----------------+----------------+----------------+
> >  >>   >   Elapsed |  42.809 (0.19)  |  42.160 (0.22) |  42.305 (0.23) |
> >  >>   >   User    | 115.709 (0.22)  | 114.358 (0.40) | 114.720 (0.31) |
> >  >>   >   System  |  41.605 (0.14)  |  40.741 (0.22) |  40.924 (0.20) |
> >  >>   >   %cpu    |   366.9 (1.45)  |   367.4 (1.17) |   367.6 (1.51) |
> >  >>   >   context |  7272.3 (68.6)  |  7248.1 (89.7) |  7249.5 (97.8) |
> >  >>   >   sleeps  | 14826.2 (110.6) | 14780.7 (86.9) | 14798.5 (63.0) |
> >  >>   >
> >  >>   >   So, wbtree is only slightly behind reordering, and the standard
> >  >>   >   deviation suggests the runs are mostly within the noise of each other.
> >  >>   >   Thanks,
> >  >>
> >  >>   Doesn't this indicate we should use reordering, instead of a new data
> >  >>   structure?
> >  >
> >  >The original problem that brought this on was scaling.  The re-ordered
> >  >array still has O(N) scaling while the tree should have ~O(logN) (note
> >  >that it currently doesn't because it needs a compaction algorithm added
> >  >after insert and remove).  So yes, it's hard to beat the results of a
> >  >test that hammers on the first couple entries of a sorted array, but I
> >  >think the tree has better than current performance and more predictable
> >  >when scaled performance.
> >
> >  Scaling doesn't matter, only actual performance.  Even a guest with
> >  512 slots would still hammer only on the first few slots, since
> >  these will contain the bulk of memory.
> >
> >  >If we knew when we were searching for which type of data, it would
> >  >perhaps be nice if we could use a sorted array for guest memory (since
> >  >it's nicely bounded into a small number of large chunks), and a tree for
> >  >mmio (where we expect the scaling to be a factor).  Thanks,
> >
> >  We have three types of memory:
> >
> >  - RAM - a few large slots
> >  - mapped mmio (for device assignment) - possible many small slots
> >  - non-mapped mmio (for emulated devices) - no slots
> >
> >  The first two are handled in exactly the same way - they're just
> >  memory slots.  We expect a lot more hits into the RAM slots, since
> >  they're much bigger.  But by far the majority of faults will be for
> >  the third category - mapped memory will be hit once per page, then
> >  handled by hardware until Linux memory management does something
> >  about the page, which should hopefully be rare (with device
> >  assignment, rare == never, since those pages are pinned).
> >
> >  Therefore our optimization priorities should be
> >  - complete miss into the slot list
> >  - hit into the RAM slots
> >  - hit into the other slots (trailing far behind)
>
> Whatever ordering considered optimal in one workload can be suboptimal
> in another. The binary search reduces the number of slots inspected
> in the average case. Using slot size as weight favours probability.

It's really difficult to come up with a workload that causes many hits 
to small slots.

> >  Of course worst-case performance matters.  For example, we might
> >  (not sure) be searching the list with the mmu spinlock held.
> >
> >  I think we still have a bit to go before we can justify the new data
> >  structure.
>
> Intensive IDE disk IO on guest with lots of assigned network devices, 3%
> improvement on netperf with rtl8139, 1% improvement on kernbench?
>
> Fail to see justification for not using it.

By itself it's great, but the miss cache will cause the code to be 
called very rarely.  So I prefer the sorted array which is simpler (and 
faster for the few-large-slots case).

--
error compiling committee.c: too many arguments to function

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