Re: [RFC PATCH 0/3] Weight-balanced binary tree + KVM growablememory slots using wbtree
From: Alex Williamson
Date: Mon Feb 28 2011 - 18:04:39 EST
On Sun, 2011-02-27 at 11:54 +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.
It seems like we need a good mixed workload benchmark. So far we've
only tested worst case, with a pure emulated I/O test, and best case,
with a pure memory test. Ordering an array only helps the latter, and
only barely beats the tree, so I suspect overall performance would be
better with a tree.
> > 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
The tree is obviously the most time and space efficient for this and the
netperf results show a pretty clear win here. I think it's really only
a question of whether we'd be ok with slow, cache thrashing, searches
here if we could effectively cache the result for next time as you've
suggested. Even then, it seems like steady state performance would be
prone to unusual slowdowns (ex. have to flush sptes on every add, what's
the regeneration time to replace all those slow lookups?).
> - hit into the RAM slots
It's really just the indirection of the tree and slightly larger element
size that gives the sorted array an edge here.
> - hit into the other slots (trailing far behind)
Obviously an array sucks at this.
> 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
Suggestions for a mixed workload benchmark? What else would you like to
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