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Re: [Qemu-devel] [PATCH v6 08/15] qdist: add module to represent frequen
From: |
Emilio G. Cota |
Subject: |
Re: [Qemu-devel] [PATCH v6 08/15] qdist: add module to represent frequency distributions of data |
Date: |
Mon, 6 Jun 2016 19:40:14 -0400 |
User-agent: |
Mutt/1.5.23 (2014-03-12) |
On Fri, Jun 03, 2016 at 20:46:07 +0300, Sergey Fedorov wrote:
> On 03/06/16 20:29, Sergey Fedorov wrote:
> > On 03/06/16 20:22, Emilio G. Cota wrote:
> >> On Sat, May 28, 2016 at 21:15:06 +0300, Sergey Fedorov wrote:
> >>> On 25/05/16 04:13, Emilio G. Cota wrote:
> >>> (snip)
> >>>> +double qdist_avg(const struct qdist *dist)
> >>>> +{
> >>>> + unsigned long count;
> >>>> + size_t i;
> >>>> + double ret = 0;
> >>>> +
> >>>> + count = qdist_sample_count(dist);
> >>>> + if (!count) {
> >>>> + return NAN;
> >>>> + }
> >>>> + for (i = 0; i < dist->n; i++) {
> >>>> + struct qdist_entry *e = &dist->entries[i];
> >>>> +
> >>>> + ret += e->x * e->count / count;
> >>> Please use Welford’s method or something like that, see
> >>> http://stackoverflow.com/a/1346890.
> >> Yes, the way the mean is computed right now, we might suffer
> >> from underflow if count is huge. But I'd rather take that, than the
> >> perf penalty of an iterative method (such as the one used
> >> in Welford's). Note that we might have huge amounts of
> >> items, e.g. one item per head bucket in qht's occupancy qdist
> >> (and 0.5M head buckets is easy to achieve).
> >>
> >> If we were to use an iterative method, we'd need to do something
> >> like:
> >>
> >> double qdist_avg(const struct qdist *dist)
> >> {
> >> size_t i, j;
> >> double ret = 0;
> >>
> >> if (!qdist_sample_count(dist)) {
> >> return NAN;
> >> }
> >> /* compute moving average to prevent under/overflow */
> >> for (i = 0; i < dist->n; i++) {
> >> struct qdist_entry *e = &dist->entries[i];
> >>
> >> for (j = 0; j < e->count; j++) {
> >>
> >> ret += (e->x - ret) / (i + j + 1);
> >> }
> >> }
> >> return ret;
> >> }
> >>
> >> Note that skipping the inner loop would be incorrect.
> > Ah, it's a shame. I'm wondering if there is some other algorithm that
> > could work for us?
>
> Maybe something like
> https://en.wikipedia.org/wiki/Kahan_summation_algorithm could help?
That algorithm is overkill for what we're doing. Pairwise summation
should suffice:
diff --git a/util/qdist.c b/util/qdist.c
index 3343640..909bd2b 100644
--- a/util/qdist.c
+++ b/util/qdist.c
@@ -367,20 +367,34 @@ unsigned long qdist_sample_count(const struct qdist *dist)
return count;
}
+static double qdist_pairwise_avg(const struct qdist *dist, size_t index,
+ size_t n, unsigned long count)
+{
+ if (n <= 2) {
+ size_t i;
+ double ret = 0;
+
+ for (i = 0; i < n; i++) {
+ struct qdist_entry *e = &dist->entries[index + i];
+
+ ret += e->x * e->count / count;
+ }
+ return ret;
+ } else {
+ size_t n2 = n / 2;
+
+ return qdist_pairwise_avg(dist, index, n2, count) +
+ qdist_pairwise_avg(dist, index + n2, n - n2, count);
+ }
+}
+
double qdist_avg(const struct qdist *dist)
{
unsigned long count;
- size_t i;
- double ret = 0;
count = qdist_sample_count(dist);
if (!count) {
return NAN;
}
- for (i = 0; i < dist->n; i++) {
- struct qdist_entry *e = &dist->entries[i];
-
- ret += e->x * e->count / count;
- }
- return ret;
+ return qdist_pairwise_avg(dist, 0, dist->n, count);
}
Emilio