bpf/benchs: Add benchmarks for comparing hashmap lookups w/ vs. w/out bloom filter

bpf/benchs: Add benchmarks for comparing hashmap lookups w/ vs. w/out bloom filter

This patch adds benchmark tests for comparing the performance of hashmap
lookups without the bloom filter vs. hashmap lookups with the bloom filter.

Checking the bloom filter first for whether the element exists should
overall enable a higher throughput for hashmap lookups, since if the
element does not exist in the bloom filter, we can avoid a costly lookup in
the hashmap.

On average, using 5 hash functions in the bloom filter tended to perform
the best across the widest range of different entry sizes. The benchmark
results using 5 hash functions (running on 8 threads on a machine with one
numa node, and taking the average of 3 runs) were roughly as follows:

value_size = 4 bytes -
	10k entries: 30% faster
	50k entries: 40% faster
	100k entries: 40% faster
	500k entres: 70% faster
	1 million entries: 90% faster
	5 million entries: 140% faster

value_size = 8 bytes -
	10k entries: 30% faster
	50k entries: 40% faster
	100k entries: 50% faster
	500k entres: 80% faster
	1 million entries: 100% faster
	5 million entries: 150% faster

value_size = 16 bytes -
	10k entries: 20% faster
	50k entries: 30% faster
	100k entries: 35% faster
	500k entres: 65% faster
	1 million entries: 85% faster
	5 million entries: 110% faster

value_size = 40 bytes -
	10k entries: 5% faster
	50k entries: 15% faster
	100k entries: 20% faster
	500k entres: 65% faster
	1 million entries: 75% faster
	5 million entries: 120% faster

Signed-off-by: Joanne Koong <joannekoong@fb.com>
Signed-off-by: Alexei Starovoitov <ast@kernel.org>
Link: https://lore.kernel.org/bpf/20211027234504.30744-6-joannekoong@fb.com