kernel/linux.git/tools/testing/selftests/bpf/bench.c, branch v6.4

selftests/bpf: Add bench for task storage creation

2023-03-26T02:52:52+00:00

This patch adds a task storage benchmark to the existing local-storage-create benchmark. For task storage, ./bench --storage-type task --batch-size 32: bpf_ma: Summary: creates 30.456 ± 0.507k/s ( 30.456k/prod), 6.08 kmallocs/create no bpf_ma: Summary: creates 31.962 ± 0.486k/s ( 31.962k/prod), 6.13 kmallocs/create ./bench --storage-type task --batch-size 64: bpf_ma: Summary: creates 30.197 ± 1.476k/s ( 30.197k/prod), 6.08 kmallocs/create no bpf_ma: Summary: creates 31.103 ± 0.297k/s ( 31.103k/prod), 6.13 kmallocs/create Signed-off-by: Martin KaFai Lau Link: https://lore.kernel.org/r/20230322215246.1675516-6-martin.lau@linux.dev Signed-off-by: Alexei Starovoitov

selftests/bpf: Add local-storage-create benchmark

2023-03-10T19:06:02+00:00

This patch tests how many kmallocs is needed to create and free a batch of UDP sockets and each socket has a 64bytes bpf storage. It also measures how fast the UDP sockets can be created. The result is from my qemu setup. Before bpf_mem_cache_alloc/free: ./bench -p 1 local-storage-create Setting up benchmark 'local-storage-create'... Benchmark 'local-storage-create' started. Iter 0 ( 73.193us): creates 213.552k/s (213.552k/prod), 3.09 kmallocs/create Iter 1 (-20.724us): creates 211.908k/s (211.908k/prod), 3.09 kmallocs/create Iter 2 ( 9.280us): creates 212.574k/s (212.574k/prod), 3.12 kmallocs/create Iter 3 ( 11.039us): creates 213.209k/s (213.209k/prod), 3.12 kmallocs/create Iter 4 (-11.411us): creates 213.351k/s (213.351k/prod), 3.12 kmallocs/create Iter 5 ( -7.915us): creates 214.754k/s (214.754k/prod), 3.12 kmallocs/create Iter 6 ( 11.317us): creates 210.942k/s (210.942k/prod), 3.12 kmallocs/create Summary: creates 212.789 ± 1.310k/s (212.789k/prod), 3.12 kmallocs/create After bpf_mem_cache_alloc/free: ./bench -p 1 local-storage-create Setting up benchmark 'local-storage-create'... Benchmark 'local-storage-create' started. Iter 0 ( 68.265us): creates 243.984k/s (243.984k/prod), 1.04 kmallocs/create Iter 1 ( 30.357us): creates 238.424k/s (238.424k/prod), 1.04 kmallocs/create Iter 2 (-18.712us): creates 232.963k/s (232.963k/prod), 1.04 kmallocs/create Iter 3 (-15.885us): creates 238.879k/s (238.879k/prod), 1.04 kmallocs/create Iter 4 ( 5.590us): creates 237.490k/s (237.490k/prod), 1.04 kmallocs/create Iter 5 ( 8.577us): creates 237.521k/s (237.521k/prod), 1.04 kmallocs/create Iter 6 ( -6.263us): creates 238.508k/s (238.508k/prod), 1.04 kmallocs/create Summary: creates 237.298 ± 2.198k/s (237.298k/prod), 1.04 kmallocs/create Signed-off-by: Martin KaFai Lau Link: https://lore.kernel.org/r/20230308065936.1550103-18-martin.lau@linux.dev Signed-off-by: Alexei Starovoitov

