Merge into master from pull request #155:
Replace flowtable module with new tcam module (https://github.com/floodlight/ivs/pull/155)
update bigcode

* submodules/bigcode 53b1a99...a0fd12e (3):
  > Merge into master from pull request #23: add bloom_filter module (https://github.com/floodlight/bigcode/pull/23)
  > Merge into master from pull request #21: PIMU: Change pps from uint32_t to double. (https://github.com/floodlight/bigcode/pull/21)
  > Merge into master from pull request #22: incremental murmur hash (https://github.com/floodlight/bigcode/pull/22)
update indigo

* submodules/indigo 25f27e9...2eba645 (1):
  > Merge into master from pull request #129: OFConnectionManager: reject OF_BSN_SET_SWITCH_PIPELINE_REQUEST from a slave (https://github.com/floodlight/indigo/pull/129)
update loxigen-artifacts

* submodules/loxigen-artifacts fc5b8fe...316a4c3 (3):
  > Artifacts from https://github.com/floodlight/loxigen/compare/43ee9a83c29119ee84931bb85275eeda07cf2f75...a5f488a034bcf3815716be675e071c87f3e7973b
  > Artifacts from https://github.com/floodlight/loxigen/compare/c77bebf074d5737483a133962725a8181ffdd2b8...43ee9a83c29119ee84931bb85275eeda07cf2f75
  > Artifacts from https://github.com/floodlight/loxigen/compare/feffbeb20c838ffeba38c71daec4d834cfb37900...c77bebf074d5737483a133962725a8181ffdd2b8
update switchlight-common

* submodules/switchlight-common 3ecdd97...9b94b93 (2):
  > Merge into master from pull request #52: add traceroute support for icmpa (https://github.com/floodlight/switchlight-common/pull/52)
  > Merge into master from pull request #47: Bigtap Arp Agent (https://github.com/floodlight/switchlight-common/pull/47)
Merge into master from pull request #156:
update submodules (https://github.com/floodlight/ivs/pull/156)
tcam: fuse masking and memcmp/murmur

Uses the new incremental hash functions. The main win is in skipping words
where the mask is zero.

Reduces time per lookup by 20% in the benchmark.
tcam: use bloom_filter module

The assumption is that most lookups in individual shards fail, so we should
make that case faster at the expense of successful lookups. The Bloom filter
uses 2 cache lines (1 per probe) to do a lookup. The hashtable also uses 2
cache lines (bucket head and (in expectation) one node). The difference is the
total number of cachelines used: n/64 for the Bloom filter, and 1.13*n for the
hashtable. Using fewer cachelines makes it more likely that the ones we need
will be already in the cache when we do a lookup.

Reduces time per lookup by 36% in the benchmark. When running benchmarks that
don't fit in L3 cache (200000 flows) this increases to 60%. In practice I
expect the speedup to be somewhere in between because other parts of the switch
(and other processes) are contending for cache space.