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bpf: optimize hashmap lookups when key_size is divisible by 4
The BPF hashmap uses the jhash() hash function. There is an optimized version of this hash function which may be used if hash size is a multiple of 4. Apply this optimization to the hashmap in a similar way as it is done in the bloom filter map. On practice the optimization is only noticeable for smaller key sizes, which, however, is sufficient for many applications. An example is listed in the following table of measurements (a hashmap of 65536 elements was used): -------------------------------------------------------------------- | key_size | fullness | lookups /sec | lookups (opt) /sec | gain | -------------------------------------------------------------------- | 4 | 25% | 42.990M | 46.000M | 7.0% | | 4 | 50% | 37.910M | 39.094M | 3.1% | | 4 | 75% | 34.486M | 36.124M | 4.7% | | 4 | 100% | 31.760M | 32.719M | 3.0% | -------------------------------------------------------------------- | 8 | 25% | 43.855M | 49.626M | 13.2% | | 8 | 50% | 38.328M | 42.152M | 10.0% | | 8 | 75% | 34.483M | 38.088M | 10.5% | | 8 | 100% | 31.306M | 34.686M | 10.8% | -------------------------------------------------------------------- | 12 | 25% | 38.398M | 43.770M | 14.0% | | 12 | 50% | 33.336M | 37.712M | 13.1% | | 12 | 75% | 29.917M | 34.440M | 15.1% | | 12 | 100% | 27.322M | 30.480M | 11.6% | -------------------------------------------------------------------- | 16 | 25% | 41.491M | 41.921M | 1.0% | | 16 | 50% | 36.206M | 36.474M | 0.7% | | 16 | 75% | 32.529M | 33.027M | 1.5% | | 16 | 100% | 29.581M | 30.325M | 2.5% | -------------------------------------------------------------------- | 20 | 25% | 34.240M | 36.787M | 7.4% | | 20 | 50% | 30.328M | 32.663M | 7.7% | | 20 | 75% | 27.536M | 29.354M | 6.6% | | 20 | 100% | 24.847M | 26.505M | 6.7% | -------------------------------------------------------------------- | 24 | 25% | 36.329M | 40.608M | 11.8% | | 24 | 50% | 31.444M | 35.059M | 11.5% | | 24 | 75% | 28.426M | 31.452M | 10.6% | | 24 | 100% | 26.278M | 28.741M | 9.4% | -------------------------------------------------------------------- | 28 | 25% | 31.540M | 31.944M | 1.3% | | 28 | 50% | 27.739M | 28.063M | 1.2% | | 28 | 75% | 24.993M | 25.814M | 3.3% | | 28 | 100% | 23.513M | 23.500M | -0.1% | -------------------------------------------------------------------- | 32 | 25% | 32.116M | 33.953M | 5.7% | | 32 | 50% | 28.879M | 29.859M | 3.4% | | 32 | 75% | 26.227M | 26.948M | 2.7% | | 32 | 100% | 23.829M | 24.613M | 3.3% | -------------------------------------------------------------------- | 64 | 25% | 22.535M | 22.554M | 0.1% | | 64 | 50% | 20.471M | 20.675M | 1.0% | | 64 | 75% | 19.077M | 19.146M | 0.4% | | 64 | 100% | 17.710M | 18.131M | 2.4% | -------------------------------------------------------------------- The following script was used to gather the results (SMT & frequency off): cd tools/testing/selftests/bpf for key_size in 4 8 12 16 20 24 28 32 64; do for nr_entries in `seq 16384 16384 65536`; do fullness=$(printf '%3s' $((nr_entries*100/65536))) echo -n "key_size=$key_size: $fullness% full: " sudo ./bench -d2 -a bpf-hashmap-lookup --key_size=$key_size --nr_entries=$nr_entries --max_entries=65536 --nr_loops=2000000 --map_flags=0x40 | grep cpu done echo done Signed-off-by: Anton Protopopov <aspsk@isovalent.com> Link: https://lore.kernel.org/r/20230401200602.3275-1-aspsk@isovalent.com Signed-off-by: Alexei Starovoitov <ast@kernel.org>
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@ -607,6 +607,8 @@ free_htab:
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static inline u32 htab_map_hash(const void *key, u32 key_len, u32 hashrnd)
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{
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if (likely(key_len % 4 == 0))
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return jhash2(key, key_len / 4, hashrnd);
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return jhash(key, key_len, hashrnd);
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}
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