- Oct 15, 2020
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Leo Yan authored
Replace the header string "Lcl" with "LclHit", which is more explicit to express the event type is LLC local hit. Signed-off-by:
Leo Yan <leo.yan@linaro.org> Tested-by:
Joe Mario <jmario@redhat.com> Acked-by:
Jiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-7-leo.yan@linaro.org Signed-off-by:
Arnaldo Carvalho de Melo <acme@redhat.com>
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Leo Yan authored
Local and remote HITM use the headers 'Lcl' and 'Rmt' respectively, suppose if we want to extend the tool to display these two dimensions under any one metrics, users cannot understand the semantics if only based on the header string 'Lcl' or 'Rmt'. To explicit express the meaning for HITM items, this patch changes the headers string as "LclHitm" and "RmtHitm", the strings are more readable and this allows to extend metrics for using HITM items. Signed-off-by:
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Leo Yan authored
The metrics "LLC Load Hitm" contains two items: one is "local Hitm" and another is "remote Hitm". "local Hitm" means: L3 HIT and was serviced by another processor core with a cross core snoop where modified copies were found; it's no doubt that "local Hitm" belongs to LLC access. But for "remote Hitm", based on the code in util/mem-events, it's the event for remote cache HIT and was serviced by another processor core with modified copies. Thus the remote Hitm is a remote cache's hit and actually it's LLC load miss. Now the display format gives users the impression that "local Hitm" and "remote Hitm" both belong to the LLC load, but this is not the fact as described. This patch changes the header from "LLC Load Hitm" to "Load Hitm", this can avoid the give the wrong impression that all Hitm belong to LLC. Signed-off-by:
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Leo Yan authored
The metrics are not organized based on memory hierarchy, e.g. the tool doesn't organize the metrics order based on memory nodes from the close node (e.g. L1/L2 cache) to far node (e.g. L3 cache and DRAM). To output metrics with more friendly form, this patch refines the metrics order based on memory hierarchy: "Core Load Hit" => "LLC Load Hit" => "LLC Ld Miss" => "Load Dram" Signed-off-by:
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Leo Yan authored
The total stores is displayed under the metrics "Store Reference", to output the same format with total records and all loads, extract the total stores number as a standalone metrics "Total Stores". After this patch, the tool shows the summary numbers ("Total records", "Total loads", "Total Stores") in the unified form. Before: # ----------- Cacheline ---------- Tot ----- LLC Load Hitm ----- Total Total ---- Store Reference ---- --- Load Dram ---- LLC ----- Core Load Hit ----- -- LLC Load Hit -- # Index Address Node PA cnt Hitm Total Lcl Rmt records Loads Total L1Hit L1Miss Lcl Rmt Ld Miss FB L1 L2 Llc Rmt # ..... .................. .... ...... ....... ....... ....... ....... ....... ....... ....... ....... ....... ........ ........ ....... ....... ....... ....... ........ ........ # 0 0x55f07d580100 0 1499 85.89% 481 481 0 7243 3879 3364 2599 765 0 0 0 548 2615 66 169 0 1 0x55f07d580080 0 1 13.93% 78 78 0 664 664 0 0 0 0 0 0 187 361 27 11 0 2 0x55f07d5800c0 0 1 0.18% 1 1 0 405 405 0 0 0 0 0 0 131 0 10 263 0 After: # ----------- Cacheline ---------- Tot ----- LLC Load Hitm ----- Total Total Total ---- Stores ---- --- Load Dram ---- LLC ----- Core Load Hit ----- -- LLC Load Hit -- # Index Address Node PA cnt Hitm Total Lcl Rmt records Loads Stores L1Hit L1Miss Lcl Rmt Ld Miss FB L1 L2 Llc Rmt # ..... .................. .... ...... ....... ....... ....... ....... ....... ....... ....... ....... ....... ........ ........ ....... ....... ....... ....... ........ ........ # 0 0x55f07d580100 0 1499 85.89% 481 481 0 7243 3879 3364 2599 765 0 0 0 548 2615 66 169 0 1 0x55f07d580080 0 1 13.93% 78 78 0 664 664 0 0 0 0 0 0 187 361 27 11 0 2 0x55f07d5800c0 0 1 0.18% 1 1 0 405 405 0 0 0 0 0 0 131 0 10 263 0 Signed-off-by: -
Leo Yan authored
To view the statistics with "breakdown" mode, it's good to show the summary numbers for the total records, all stores and all loads, then the sequential conlumns can be used to break into more detailed items. To achieve this purpose, this patch displays the summary numbers for records/stores/loads continuously and places them before breakdown items, this can allow uses to easily read the summarized statistics. Signed-off-by:
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- Oct 14, 2020
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Ian Rogers authored
The existing approach to synchronization between threads in the numa benchmark is unbalanced mutexes. This synchronization causes thread sanitizer to warn of locks being taken twice on a thread without an unlock, as well as unlocks with no corresponding locks. This change replaces the synchronization with more regular condition variables. While this fixes one class of thread sanitizer warnings, there still remain warnings of data races due to threads reading and writing shared memory without any atomics. Committer testing: Basic run on a non-NUMA machine. # perf bench numa # List of available benchmarks for collection 'numa': mem: Benchmark for NUMA workloads all: Run all NUMA benchmarks # perf bench numa all # Running numa/mem benchmark... # Running main, "perf bench numa numa-mem" # # Running test on: Linux five 5.8.12-200.fc32.x86_64 #1 SMP Mon Sep 28 12:17:31 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux # # Running RAM-bw-local, "perf bench numa mem -p 1 -t 1 -P 1024 -C 0 -M 0 -s 20 -zZq --thp 1 --no-data_rand_walk" 20.076 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.073 secs average thread-runtime 0.190 % difference between max/avg runtime 241.828 GB data processed, per thread 241.828 GB data processed, total 0.083 nsecs/byte/thread runtime 12.045 GB/sec/thread speed 12.045 GB/sec total speed # Running RAM-bw-local-NOTHP, "perf bench numa mem -p 1 -t 1 -P 1024 -C 0 -M 0 -s 20 -zZq --thp 1 --no-data_rand_walk --thp -1" 20.045 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.014 secs average thread-runtime 0.111 % difference between max/avg runtime 234.304 