selftest/bpf/benchs: Add benchmark for hashmap lookups

2023-02-16T00:29:31+00:00

Add a new benchmark which measures hashmap lookup operations speed. A user can control the following parameters of the benchmark: * key_size (max 1024): the key size to use * max_entries: the hashmap max entries * nr_entries: the number of entries to insert/lookup * nr_loops: the number of loops for the benchmark * map_flags The hashmap flags passed to BPF_MAP_CREATE The BPF program performing the benchmarks calls two nested bpf_loop: bpf_loop(nr_loops/nr_entries) bpf_loop(nr_entries) bpf_map_lookup() So the nr_loops determines the number of actual map lookups. All lookups are successful. Example (the output is generated on a AMD Ryzen 9 3950X machine): for nr_entries in `seq 4096 4096 65536`; do echo -n "$((nr_entries*100/65536))% full: "; sudo ./bench -d2 -a bpf-hashmap-lookup --key_size=4 --nr_entries=$nr_entries --max_entries=65536 --nr_loops=1000000 --map_flags=0x40 | grep cpu; done 6% full: cpu01: lookup 50.739M ± 0.018M events/sec (approximated from 32 samples of ~19ms) 12% full: cpu01: lookup 47.751M ± 0.015M events/sec (approximated from 32 samples of ~20ms) 18% full: cpu01: lookup 45.153M ± 0.013M events/sec (approximated from 32 samples of ~22ms) 25% full: cpu01: lookup 43.826M ± 0.014M events/sec (approximated from 32 samples of ~22ms) 31% full: cpu01: lookup 41.971M ± 0.012M events/sec (approximated from 32 samples of ~23ms) 37% full: cpu01: lookup 41.034M ± 0.015M events/sec (approximated from 32 samples of ~24ms) 43% full: cpu01: lookup 39.946M ± 0.012M events/sec (approximated from 32 samples of ~25ms) 50% full: cpu01: lookup 38.256M ± 0.014M events/sec (approximated from 32 samples of ~26ms) 56% full: cpu01: lookup 36.580M ± 0.018M events/sec (approximated from 32 samples of ~27ms) 62% full: cpu01: lookup 36.252M ± 0.012M events/sec (approximated from 32 samples of ~27ms) 68% full: cpu01: lookup 35.200M ± 0.012M events/sec (approximated from 32 samples of ~28ms) 75% full: cpu01: lookup 34.061M ± 0.009M events/sec (approximated from 32 samples of ~29ms) 81% full: cpu01: lookup 34.374M ± 0.010M events/sec (approximated from 32 samples of ~29ms) 87% full: cpu01: lookup 33.244M ± 0.011M events/sec (approximated from 32 samples of ~30ms) 93% full: cpu01: lookup 32.182M ± 0.013M events/sec (approximated from 32 samples of ~31ms) 100% full: cpu01: lookup 31.497M ± 0.016M events/sec (approximated from 32 samples of ~31ms) Signed-off-by: Anton Protopopov Signed-off-by: Andrii Nakryiko Link: https://lore.kernel.org/bpf/20230213091519.1202813-8-aspsk@isovalent.com

selftest/bpf/benchs: Print less if the quiet option is set

2023-02-16T00:29:31+00:00

The bench utility will print Setting up benchmark ''... Benchmark '' started. on startup to stdout. Suppress this output if --quiet option if given. This makes it simpler to parse benchmark output by a script. Signed-off-by: Anton Protopopov Signed-off-by: Andrii Nakryiko Link: https://lore.kernel.org/bpf/20230213091519.1202813-7-aspsk@isovalent.com

selftest/bpf/benchs: Make quiet option common

2023-02-16T00:29:31+00:00

The "local-storage-tasks-trace" benchmark has a `--quiet` option. Move it to the list of common options, so that the main code and other benchmarks can use (new) env.quiet variable. Patch the run_bench_local_storage_rcu_tasks_trace.sh helper script accordingly. Signed-off-by: Anton Protopopov Signed-off-by: Andrii Nakryiko Link: https://lore.kernel.org/bpf/20230213091519.1202813-6-aspsk@isovalent.com

