The Datapath Classifier uses tuple space search for flow classification.
The rules are arranged into a set of tuples/subtables (each with a
distinct mask).  Each subtable is implemented as a hash table and lookup
is done with flow keys formed by selecting the bits from the packet header
based on each subtable's mask. Tuple space search will sequentially search
each subtable until a match is found. With a large number of subtables, a
sequential search of the subtables could consume a lot of CPU cycles. In
a testbench with a uniform traffic pattern equally distributed across 20
subtables, we measured that up to 65% of total execution time is attributed
to the megaflow cache lookup.

This patch presents the idea of the two-layer hierarchical lookup, where a
low overhead first level of indirection is accessed first, we call this
level cuckoo distributor (CD). If a flow key has been inserted in the flow
table the first level will indicate with high probability that which
subtable to look into. A lookup is performed on the second level (the
target subtable) to retrieve the result. If the key doesn’t have a match,
then we revert back to the sequential search of subtables. The patch is
partially inspired by earlier concepts proposed in "simTable"[1] and
"Cuckoo Filter"[2], and DPDK's Cuckoo Hash implementation.

This patch can improve the already existing Subtable Ranking when traffic
data has high entropy. Subtable Ranking helps minimize the number of
traversed subtables when most of the traffic hit the same subtable.
However, in the case of high entropy traffic such as traffic coming from
a physical port, multiple subtables could be hit with a similar frequency.
In this case the average subtable lookups per hit would be much greater
than 1. In addition, CD can adaptively turn off when it finds the traffic
mostly hit one subtable. Thus, CD will not be an overhead when Subtable
Ranking works well.

Scheme:
CD is in front of the subtables. Packets are directed to corresponding subtable
if hit in CD instead of searching each subtable sequentially.
 -------
|  CD   |
 -------
       \
        \
 -----  -----     -----
|sub  ||sub  |...|sub  |
|table||table|   |table|
 -----  -----     -----

 Evaluation:
 ----------
We create a set of rules with various src IP. We feed traffic containing various
numbers of flows with various src IP and dst IP. All the flows hit 10/20/30
rules creating 10/20/30 subtables. We will explain the rule/traffic setup
in detail later.

The table below shows the preliminary continuous testing results (full line
speed test) we collected with a uni-directional phy-to-phy setup. OvS
runs with 1 PMD. We use Spirent as the hardware traffic generator.

 Before v2 rebase:
 ----
AVX2 data:
20k flows:
no.subtable: 10          20          30
cd-ovs       4267332     3478251     3126763
orig-ovs     3260883     2174551     1689981
speedup      1.31x       1.60x       1.85x

100k flows:
no.subtable: 10          20          30
cd-ovs       4015783     3276100     2970645
orig-ovs     2692882     1711955     1302321
speedup      1.49x       1.91x       2.28x

1M flows:
no.subtable: 10          20          30
cd-ovs       3895961     3170530     2968555
orig-ovs     2683455     1646227     1240501
speedup      1.45x       1.92x       2.39x

Scalar data:
1M flows:
no.subtable: 10          20          30
cd-ovs       3658328     3028111     2863329
orig_ovs     2683455     1646227     1240501
speedup      1.36x       1.84x       2.31x

 After v2 rebase:
 ----
After rebase for v1, we tested 1M flows, 20 table cases, the results still hold.
1M flows:
no.subtable:   20
cd-ovs         3066483
orig-ovs       1588049
speedup        1.93x


 Test rules/traffic setup:
 ----
To setup a test case with 20 subtables, the rule set we use is like below:
tcp,nw_src=1.0.0.0/8, actions=output:1
udp,nw_src=2.0.0.0/9, actions=output:1
udp,nw_src=3.0.0.0/10,actions=output:1
udp,nw_src=4.0.0.0/11,actions=output:1
...
udp,nw_src=18.0.0.0/25,actions=output:1
udp,nw_src=19.0.0.0/26,actions=output:1
udp,nw_src=20.0.0.0/27,actions=output:1

Then for the traffic generator, we generate corresponding traffics with
src_ip varying from 1.0.0.0 to 20.0.0.0. For each src_ip, we change
dst_ip for 50000 different values. This will effectively generate 1M
different flows hitting the 20 rules we created. And because the different
wildcarding bits in nw_src, the 20 rules will belong to 20 subtables.
We use 64 Bytes packet across all tests.

How to check if CD works or not for your use case:
 ----
CD cannot improve throughput for all use cases. It targets on use cases when
multiple subtables exist and when the top-ranked subtable is not hit by the
vast majority of the traffic.

One can use $OVS_DIR/utilities/ovs-appctl dpif-netdev/pmd-stats-show
command to check CD statistics: hit/miss.
Another statistic also shown is: "avg. subtable lookups per hit".
In our test case, the original OvS will have an average subtable lookups value
as 10, because there are in total of 20 subtables, and on average, a hit happens
after iterating half of them. In such case, iterating 10 subtables are
very expensive.

By using CD, this value will be close to 1, which means on average only 1
subtable needs to be iterated to hit the rule, which reduces a lot of overhead.

Other statistics to notice about is "megaflow hits" and "emc hits".
If most packets hit EMC, CD does not improve much of the throughput
since CD is used to optimize megaflow search instead of EMC lookup. If your test
case has less than 8k flows, all of them may be EMC hit.

Note that CD is adaptively turned on/off according to the number of subtables 
and
their iterated pattern. If it finds there is not much benefit, CD will turn off
itself automatically.


 References:
 ----------
[1] H. Lee and B. Lee, Approaches for improving tuple space search-based
table lookup, ICTC '15
[2] B. Fan, D. G. Andersen, M. Kaminsky, and M. D. Mitzenmacher,
Cuckoo Filter: Practically Better Than Bloom, CoNEXT '14

The previous RFC on mailing list are at:
https://mail.openvswitch.org/pipermail/ovs-dev/2017-April/330570.html

v2: Rebase to master head.
    Add more testing details in cover letter.
    Change commit messages.
    Minor style changes to code.
    Fix build errors happens without AVX and DPDK library.

Yipeng Wang (5):
  dpif-netdev: Basic CD feature with scalar lookup.
  dpif-netdev: Add AVX2 implementation for CD lookup.
  dpif-netdev: Add CD statistics
  dpif-netdev: Add adaptive CD mechanism
  unit-test: Add a delay for CD initialization.

 lib/dpif-netdev.c     | 567 +++++++++++++++++++++++++++++++++++++++++++++++++-
 tests/ofproto-dpif.at |   3 +
 2 files changed, 560 insertions(+), 10 deletions(-)

-- 
2.7.4

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