GB data processed, per thread 234.304 GB data processed, total 0.086 nsecs/byte/thread runtime 11.689 GB/sec/thread speed 11.689 GB/sec total speed # Running RAM-bw-remote, "perf bench numa mem -p 1 -t 1 -P 1024 -C 0 -M 1 -s 20 -zZq --thp 1 --no-data_rand_walk" Test not applicable, system has only 1 nodes. # Running RAM-bw-local-2x, "perf bench numa mem -p 2 -t 1 -P 1024 -C 0,2 -M 0x2 -s 20 -zZq --thp 1 --no-data_rand_walk" 20.138 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.121 secs average thread-runtime 0.342 % difference between max/avg runtime 135.961 GB data processed, per thread 271.922 GB data processed, total 0.148 nsecs/byte/thread runtime 6.752 GB/sec/thread speed 13.503 GB/sec total speed # Running RAM-bw-remote-2x, "perf bench numa mem -p 2 -t 1 -P 1024 -C 0,2 -M 1x2 -s 20 -zZq --thp 1 --no-data_rand_walk" Test not applicable, system has only 1 nodes. # Running RAM-bw-cross, "perf bench numa mem -p 2 -t 1 -P 1024 -C 0,8 -M 1,0 -s 20 -zZq --thp 1 --no-data_rand_walk" Test not applicable, system has only 1 nodes. # Running 1x3-convergence, "perf bench numa mem -p 1 -t 3 -P 512 -s 100 -zZ0qcm --thp 1" 0.747 secs latency to NUMA-converge 0.747 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.714 secs average thread-runtime 50.000 % difference between max/avg runtime 3.228 GB data processed, per thread 9.683 GB data processed, total 0.231 nsecs/byte/thread runtime 4.321 GB/sec/thread speed 12.964 GB/sec total speed # Running 1x4-convergence, "perf bench numa mem -p 1 -t 4 -P 512 -s 100 -zZ0qcm --thp 1" 1.127 secs latency to NUMA-converge 1.127 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.089 secs average thread-runtime 5.624 % difference between max/avg runtime 3.765 GB data processed, per thread 15.062 GB data processed, total 0.299 nsecs/byte/thread runtime 3.342 GB/sec/thread speed 13.368 GB/sec total speed # Running 1x6-convergence, "perf bench numa mem -p 1 -t 6 -P 1020 -s 100 -zZ0qcm --thp 1" 1.003 secs latency to NUMA-converge 1.003 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.889 secs average thread-runtime 50.000 % difference between max/avg runtime 2.141 GB data processed, per thread 12.847 GB data processed, total 0.469 nsecs/byte/thread runtime 2.134 GB/sec/thread speed 12.805 GB/sec total speed # Running 2x3-convergence, "perf bench numa mem -p 2 -t 3 -P 1020 -s 100 -zZ0qcm --thp 1" 1.814 secs latency to NUMA-converge 1.814 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.716 secs average thread-runtime 22.440 % difference between max/avg runtime 3.747 GB data processed, per thread 22.483 GB data processed, total 0.484 nsecs/byte/thread runtime 2.065 GB/sec/thread speed 12.393 GB/sec total speed # Running 3x3-convergence, "perf bench numa mem -p 3 -t 3 -P 1020 -s 100 -zZ0qcm --thp 1" 2.065 secs latency to NUMA-converge 2.065 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.947 secs average thread-runtime 25.788 % difference between max/avg runtime 2.855 GB data processed, per thread 25.694 GB data processed, total 0.723 nsecs/byte/thread runtime 1.382 GB/sec/thread speed 12.442 GB/sec total speed # Running 4x4-convergence, "perf bench numa mem -p 4 -t 4 -P 512 -s 100 -zZ0qcm --thp 1" 1.912 secs latency to NUMA-converge 1.912 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.775 secs average thread-runtime 23.852 % difference between max/avg runtime 1.479 GB data processed, per thread 23.668 GB data processed, total 1.293 nsecs/byte/thread runtime 0.774 GB/sec/thread speed 12.378 GB/sec total speed # Running 4x4-convergence-NOTHP, "perf bench numa mem -p 4 -t 4 -P 512 -s 100 -zZ0qcm --thp 1 --thp -1" 1.783 secs latency to NUMA-converge 1.783 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.633 secs average thread-runtime 21.960 % difference between max/avg runtime 1.345 GB data processed, per thread 21.517 GB data processed, total 1.326 nsecs/byte/thread runtime 0.754 GB/sec/thread speed 12.067 GB/sec total speed # Running 4x6-convergence, "perf bench numa mem -p 4 -t 6 -P 1020 -s 100 -zZ0qcm --thp 1" 5.396 secs latency to NUMA-converge 5.396 secs slowest (max) thread-runtime 4.000 secs fastest (min) thread-runtime 4.928 secs average thread-runtime 12.937 % difference between max/avg runtime 2.721 GB data processed, per thread 65.306 GB data processed, total 1.983 nsecs/byte/thread runtime 0.504 GB/sec/thread speed 12.102 GB/sec total speed # Running 4x8-convergence, "perf bench numa mem -p 4 -t 8 -P 512 -s 100 -zZ0qcm --thp 1" 3.121 secs latency to NUMA-converge 3.121 secs slowest (max) thread-runtime 2.000 secs fastest (min) thread-runtime 2.836 secs average thread-runtime 17.962 % difference between max/avg runtime 1.194 GB data processed, per thread 38.192 GB data processed, total 2.615 nsecs/byte/thread runtime 0.382 GB/sec/thread speed 12.236 GB/sec total speed # Running 8x4-convergence, "perf bench numa mem -p 8 -t 4 -P 512 -s 100 -zZ0qcm --thp 1" 4.302 secs latency to NUMA-converge 4.302 secs slowest (max) thread-runtime 3.000 secs fastest (min) thread-runtime 4.045 secs average thread-runtime 15.133 % difference between max/avg runtime 1.631 GB data processed, per thread 52.178 GB data processed, total 2.638 nsecs/byte/thread runtime 0.379 GB/sec/thread speed 12.128 GB/sec total speed # Running 8x4-convergence-NOTHP, "perf bench numa mem -p 8 -t 4 -P 512 -s 100 -zZ0qcm --thp 1 --thp -1" 4.418 secs latency to NUMA-converge 4.418 secs slowest (max) thread-runtime 3.000 secs fastest (min) thread-runtime 4.104 secs average thread-runtime 16.045 % difference between max/avg runtime 1.664 GB data processed, per thread 53.254 GB data processed, total 2.655 nsecs/byte/thread runtime 0.377 GB/sec/thread speed 12.055 GB/sec total speed # Running 3x1-convergence, "perf bench numa mem -p 3 -t 1 -P 512 -s 100 -zZ0qcm --thp 1" 0.973 secs latency to NUMA-converge 0.973 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.955 secs average thread-runtime 50.000 % difference between max/avg runtime 4.124 GB data processed, per thread 12.372 GB data processed, total 0.236 nsecs/byte/thread runtime 4.238 GB/sec/thread speed 12.715 GB/sec total speed # Running 4x1-convergence, "perf bench numa mem -p 4 -t 1 -P 512 -s 100 -zZ0qcm --thp 1" 0.820 secs latency to NUMA-converge 0.820 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.808 secs average thread-runtime 