selftest/bpf/benchs: Enhance argp parsing

2023-02-16T00:29:31+00:00

To parse command line the bench utility uses the argp_parse() function. This function takes as an argument a parent 'struct argp' structure which defines common command line options and an array of children 'struct argp' structures which defines additional command line options for particular benchmarks. This implementation doesn't allow benchmarks to share option names, e.g., if two benchmarks want to use, say, the --option option, then only one of them will succeed (the first one encountered in the array). This will be convenient if same option names could be used in different benchmarks (with the same semantics, e.g., --nr_loops=N). Fix this by calling the argp_parse() function twice. The first call is the same as it was before, with all children argps, and helps to find the benchmark name and to print a combined help message if anything is wrong. Given the name, we can call the argp_parse the second time, but now the children array points only to a correct benchmark thus always calling the correct parsers. (If there's no a specific list of arguments, then only one call to argp_parse will be done.) Signed-off-by: Anton Protopopov Signed-off-by: Andrii Nakryiko Link: https://lore.kernel.org/bpf/20230213091519.1202813-4-aspsk@isovalent.com

selftests/bpf: Add benchmark for local_storage RCU Tasks Trace usage

2022-07-07T14:35:21+00:00

This benchmark measures grace period latency and kthread cpu usage of RCU Tasks Trace when many processes are creating/deleting BPF local_storage. Intent here is to quantify improvement on these metrics after Paul's recent RCU Tasks patches [0]. Specifically, fork 15k tasks which call a bpf prog that creates/destroys task local_storage and sleep in a loop, resulting in many call_rcu_tasks_trace calls. To determine grace period latency, trace time elapsed between rcu_tasks_trace_pregp_step and rcu_tasks_trace_postgp; for cpu usage look at rcu_task_trace_kthread's stime in /proc/PID/stat. On my virtualized test environment (Skylake, 8 cpus) benchmark results demonstrate significant improvement: BEFORE Paul's patches: SUMMARY tasks_trace grace period latency avg 22298.551 us stddev 1302.165 us SUMMARY ticks per tasks_trace grace period avg 2.291 stddev 0.324 AFTER Paul's patches: SUMMARY tasks_trace grace period latency avg 16969.197 us stddev 2525.053 us SUMMARY ticks per tasks_trace grace period avg 1.146 stddev 0.178 Note that since these patches are not in bpf-next benchmarking was done by cherry-picking this patch onto rcu tree. [0] https://lore.kernel.org/rcu/20220620225402.GA3842369@paulmck-ThinkPad-P17-Gen-1/ Signed-off-by: Dave Marchevsky Signed-off-by: Daniel Borkmann Acked-by: Paul E. McKenney Acked-by: Martin KaFai Lau Link: https://lore.kernel.org/bpf/20220705190018.3239050-1-davemarchevsky@fb.com

