Martin KaFai Lau wrote: > On Tue, Jun 21, 2022 at 10:49:46PM -0700, John Fastabend wrote: > > Martin KaFai Lau wrote: > > > On Tue, Jun 21, 2022 at 12:17:54PM -0700, John Fastabend wrote: > > > > > Hashmap Control > > > > > =============== > > > > > num keys: 10 > > > > > hashmap (control) sequential get: hits throughput: 20.900 ± 0.334 M ops/s, hits latency: 47.847 ns/op, important_hits throughput: 20.900 ± 0.334 M ops/s > > > > > > > > > > num keys: 1000 > > > > > hashmap (control) sequential get: hits throughput: 13.758 ± 0.219 M ops/s, hits latency: 72.683 ns/op, important_hits throughput: 13.758 ± 0.219 M ops/s > > > > > > > > > > num keys: 10000 > > > > > hashmap (control) sequential get: hits throughput: 6.995 ± 0.034 M ops/s, hits latency: 142.959 ns/op, important_hits throughput: 6.995 ± 0.034 M ops/s > > > > > > > > > > num keys: 100000 > > > > > hashmap (control) sequential get: hits throughput: 4.452 ± 0.371 M ops/s, hits latency: 224.635 ns/op, important_hits throughput: 4.452 ± 0.371 M ops/s > > > > > > > > > > num keys: 4194304 > > > > > hashmap (control) sequential get: hits throughput: 3.043 ± 0.033 M ops/s, hits latency: 328.587 ns/op, important_hits throughput: 3.043 ± 0.033 M ops/s > > > > > > > > > > > > > Why is the hashmap lookup not constant with the number of keys? It looks > > > > like its prepopulated without collisions so I wouldn't expect any > > > > extra ops on the lookup side after looking at the code quickly. > > > It may be due to the cpu-cache misses as the map grows. > > > > Maybe but, values are just ints so even 1k * 4B = 4kB should be > > inside an otherwise unused server class system. Would be more > > believable (to me at least) if the drop off happened at 100k or > > more. > It is not only value (and key) size. There is overhead. > htab_elem alone is 48bytes. key and value need to 8bytes align also. > Right late night math didn't add up. Now I'm wondering if we can make hashmap behave much better, that drop off is looking really ugly. > From a random machine: > lscpu -C > NAME ONE-SIZE ALL-SIZE WAYS TYPE LEVEL SETS PHY-LINE COHERENCY-SIZE > L1d 32K 576K 8 Data 1 64 1 64 > L1i 32K 576K 8 Instruction 1 64 1 64 > L2 1M 18M 16 Unified 2 1024 1 64 > L3 24.8M 24.8M 11 Unified 3 36864 1 64 Could you do a couple more data point then, num keys=100,200,400? I would expect those to fit in the cache and be same as 10 by the cache theory. I could try as well but looking like Friday before I have a spare moment. Thanks, John