50.000 % difference between max/avg runtime 2.555 GB data processed, per thread 10.220 GB data processed, total 0.321 nsecs/byte/thread runtime 3.117 GB/sec/thread speed 12.468 GB/sec total speed # Running 8x1-convergence, "perf bench numa mem -p 8 -t 1 -P 512 -s 100 -zZ0qcm --thp 1" 0.667 secs latency to NUMA-converge 0.667 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.607 secs average thread-runtime 50.000 % difference between max/avg runtime 1.009 GB data processed, per thread 8.069 GB data processed, total 0.661 nsecs/byte/thread runtime 1.512 GB/sec/thread speed 12.095 GB/sec total speed # Running 16x1-convergence, "perf bench numa mem -p 16 -t 1 -P 256 -s 100 -zZ0qcm --thp 1" 1.546 secs latency to NUMA-converge 1.546 secs slowest (max) thread-runtime 1.000 secs fastest (min) thread-runtime 1.485 secs average thread-runtime 17.664 % difference between max/avg runtime 1.162 GB data processed, per thread 18.594 GB data processed, total 1.331 nsecs/byte/thread runtime 0.752 GB/sec/thread speed 12.025 GB/sec total speed # Running 32x1-convergence, "perf bench numa mem -p 32 -t 1 -P 128 -s 100 -zZ0qcm --thp 1" 0.812 secs latency to NUMA-converge 0.812 secs slowest (max) thread-runtime 0.000 secs fastest (min) thread-runtime 0.739 secs average thread-runtime 50.000 % difference between max/avg runtime 0.309 GB data processed, per thread 9.874 GB data processed, total 2.630 nsecs/byte/thread runtime 0.380 GB/sec/thread speed 12.166 GB/sec total speed # Running 2x1-bw-process, "perf bench numa mem -p 2 -t 1 -P 1024 -s 20 -zZ0q --thp 1" 20.044 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.020 secs average thread-runtime 0.109 % difference between max/avg runtime 125.750 GB data processed, per thread 251.501 GB data processed, total 0.159 nsecs/byte/thread runtime 6.274 GB/sec/thread speed 12.548 GB/sec total speed # Running 3x1-bw-process, "perf bench numa mem -p 3 -t 1 -P 1024 -s 20 -zZ0q --thp 1" 20.148 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.090 secs average thread-runtime 0.367 % difference between max/avg runtime 85.267 GB data processed, per thread 255.800 GB data processed, total 0.236 nsecs/byte/thread runtime 4.232 GB/sec/thread speed 12.696 GB/sec total speed # Running 4x1-bw-process, "perf bench numa mem -p 4 -t 1 -P 1024 -s 20 -zZ0q --thp 1" 20.169 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.100 secs average thread-runtime 0.419 % difference between max/avg runtime 63.144 GB data processed, per thread 252.576 GB data processed, total 0.319 nsecs/byte/thread runtime 3.131 GB/sec/thread speed 12.523 GB/sec total speed # Running 8x1-bw-process, "perf bench numa mem -p 8 -t 1 -P 512 -s 20 -zZ0q --thp 1" 20.175 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.107 secs average thread-runtime 0.433 % difference between max/avg runtime 31.267 GB data processed, per thread 250.133 GB data processed, total 0.645 nsecs/byte/thread runtime 1.550 GB/sec/thread speed 12.398 GB/sec total speed # Running 8x1-bw-process-NOTHP, "perf bench numa mem -p 8 -t 1 -P 512 -s 20 -zZ0q --thp 1 --thp -1" 20.216 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.113 secs average thread-runtime 0.535 % difference between max/avg runtime 30.998 GB data processed, per thread 247.981 GB data processed, total 0.652 nsecs/byte/thread runtime 1.533 GB/sec/thread speed 12.266 GB/sec total speed # Running 16x1-bw-process, "perf bench numa mem -p 16 -t 1 -P 256 -s 20 -zZ0q --thp 1" 20.234 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.174 secs average thread-runtime 0.577 % difference between max/avg runtime 15.377 GB data processed, per thread 246.039 GB data processed, total 1.316 nsecs/byte/thread runtime 0.760 GB/sec/thread speed 12.160 GB/sec total speed # Running 1x4-bw-thread, "perf bench numa mem -p 1 -t 4 -T 256 -s 20 -zZ0q --thp 1" 20.040 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.028 secs average thread-runtime 0.099 % difference between max/avg runtime 66.832 GB data processed, per thread 267.328 GB data processed, total 0.300 nsecs/byte/thread runtime 3.335 GB/sec/thread speed 13.340 GB/sec total speed # Running 1x8-bw-thread, "perf bench numa mem -p 1 -t 8 -T 256 -s 20 -zZ0q --thp 1" 20.064 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.034 secs average thread-runtime 0.160 % difference between max/avg runtime 32.911 GB data processed, per thread 263.286 GB data processed, total 0.610 nsecs/byte/thread runtime 1.640 GB/sec/thread speed 13.122 GB/sec total speed # Running 1x16-bw-thread, "perf bench numa mem -p 1 -t 16 -T 128 -s 20 -zZ0q --thp 1" 20.092 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.052 secs average thread-runtime 0.230 % difference between max/avg runtime 16.131 GB data processed, per thread 258.088 GB data processed, total 1.246 nsecs/byte/thread runtime 0.803 GB/sec/thread speed 12.845 GB/sec total speed # Running 1x32-bw-thread, "perf bench numa mem -p 1 -t 32 -T 64 -s 20 -zZ0q --thp 1" 20.099 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.063 secs average thread-runtime 0.247 % difference between max/avg runtime 7.962 GB data processed, per thread 254.773 GB data processed, total 2.525 nsecs/byte/thread runtime 0.396 GB/sec/thread speed 12.676 GB/sec total speed # Running 2x3-bw-process, "perf bench numa mem -p 2 -t 3 -P 512 -s 20 -zZ0q --thp 1" 20.150 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.120 secs average thread-runtime 0.372 % difference between max/avg runtime 44.827 GB data processed, per thread 268.960 GB data processed, total 0.450 nsecs/byte/thread runtime 2.225 GB/sec/thread speed 13.348 GB/sec total speed # Running 4x4-bw-process, "perf bench numa mem -p 4 -t 4 -P 512 -s 20 -zZ0q --thp 1" 20.258 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.168 secs average thread-runtime 0.636 % difference between max/avg runtime 17.079 GB data processed, per thread 273.263 GB data processed, total 1.186 nsecs/byte/thread runtime 0.843 GB/sec/thread speed 13.489 GB/sec total speed # Running 4x6-bw-process, "perf bench numa mem -p 4 -t 6 -P 512 -s 20 -zZ0q --thp 1" 20.559 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.382 secs average thread-runtime 1.359 % difference between max/avg runtime 10.758 GB data processed, per thread 258.201 GB data processed, total 1.911 nsecs/byte/thread runtime 0.523 