selftests/bpf: Add benchmark for local_storage get

2022-06-23T02:14:33+00:00

Add a benchmarks to demonstrate the performance cliff for local_storage get as the number of local_storage maps increases beyond current local_storage implementation's cache size. "sequential get" and "interleaved get" benchmarks are added, both of which do many bpf_task_storage_get calls on sets of task local_storage maps of various counts, while considering a single specific map to be 'important' and counting task_storage_gets to the important map separately in addition to normal 'hits' count of all gets. Goal here is to mimic scenario where a particular program using one map - the important one - is running on a system where many other local_storage maps exist and are accessed often. While "sequential get" benchmark does bpf_task_storage_get for map 0, 1, ..., {9, 99, 999} in order, "interleaved" benchmark interleaves 4 bpf_task_storage_gets for the important map for every 10 map gets. This is meant to highlight performance differences when important map is accessed far more frequently than non-important maps. A "hashmap control" benchmark is also included for easy comparison of standard bpf hashmap lookup vs local_storage get. The benchmark is similar to "sequential get", but creates and uses BPF_MAP_TYPE_HASH instead of local storage. Only one inner map is created - a hashmap meant to hold tid -> data mapping for all tasks. Size of the hashmap is hardcoded to my system's PID_MAX_LIMIT (4,194,304). The number of these keys which are actually fetched as part of the benchmark is configurable. Addition of this benchmark is inspired by conversation with Alexei in a previous patchset's thread [0], which highlighted the need for such a benchmark to motivate and validate improvements to local_storage implementation. My approach in that series focused on improving performance for explicitly-marked 'important' maps and was rejected with feedback to make more generally-applicable improvements while avoiding explicitly marking maps as important. Thus the benchmark reports both general and important-map-focused metrics, so effect of future work on both is clear. Regarding the benchmark results. On a powerful system (Skylake, 20 cores, 256gb ram): 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 Local Storage ============= num_maps: 1 local_storage cache sequential get: hits throughput: 47.298 ± 0.180 M ops/s, hits latency: 21.142 ns/op, important_hits throughput: 47.298 ± 0.180 M ops/s local_storage cache interleaved get: hits throughput: 55.277 ± 0.888 M ops/s, hits latency: 18.091 ns/op, important_hits throughput: 55.277 ± 0.888 M ops/s num_maps: 10 local_storage cache sequential get: hits throughput: 40.240 ± 0.802 M ops/s, hits latency: 24.851 ns/op, important_hits throughput: 4.024 ± 0.080 M ops/s local_storage cache interleaved get: hits throughput: 48.701 ± 0.722 M ops/s, hits latency: 20.533 ns/op, important_hits throughput: 17.393 ± 0.258 M ops/s num_maps: 16 local_storage cache sequential get: hits throughput: 44.515 ± 0.708 M ops/s, hits latency: 22.464 ns/op, important_hits throughput: 2.782 ± 0.044 M ops/s local_storage cache interleaved get: hits throughput: 49.553 ± 2.260 M ops/s, hits latency: 20.181 ns/op, important_hits throughput: 15.767 ± 0.719 M ops/s num_maps: 17 local_storage cache sequential get: hits throughput: 38.778 ± 0.302 M ops/s, hits latency: 25.788 ns/op, important_hits throughput: 2.284 ± 0.018 M ops/s local_storage cache interleaved get: hits throughput: 43.848 ± 1.023 M ops/s, hits latency: 22.806 ns/op, important_hits throughput: 13.349 ± 0.311 M ops/s num_maps: 24 local_storage cache sequential get: hits throughput: 19.317 ± 0.568 M ops/s, hits latency: 51.769 ns/op, important_hits throughput: 0.806 ± 0.024 M ops/s local_storage cache interleaved get: hits throughput: 24.397 ± 0.272 M ops/s, hits latency: 40.989 ns/op, important_hits throughput: 6.863 ± 0.077 M ops/s num_maps: 32 local_storage cache sequential get: hits throughput: 13.333 ± 0.135 M ops/s, hits latency: 75.000 ns/op, important_hits throughput: 0.417 ± 0.004 M ops/s local_storage cache interleaved get: hits throughput: 16.898 ± 0.383 M ops/s, hits latency: 59.178 ns/op, important_hits throughput: 4.717 ± 0.107 M ops/s num_maps: 100 local_storage cache sequential get: hits throughput: 6.360 ± 0.107 M ops/s, hits latency: 157.233 ns/op, important_hits throughput: 0.064 ± 0.001 M ops/s local_storage cache interleaved get: hits throughput: 7.303 ± 0.362 M ops/s, hits latency: 136.930 ns/op, important_hits throughput: 1.907 ± 0.094 M ops/s num_maps: 1000 local_storage cache sequential get: hits throughput: 0.452 ± 0.010 M ops/s, hits latency: 2214.022 ns/op, important_hits throughput: 0.000 ± 0.000 M ops/s local_storage cache interleaved get: hits throughput: 0.542 ± 0.007 M ops/s, hits latency: 1843.341 ns/op, important_hits throughput: 0.136 ± 0.002 M ops/s Looking at the "sequential get" results, it's clear that as the number of task local_storage maps grows beyond the current cache size (16), there's a significant reduction in hits throughput. Note that current local_storage implementation assigns a cache_idx to maps as they are created. Since "sequential get" is creating maps 0..n in order and then doing bpf_task_storage_get calls in the same order, the benchmark is effectively ensuring that a map will not be in cache