GB/sec/thread speed 12.559 GB/sec total speed # Running 4x8-bw-process, "perf bench numa mem -p 4 -t 8 -P 512 -s 20 -zZ0q --thp 1" 20.744 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.516 secs average thread-runtime 1.792 % difference between max/avg runtime 8.069 GB data processed, per thread 258.201 GB data processed, total 2.571 nsecs/byte/thread runtime 0.389 GB/sec/thread speed 12.447 GB/sec total speed # Running 4x8-bw-process-NOTHP, "perf bench numa mem -p 4 -t 8 -P 512 -s 20 -zZ0q --thp 1 --thp -1" 20.855 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.561 secs average thread-runtime 2.050 % difference between max/avg runtime 8.069 GB data processed, per thread 258.201 GB data processed, total 2.585 nsecs/byte/thread runtime 0.387 GB/sec/thread speed 12.381 GB/sec total speed # Running 3x3-bw-process, "perf bench numa mem -p 3 -t 3 -P 512 -s 20 -zZ0q --thp 1" 20.134 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.077 secs average thread-runtime 0.333 % difference between max/avg runtime 28.091 GB data processed, per thread 252.822 GB data processed, total 0.717 nsecs/byte/thread runtime 1.395 GB/sec/thread speed 12.557 GB/sec total speed # Running 5x5-bw-process, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 20.588 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.375 secs average thread-runtime 1.427 % difference between max/avg runtime 10.177 GB data processed, per thread 254.436 GB data processed, total 2.023 nsecs/byte/thread runtime 0.494 GB/sec/thread speed 12.359 GB/sec total speed # Running 2x16-bw-process, "perf bench numa mem -p 2 -t 16 -P 512 -s 20 -zZ0q --thp 1" 20.657 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.429 secs average thread-runtime 1.589 % difference between max/avg runtime 8.170 GB data processed, per thread 261.429 GB data processed, total 2.528 nsecs/byte/thread runtime 0.395 GB/sec/thread speed 12.656 GB/sec total speed # Running 1x32-bw-process, "perf bench numa mem -p 1 -t 32 -P 2048 -s 20 -zZ0q --thp 1" 22.981 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 21.996 secs average thread-runtime 6.486 % difference between max/avg runtime 8.863 GB data processed, per thread 283.606 GB data processed, total 2.593 nsecs/byte/thread runtime 0.386 GB/sec/thread speed 12.341 GB/sec total speed # Running numa02-bw, "perf bench numa mem -p 1 -t 32 -T 32 -s 20 -zZ0q --thp 1" 20.047 secs slowest (max) thread-runtime 19.000 secs fastest (min) thread-runtime 20.026 secs average thread-runtime 2.611 % difference between max/avg runtime 8.441 GB data processed, per thread 270.111 GB data processed, total 2.375 nsecs/byte/thread runtime 0.421 GB/sec/thread speed 13.474 GB/sec total speed # Running numa02-bw-NOTHP, "perf bench numa mem -p 1 -t 32 -T 32 -s 20 -zZ0q --thp 1 --thp -1" 20.088 secs slowest (max) thread-runtime 19.000 secs fastest (min) thread-runtime 20.025 secs average thread-runtime 2.709 % difference between max/avg runtime 8.411 GB data processed, per thread 269.142 GB data processed, total 2.388 nsecs/byte/thread runtime 0.419 GB/sec/thread speed 13.398 GB/sec total speed # Running numa01-bw-thread, "perf bench numa mem -p 2 -t 16 -T 192 -s 20 -zZ0q --thp 1" 20.293 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.175 secs average thread-runtime 0.721 % difference between max/avg runtime 7.918 GB data processed, per thread 253.374 GB data processed, total 2.563 nsecs/byte/thread runtime 0.390 GB/sec/thread speed 12.486 GB/sec total speed # Running numa01-bw-thread-NOTHP, "perf bench numa mem -p 2 -t 16 -T 192 -s 20 -zZ0q --thp 1 --thp -1" 20.411 secs slowest (max) thread-runtime 20.000 secs fastest (min) thread-runtime 20.226 secs average thread-runtime 1.006 % difference between max/avg runtime 7.931 GB data processed, per thread 253.778 GB data processed, total 2.574 nsecs/byte/thread runtime 0.389 GB/sec/thread speed 12.434 GB/sec total speed # Signed-off-by:Ian Rogers <irogers@google.com> Acked-by:
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John Garry authored
The event code for events referencing std arch events is incorrectly evaluated in json_events(). The issue is that je.event is evaluated properly from try_fixup(), but later NULLified from the real_event() call, as "event" may be NULL. Fix by setting "event" same je.event in try_fixup(). Also remove support for overwriting event code for events using std arch events, as it is not used. Signed-off-by:
John Garry <john.garry@huawei.com> Reviewed-By:
Kajol <Jain<kjain@linux.ibm.com> Acked-by:
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Jin Yao authored
This patch enables perf-diff with "--stream" option. "--stream": Enable hot streams comparison Now let's see example. perf record -b ... Generate perf.data.old with branch data perf record -b ... Generate perf.data with branch data perf diff --stream [ Matched hot streams ] hot chain pair 1: cycles: 1, hits: 27.77% cycles: 1, hits: 9.24% --------------------------- -------------------------- main div.c:39 main div.c:39 main div.c:44 main div.c:44 hot chain pair 2: cycles: 34, hits: 20.06% cycles: 27, hits: 16.98% --------------------------- -------------------------- __random_r random_r.c:360 __random_r random_r.c:360 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:380 __random_r random_r.c:380 __random_r random_r.c:357 __random_r random_r.c:357 __random random.c:293 __random random.c:293 __random random.c:293 __random random.c:293 __random random.c:291 __random random.c:291 __random random.c:291 __random random.c:291 __random random.c:291 __random random.c:291 __random random.c:288 __random random.c:288 rand rand.c:27 rand rand.c:27 rand rand.c:26 rand rand.c:26 rand@plt rand@plt rand@plt rand@plt compute_flag div.c:25 compute_flag div.c:25 compute_flag div.c:22 compute_flag div.c:22 main div.c:40 main div.c:40 main div.c:40 main div.c:40 main div.c:39 main div.c:39 hot chain pair 3: cycles: 9, hits: 4.48% cycles: 6, hits: 4.51% --------------------------- -------------------------- __random_r random_r.c:360 __random_r random_r.c:360 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:380 __random_r random_r.c:380 [ Hot streams in old perf data only ] hot chain 1: cycles: 18, hits: 6.75% -------------------------- __random_r random_r.c:360 __random_r random_r.c:388 __random_r random_r.c:388 __random_r random_r.c:380 __random_r random_r.c:357 __random random.c:293 __random random.c:293 __random random.c:291 __random random.c:291 __random random.c:291 __random random.c:288 rand rand.c:27 rand rand.c:26 rand@plt rand@plt compute_flag div.c:25 compute_flag div.c:22 main div.c:40 hot chain 2: cycles: 29, hits: 2.78% -------------------------- compute_flag div.c:22 main div.c:40 main div.c:40 main div.c:39 [ Hot streams in new perf data only ] hot chain 1: cycles: 4, hits: 4.54% -------------------------- main div.c:42 compute_flag div.c:28 hot chain 2: cycles: 5, hits: 3.51% -------------------------- main div.c:39 main div.c:44 main div.c:42 compute_flag div.c:28 Signed-off-by:Jin Yao <yao.jin@linux.intel.com> Acked-by:
Jiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-8-yao.jin@linux.intel.com Signed-off-by:
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Jin Yao authored
We show the streams separately. They are divided into different sections. 1. "Matched hot streams" 2. "Hot streams in old perf data only" 3. "Hot streams in new perf data only". For each stream, we report the cycles and hot percent (hits%). For example, cycles: 2, hits: 4.08% -------------------------- main div.c:42 compute_flag div.c:28 Signed-off-by: -
Jin Yao authored
We have used callchain_node->hit to measure the hot level of one stream. This patch calculates the sum of hits of total streams. Thus in next patch, we can use following formula to report hot percent for one stream. hot percent = callchain_node->hit / sum of total hits Signed-off-by:
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Jin Yao authored
In previous patch, we have created an evsel_streams for one event, and top N hottest streams will be saved in a stream array in evsel_streams. This patch compares total streams among two evsel_streams. Once two streams are fully matched, they will be linked as a pair. From the pair, we can know which streams are matched. Signed-off-by:
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Jin Yao authored
Stream is the branch history which is aggregated by the branch records from perf samples. Now we support the callchain as stream. If the callchain entries of one stream are fully matched with the callchain entries of another stream, we think two streams are matched. For example, cycles: 1, hits: 26.80% cycles: 1, hits: 27.30% ----------------------- ----------------------- main div.c:39 main div.c:39 main div.c:44 main div.c:44 Above two streams are matched (we don't consider the case that source code is changed). The matching logic is, compare the chain string first. If it's not matched, fallback to dso address comparison. Signed-off-by: -
Jin Yao authored
In previous patch, we have created evsel_streams array. This patch returns the specified evsel_streams according to the evsel_idx. Signed-off-by:
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Jin Yao authored
We define a stream as the branch history which is aggregated by the branch records from perf samples. For example, the callchains aggregated from the branch records are considered as streams. By browsing the hot stream, we can understand the hot code path. Now we only support the callchain for stream. For measuring the hot level for a stream, we use the callchain_node->hit, higher is hotter. There may be many callchains sampled so we only focus on the top N hottest callchains. N is a user defined parameter or predefined default value (nr_streams_max). This patch creates an evsel_streams array per event, and saves the top N hottest streams in a stream array. So now we can get the per-event top N hottest streams. Signed-off-by:
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Andi Kleen authored
Document the higher level --insn-trace etc. perf script options. Include the howto how to build xed into the manpage Signed-off-by:
Andi Kleen <ak@linux.intel.com> Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Jiri Olsa <jolsa@kernel.org> Link: http://lore.kernel.org/lkml/20201014035346.4772-1-andi@firstfloor.org Signed-off-by:
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Andi Kleen authored
Peter suggested that using the exclusive mode in perf could avoid some problems with bad scheduling of groups. Exclusive is implemented in the kernel, but wasn't exposed by the perf tool, so hard to use without custom low level API users. Add support for marking groups or events with :e for exclusive in the perf tool. The implementation is basically the same as the existing pinned attribute. Committer testing: # perf test "parse event" 6: Parse event definition strings : Ok # perf test -v "parse event" |& grep :u*e running test 56 'instructions:uep' running test 57 '{cycles,cache-misses,branch-misses}:e' # # # grep "model name" -m1 /proc/cpuinfo model name : AMD Ryzen 9 3900X 12-Core Processor # # perf stat -a -e '{cycles,cache-misses,branch-misses}:e' sleep 1 Performance counter stats for 'system wide': <not counted> cycles (0.00%) <not counted> cache-misses (0.00%) <not counted> branch-misses (0.00%) 1.001269893 seconds time elapsed Some events weren't counted. Try disabling the NMI watchdog: echo 0 > /proc/sys/kernel/nmi_watchdog perf stat ... echo 1 > /proc/sys/kernel/nmi_watchdog # echo 0 > /proc/sys/kernel/nmi_watchdog # perf stat -a -e '{cycles,cache-misses,branch-misses}:e' sleep 1 Performance counter stats for 'system wide': 1,298,663,141 cycles 30,962,215 cache-misses 5,325,150 branch-misses 1.001474934 seconds time elapsed # # The output for asking for precise events on AMD needs to improve, it # supposedly works only for system wide or per CPU # # perf stat -a -e '{cycles,cache-misses,branch-misses}:uep' sleep 1 Error: The sys_perf_event_open() syscall returned with 22 (Invalid argument) for event (cycles). /bin/dmesg | grep -i perf may provide additional information. # perf stat -a -e '{cycles,cache-misses,branch-misses}:ue' sleep 1 Performance counter stats for 'system wide': 746,363,126 cycles 16,881,611 cache-misses 2,871,259 branch-misses 1.001636066 seconds time elapsed # Signed-off-by: -
Jiri Olsa authored