when the program tries to access it. For "interleaved get" results, important-map hits throughput is greatly increased as the important map is more likely to be in cache by virtue of being accessed far more frequently. Throughput still reduces as # maps increases, though. To get a sense of the overhead of the benchmark program, I commented out bpf_task_storage_get/bpf_map_lookup_elem in local_storage_bench.c and ran the benchmark on the same host as the 'real' run. Results: Hashmap Control =============== num keys: 10 hashmap (control) sequential get: hits throughput: 54.288 ± 0.655 M ops/s, hits latency: 18.420 ns/op, important_hits throughput: 54.288 ± 0.655 M ops/s num keys: 1000 hashmap (control) sequential get: hits throughput: 52.913 ± 0.519 M ops/s, hits latency: 18.899 ns/op, important_hits throughput: 52.913 ± 0.519 M ops/s num keys: 10000 hashmap (control) sequential get: hits throughput: 53.480 ± 1.235 M ops/s, hits latency: 18.699 ns/op, important_hits throughput: 53.480 ± 1.235 M ops/s num keys: 100000 hashmap (control) sequential get: hits throughput: 54.982 ± 1.902 M ops/s, hits latency: 18.188 ns/op, important_hits throughput: 54.982 ± 1.902 M ops/s num keys: 4194304 hashmap (control) sequential get: hits throughput: 50.858 ± 0.707 M ops/s, hits latency: 19.662 ns/op, important_hits throughput: 50.858 ± 0.707 M ops/s Local Storage ============= num_maps: 1 local_storage cache sequential get: hits throughput: 110.990 ± 4.828 M ops/s, hits latency: 9.010 ns/op, important_hits throughput: 110.990 ± 4.828 M ops/s local_storage cache interleaved get: hits throughput: 161.057 ± 4.090 M ops/s, hits latency: 6.209 ns/op, important_hits throughput: 161.057 ± 4.090 M ops/s num_maps: 10 local_storage cache sequential get: hits throughput: 112.930 ± 1.079 M ops/s, hits latency: 8.855 ns/op, important_hits throughput: 11.293 ± 0.108 M ops/s local_storage cache interleaved get: hits throughput: 115.841 ± 2.088 M ops/s, hits latency: 8.633 ns/op, important_hits throughput: 41.372 ± 0.746 M ops/s num_maps: 16 local_storage cache sequential get: hits throughput: 115.653 ± 0.416 M ops/s, hits latency: 8.647 ns/op, important_hits throughput: 7.228 ± 0.026 M ops/s local_storage cache interleaved get: hits throughput: 138.717 ± 1.649 M ops/s, hits latency: 7.209 ns/op, important_hits throughput: 44.137 ± 0.525 M ops/s num_maps: 17 local_storage cache sequential get: hits throughput: 112.020 ± 1.649 M ops/s, hits latency: 8.927 ns/op, important_hits throughput: 6.598 ± 0.097 M ops/s local_storage cache interleaved get: hits throughput: 128.089 ± 1.960 M ops/s, hits latency: 7.807 ns/op, important_hits throughput: 38.995 ± 0.597 M ops/s num_maps: 24 local_storage cache sequential get: hits throughput: 92.447 ± 5.170 M ops/s, hits latency: 10.817 ns/op, important_hits throughput: 3.855 ± 0.216 M ops/s local_storage cache interleaved get: hits throughput: 128.844 ± 2.808 M ops/s, hits latency: 7.761 ns/op, important_hits throughput: 36.245 ± 0.790 M ops/s num_maps: 32 local_storage cache sequential get: hits throughput: 102.042 ± 1.462 M ops/s, hits latency: 9.800 ns/op, important_hits throughput: 3.194 ± 0.046 M ops/s local_storage cache interleaved get: hits throughput: 126.577 ± 1.818 M ops/s, hits latency: 7.900 ns/op, important_hits throughput: 35.332 ± 0.507 M ops/s num_maps: 100 local_storage cache sequential get: hits throughput: 111.327 ± 1.401 M ops/s, hits latency: 8.983 ns/op, important_hits throughput: 1.113 ± 0.014 M ops/s local_storage cache interleaved get: hits throughput: 131.327 ± 1.339 M ops/s, hits latency: 7.615 ns/op, important_hits throughput: 34.302 ± 0.350 M ops/s num_maps: 1000 local_storage cache sequential get: hits throughput: 101.978 ± 0.563 M ops/s, hits latency: 9.806 ns/op, important_hits throughput: 0.102 ± 0.001 M ops/s local_storage cache interleaved get: hits throughput: 141.084 ± 1.098 M ops/s, hits latency: 7.088 ns/op, important_hits throughput: 35.430 ± 0.276 M ops/s Adjusting for overhead, latency numbers for "hashmap control" and "sequential get" are: hashmap_control_1k: ~53.8ns hashmap_control_10k: ~124.2ns hashmap_control_100k: ~206.5ns sequential_get_1: ~12.1ns sequential_get_10: ~16.0ns sequential_get_16: ~13.8ns sequential_get_17: ~16.8ns sequential_get_24: ~40.9ns sequential_get_32: ~65.2ns sequential_get_100: ~148.2ns sequential_get_1000: ~2204ns Clearly demonstrating a cliff. In the discussion for v1 of this patch, Alexei noted that local_storage was 2.5x faster than a large hashmap when initially implemented [1]. The benchmark results show that local_storage is 5-10x faster: a long-running BPF application putting some pid-specific info into a hashmap for each pid it sees will probably see on the order of 10-100k pids. Bench numbers for hashmaps of this size are ~10x slower than sequential_get_16, but as the number of local_storage maps grows far past local_storage cache size the performance advantage shrinks and eventually reverses. When running the benchmarks it may be necessary to bump 'open files' ulimit for a successful run. [0]: https://lore.kernel.org/all/20220420002143.1096548-1-davemarchevsky@fb.com [1]: https://lore.kernel.org/bpf/20220511173305.ftldpn23m4ski3d3@MBP-98dd607d3435.dhcp.thefacebook.com/ Signed-off-by: Dave Marchevsky Link: https://lore.kernel.org/r/20220620222554.270578-1-davemarchevsky@fb.com Signed-off-by: Alexei Starovoitov