Add a test for the build id cache that adds a binary with sha1 and md5 build ids and verifies it's added properly. The test updates build id cache with 'perf record' and 'perf buildid-cache -a'. Committer testing: # perf test "build id" 82: build id cache operations : Ok # # perf test -v "build id" 82: build id cache operations : --- start --- test child forked, pid 447218 test binaries: /tmp/perf.ex.SHA1.B8I /tmp/perf.ex.MD5.7Nv Adding d1abc1eb7568358cf23c959566f23462461834d1 /tmp/perf.ex.SHA1.B8I: Ok build id: d1abc1eb7568358cf23c959566f23462461834d1 link: /tmp/perf.debug.sS2/.build-id/d1/abc1eb7568358cf23c959566f23462461834d1 file: /tmp/perf.debug.sS2/.build-id/d1/../../tmp/perf.ex.SHA1.B8I/d1abc1eb7568358cf23c959566f23462461834d1/elf OK for /tmp/perf.ex.SHA1.B8I Adding a50e350e97c43b4708d09bcd85ebfff7 /tmp/perf.ex.MD5.7Nv: Ok build id: a50e350e97c43b4708d09bcd85ebfff7 link: /tmp/perf.debug.IuW/.build-id/a5/0e350e97c43b4708d09bcd85ebfff7 file: /tmp/perf.debug.IuW/.build-id/a5/../../tmp/perf.ex.MD5.7Nv/a50e350e97c43b4708d09bcd85ebfff7/elf OK for /tmp/perf.ex.MD5.7Nv [ perf record: Woken up 1 times to write data ] [ perf record: Captured and wrote 0.034 MB /tmp/perf.data.xrH ] build id: d1abc1eb7568358cf23c959566f23462461834d1 link: /tmp/perf.debug.eGR/.build-id/d1/abc1eb7568358cf23c959566f23462461834d1 file: /tmp/perf.debug.eGR/.build-id/d1/../../tmp/perf.ex.SHA1.B8I/d1abc1eb7568358cf23c959566f23462461834d1/elf OK for /tmp/perf.ex.SHA1.B8I [ perf record: Woken up 2 times to write data ] [ perf record: Captured and wrote 0.034 MB /tmp/perf.data.cbE ] build id: a50e350e97c43b4708d09bcd85ebfff7 link: /tmp/perf.debug.82t/.build-id/a5/0e350e97c43b4708d09bcd85ebfff7 file: /tmp/perf.debug.82t/.build-id/a5/../../tmp/perf.ex.MD5.7Nv/a50e350e97c43b4708d09bcd85ebfff7/elf OK for /tmp/perf.ex.MD5.7Nv test child finished with 0 ---- end ---- build id cache operations: Ok # Signed-off-by:
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Jiri Olsa authored
With shorter md5 build ids we need to align their paths properly with other build ids: $ perf buildid-list 17f4e448cc746582ea1881528deb549f7fdb3fd5 [kernel.kallsyms] a50e350e97c43b4708d09bcd85ebfff7 .../tools/perf/buildid-ex-md5 1805c738c8f3ec0f47b7ea09080c28f34d18a82b /usr/lib64/ld-2.31.so $ Signed-off-by:
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Jiri Olsa authored
We do not store size with build ids in perf data, but there's enough space to do it. Adding misc bit PERF_RECORD_MISC_BUILD_ID_SIZE to mark build id event with size. With this fix the dso with md5 build id will have correct build id data and will be usable for debuginfod processing if needed (coming in following patches). Committer notes: Use %zu with size_t to fix this error on 32-bit arches: util/header.c: In function '__event_process_build_id': util/header.c:2105:3: error: format '%lu' expects argument of type 'long unsigned int', but argument 6 has type 'size_t' [-Werror=format=] pr_debug("build id event received for %s: %s [%lu]\n", ^ Signed-off-by: -
Jiri Olsa authored
Passing build_id object to dso__build_id_equal(), so we can properly check build id with different size than sha1. Signed-off-by:
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Jiri Olsa authored
Passing build_id object to dso__set_build_id(), so it's easier to initialize dos's build id object. Signed-off-by:
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Jiri Olsa authored
Passing build_id object to build_id__sprintf function, so it can operate with the proper size of build id. This will create proper md5 build id readable names, like following: a50e350e97c43b4708d09bcd85ebfff7 instead of: a50e350e97c43b4708d09bcd85ebfff700000000 Signed-off-by:
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Jiri Olsa authored
Passing build id object to sysfs__read_build_id function, so it can populate the size of the build_id object. Signed-off-by:
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Jiri Olsa authored
Pass a build_id object to filename__read_build_id function, so it can populate the size of the build_id object. Changing filename__read_build_id() code for both ELF/non-ELF code. Signed-off-by:
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Jiri Olsa authored
Replace build_id byte array with struct build_id object and all the code that references it. The objective is to carry size together with build id array, so it's better to keep both together. This is preparatory change for following patches, and there's no functional change. Signed-off-by:
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- Oct 13, 2020
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Arnaldo Carvalho de Melo authored
We'll use it to ask for extra config files to be loaded, profile like stuff that will be used first to make 'perf trace' mimic 'strace' output via a 'perf strace' command that just sets up 'perf trace' output. At some point it'll be used for regression tests, where we'll run some simple commands like: perf strace ls > perf-strace.output strace ls > strace.output And then do some mutable syscall arg aware diff like tool to deal with arguments for things like mmap, that change at each execution, to be first ignored and then properly tracked when used accoss multiple syscalls. Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Ian Rogers <irogers@google.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Signed-off-by: -
James Clark authored
Some distros don't come with python2 and only have python3 available. This causes the "'import perf' in python" self test to fail. This change adds python3 to the list of possible python versions that are autodetected but maintains the priorities for 'python2' and 'python' detection. Python3 has the lowest priority. Committer notes: On a fedora system without python2 packages the 'perf test python' continues to work: # python2 bash: python2: command not found... Similar command is: 'python' # rpm -qa | grep python2 # That "Similar command" gives the clue: # rpm -qf /usr/bin/python python-unversioned-command-3.8.5-5.fc32.noarch # rpm -ql python-unversioned-command /usr/bin/python /usr/share/man/man1/python.1.gz # With it in place the 'python' binary is found and perf builds the python binding using python3: # perf test -v python 19: 'import perf' in python : --- start --- test child forked, pid 379988 python usage test: "echo "import sys ; sys.path.append('/tmp/build/perf/python'); import perf" | '/usr/bin/python' " test child finished with 0 ---- end ---- 'import perf' in python: Ok # Looking at that path: # ls -la /tmp/build/perf/python total 1864 drwxrwxr-x. 2 acme acme 60 Oct 13 16:20 . drwxrwxr-x. 18 acme acme 4420 Oct 13 16:28 .. -rwxrwxr-x. 1 acme acme 1907216 Oct 13 16:28 perf.cpython-38-x86_64-linux-gnu.so # And: # ldd ~/bin/perf | grep python libpython3.8.so.1.0 => /lib64/libpython3.8.so.1.0 (0x00007f5471187000) # As soon as we remove it: # rpm -e python-unversioned-command-3.8.5-5.fc32.noarch # hash -r # python bash: python: command not found... Install package 'python-unversioned-command' to provide command 'python'? [N/y] n # And rebuilding perf now doesn't find python in the system: make: Entering directory '/home/acme/git/perf/tools/perf' BUILD: Doing 'make -j24' parallel build <SNIP> Makefile.config:786: No python interpreter was found: disables Python support - please install python-devel/python-dev <SNIP> After this patch: $ rpm -qi python-unversioned-command package python-unversioned-command is not installed $ $ python bash: python: command not found... Install package 'python-unversioned-command' to provide command 'python'? [N/y] ^C $ $ m make: Entering directory '/home/acme/git/perf/tools/perf' BUILD: Doing 'make -j24' parallel build <SNIP> CC /tmp/build/perf/tests/attr.o CC /tmp/build/perf/tests/python-use.o DESCEND plugins GEN /tmp/build/perf/python/perf.so INSTALL trace_plugins LD /tmp/build/perf/tests/perf-in.o LD /tmp/build/perf/perf-in.o LINK /tmp/build/perf/perf <SNIP> make: Leaving directory '/home/acme/git/perf/tools/perf' 19: 'import perf' in python : Ok $ ldd ~/bin/perf | grep python libpython3.8.so.1.0 => /lib64/libpython3.8.so.1.0 (0x00007f2c8c708000) $ ls -la /tmp/build/perf/python total 1864 drwxrwxr-x. 2 acme acme 60 Oct 13 16:20 . drwxrwxr-x. 18 acme acme 4420 Oct 13 16:31 .. -rwxrwxr-x. 1 acme acme 1907216 Oct 13 16:31 perf.cpython-38-x86_64-linux-gnu.so $ Signed-off-by:James Clark <james.clark@arm.com> Cc: Alexander Shishkin <alexander.shishkin@linux.intel.com> Cc: Jiri Olsa <jolsa@redhat.com> Cc: Mark Rutland <mark.rutland@arm.com> Cc: Namhyung Kim <namhyung@kernel.org> Cc: Peter Zijlstra <peterz@infradead.org> LPU-Reference: 20201005080645.6588-1-james.clark@arm.com Signed-off-by:
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Arnaldo Carvalho de Melo authored
To help figure out where it is getting the binding. Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Ian Rogers <irogers@google.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Signed-off-by: -
Vasily Gorbik authored
Currently BUILD_BUG() macro is expanded to smth like the following: do { extern void __compiletime_assert_0(void) __attribute__((error("BUILD_BUG failed"))); if (!(!(1))) __compiletime_assert_0(); } while (0); If used in a function body this obviously would produce build errors with -Wnested-externs and -Werror. To enable BUILD_BUG() usage in tools/arch/x86/lib/insn.c which perf includes in intel-pt-decoder, build perf without -Wnested-externs. Reported-by:Stephen Rothwell <sfr@canb.auug.org.au> Signed-off-by:
Vasily Gorbik <gor@linux.ibm.com> Acked-by:
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Jiri Slaby authored
'perf trace ls' started crashing after commit d21cb73a on !HAVE_SYSCALL_TABLE_SUPPORT configs (armv7l here) like this: 0 strlen () at ../sysdeps/arm/armv6t2/strlen.S:126 1 0xb6800780 in __vfprintf_internal (s=0xbeff9908, s@entry=0xbeff9900, format=0xa27160 "]: %s()", ap=..., mode_flags=<optimized out>) at vfprintf-internal.c:1688 ... 5 0x0056ecdc in fprintf (__fmt=0xa27160 "]: %s()", __stream=<optimized out>) at /usr/include/bits/stdio2.h:100 6 trace__sys_exit (trace=trace@entry=0xbeffc710, evsel=evsel@entry=0xd968d0, event=<optimized out>, sample=sample@entry=0xbeffc3e8) at builtin-trace.c:2475 7 0x00566d40 in trace__handle_event (sample=0xbeffc3e8, event=<optimized out>, trace=0xbeffc710) at builtin-trace.c:3122 ... 15 main (argc=2, argv=0xbefff6e8) at perf.c:538 It is because memset in trace__read_syscall_info zeroes wrong memory: 1) when initializing for the first time, it does not reset the last id. 2) in other cases, it resets the last id of previous buffer. ad 1) it causes the crash above as sc->name used in the fprintf above contains garbage. ad 2) it sets nonexistent from true back to false for id 11 here. Not sure, what the consequences are. So fix it by introducing a special case for the initial initialization and do the right +1 in both cases. Fixes: d21cb73a ("perf trace: Grow the syscall table as needed when using libaudit") Signed-off-by:
Jiri Slaby <jslaby@suse.cz> Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Cc: Peter Zijlstra <peterz@infradead.org> Link: http://lore.kernel.org/lkml/20201001093419.15761-1-jslaby@suse.cz Signed-off-by:
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Leo Yan authored
Since commit b027cc6f ("perf c2c: Fix 'perf c2c record -e list' to show the default events used"), "perf c2c" tool can show the memory events properly, it's no reason to still suggest user to use the command "perf mem record -e list" for showing events. This patch updates the usage for showing memory events with command "perf c2c record -e list". Signed-off-by:
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Arnaldo Carvalho de Melo authored
To pick fixes that missed v5.9. Signed-off-by: -
Tzvetomir Stoyanov (VMware) authored
There are internal library functions, which are not declared as a static. They are used inside the library from different files. Hide them from the library users, as they are not part of the API. These functions are made hidden and are renamed without the prefix "tep_": tep_free_plugin_paths tep_peek_char tep_buffer_init tep_get_input_buf_ptr tep_get_input_buf tep_read_token tep_free_token tep_free_event tep_free_format_field __tep_parse_format Link: https://lore.kernel.org/linux-trace-devel/e4afdd82deb5e023d53231bb13e08dca78085fb0.camel@decadent.org.uk/ Reported-by:
Ben Hutchings <ben@decadent.org.uk> Signed-off-by:
Tzvetomir Stoyanov (VMware) <tz.stoyanov@gmail.com> Reviewed-by:
Steven Rostedt (VMware) <rostedt@goodmis.org> Cc: linux-trace-devel@vger.kernel.org Link: http://lore.kernel.org/lkml/20200930110733.280534-1-tz.stoyanov@gmail.com Signed-off-by:
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Joel Fernandes (Google) authored