selftest/bpf/benchs: Add bpf_map benchmark

2022-06-11T21:25:35+00:00

Add benchmark for hash_map to reproduce the worst case that non-stop update when map's free is zero. Just like this: ./run_bench_bpf_hashmap_full_update.sh Setting up benchmark 'bpf-hashmap-ful-update'... Benchmark 'bpf-hashmap-ful-update' started. 1:hash_map_full_perf 555830 events per sec ... Signed-off-by: Feng Zhou Link: https://lore.kernel.org/r/20220610023308.93798-3-zhoufeng.zf@bytedance.com Signed-off-by: Alexei Starovoitov

selftests/bpf: Use libbpf 1.0 API mode instead of RLIMIT_MEMLOCK

2022-04-11T03:17:16+00:00

We have switched to memcg-based memory accouting and thus the rlimit is not needed any more. LIBBPF_STRICT_AUTO_RLIMIT_MEMLOCK was introduced in libbpf for backward compatibility, so we can use it instead now. After this change, the header tools/testing/selftests/bpf/bpf_rlimit.h can be removed. This patch also removes the useless header sys/resource.h from many files in tools/testing/selftests/bpf/. Signed-off-by: Yafang Shao Signed-off-by: Andrii Nakryiko Link: https://lore.kernel.org/bpf/20220409125958.92629-3-laoar.shao@gmail.com