The 'perf sched latency' tool is really useful at showing worst-case latencies that task encountered since wakeup. However it shows only the end of the latency. Often times the start of a latency is interesting as it can show what else was going on at the time to cause the latency. I certainly myself spending a lot of time backtracking to the start of the latency in "perf sched script" which wastes a lot of time. This patch therefore adds a new column "Max delay start". Considering this, also rename "Maximum delay at" to "Max delay end" as its easier to understand. Example of the new output: ---------------------------------------------------------------------------------------------------------------------------------- Task | Runtime ms | Switches | Avg delay ms | Max delay ms | Max delay start | Max delay end | ---------------------------------------------------------------------------------------------------------------------------------- MediaScannerSer:11936 | 651.296 ms | 67978 | avg: 0.113 ms | max: 77.250 ms | max start: 477.691360 s | max end: 477.768610 s audio@2.0-servi:(3) | 0.000 ms | 3440 | avg: 0.034 ms | max: 72.267 ms | max start: 477.697051 s | max end: 477.769318 s AudioOut_1D:8112 | 0.000 ms | 2588 | avg: 0.083 ms | max: 64.020 ms | max start: 477.710740 s | max end: 477.774760 s Time-limited te:14973 | 7966.090 ms | 24807 | avg: 0.073 ms | max: 15.563 ms | max start: 477.162746 s | max end: 477.178309 s surfaceflinger:8049 | 9.680 ms | 603 | avg: 0.063 ms | max: 13.275 ms | max start: 476.931791 s | max end: 476.945067 s HeapTaskDaemon:(3) | 1588.830 ms | 7040 | avg: 0.065 ms | max: 6.880 ms | max start: 473.666043 s | max end: 473.672922 s mount-passthrou:(3) | 1370.809 ms | 68904 | avg: 0.011 ms | max: 6.524 ms | max start: 478.090630 s | max end: 478.097154 s ReferenceQueueD:(3) | 11.794 ms | 1725 | avg: 0.014 ms | max: 6.521 ms | max start: 476.119782 s | max end: 476.126303 s writer:14077 | 18.410 ms | 1427 | avg: 0.036 ms | max: 6.131 ms | max start: 474.169675 s | max end: 474.175805 s Signed-off-by:
Joel Fernandes (Google) <joel@joelfernandes.org> Acked-by:
Namhyung Kim <namhyung@kernel.org> Link: https://lore.kernel.org/r/20200925235634.4089867-1-joel@joelfernandes.org Signed-off-by:
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Sandipan Das authored
This replaces the incorrectly spelled word "localtion" with "location" in some power8 PMU event descriptions. Fixes: 2a81fa3b ("perf vendor events: Add power8 PMU events") Signed-off-by:
Sandipan Das <sandipan@linux.ibm.com> Reviewed-by:
Kajol Jain <kjain@linux.ibm.com> Cc: Jiri Olsa <jolsa@redhat.com> Cc: Madhavan Srinivasan <maddy@linux.vnet.ibm.com> Cc: Michael Ellerman <mpe@ellerman.id.au> Cc: Ravi Bangoria <ravi.bangoria@linux.ibm.com> Cc: Sukadev Bhattiprolu <sukadev@linux.vnet.ibm.com> Link: http://lore.kernel.org/lkml/20201012050205.328523-1-sandipan@linux.ibm.com Signed-off-by:
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Namhyung Kim authored
For comparison, it now runs the benchmark twice - one if regular -b and another for --buildid-all. $ perf bench internals inject-build-id # Running 'internals/inject-build-id' benchmark: Average build-id injection took: 21.002 msec (+- 0.172 msec) Average time per event: 2.059 usec (+- 0.017 usec) Average memory usage: 8169 KB (+- 0 KB) Average build-id-all injection took: 19.543 msec (+- 0.124 msec) Average time per event: 1.916 usec (+- 0.012 usec) Average memory usage: 7348 KB (+- 0 KB) Signed-off-by: -
Namhyung Kim authored
Like 'perf record', we can even more speedup build-id processing by just using all DSOs. Then we don't need to look at all the sample events anymore. The following patch will update 'perf bench' to show the result of the --buildid-all option too. Signed-off-by:
Stephane Eranian <eranian@google.com> Acked-by:
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Namhyung Kim authored
No need to load symbols in a DSO when injecting build-id. I guess the reason was to check the DSO is a special file like anon files. Use some helper functions in map.c to check them before reading build-id. Also pass sample event's cpumode to a new build-id event. It brought a speedup in the benchmark of 25 -> 21 msec on my laptop. Also the memory usage (Max RSS) went down by ~200 KB. # Running 'internals/inject-build-id' benchmark: Average build-id injection took: 21.389 msec (+- 0.138 msec) Average time per event: 2.097 usec (+- 0.014 usec) Average memory usage: 8225 KB (+- 0 KB) Committer notes: Before: $ perf stat -r5 perf bench internals inject-build-id > /dev/null Performance counter stats for 'perf bench internals inject-build-id' (5 runs): 4,020.56 msec task-clock:u # 1.271 CPUs utilized ( +- 0.74% ) 0 context-switches:u # 0.000 K/sec 0 cpu-migrations:u # 0.000 K/sec 123,354 page-faults:u # 0.031 M/sec ( +- 0.81% ) 7,119,951,568 cycles:u # 1.771 GHz ( +- 1.74% ) (83.27%) 230,086,969 stalled-cycles-frontend:u # 3.23% frontend cycles idle ( +- 1.97% ) (83.41%) 1,168,298,765 stalled-cycles-backend:u # 16.41% backend cycles idle ( +- 1.13% ) (83.44%) 11,173,083,669 instructions:u # 1.57 insn per cycle # 0.10 stalled cycles per insn ( +- 1.58% ) (83.31%) 2,413,908,936 branches:u # 600.392 M/sec ( +- 1.69% ) (83.26%) 46,576,289 branch-misses:u # 1.93% of all branches ( +- 2.20% ) (83.31%) 3.1638 +- 0.0309 seconds time elapsed ( +- 0.98% ) $ After: $ perf stat -r5 perf bench internals inject-build-id > /dev/null Performance counter stats for 'perf bench internals inject-build-id' (5 runs): 2,379.94 msec task-clock:u # 1.473 CPUs utilized ( +- 0.18% ) 0 context-switches:u # 0.000 K/sec 0 cpu-migrations:u # 0.000 K/sec 62,584 page-faults:u # 0.026 M/sec ( +- 0.07% ) 2,372,389,668 cycles:u # 0.997 GHz ( +- 0.29% ) (83.14%) 106,937,862 stalled-cycles-frontend:u # 4.51% frontend cycles idle ( +- 4.89% ) (83.20%) 581,697,915 stalled-cycles-backend:u # 24.52% backend cycles idle ( +- 0.71% ) (83.47%) 3,659,692,199 instructions:u # 1.54 insn per cycle # 0.16 stalled cycles per insn ( +- 0.10% ) (83.63%) 791,372,961 branches:u # 332.518 M/sec ( +- 0.27% ) (83.39%) 10,648,083 branch-misses:u # 1.35% of all branches ( +- 0.22% ) (83.16%) 1.61570 +- 0.00172 seconds time elapsed ( +- 0.11% ) $ Signed-off-by: -
Namhyung Kim authored
It should be in a proper mnt namespace when accessing the file. I think this had no problem since the build-id was actually read from map__load() -> dso__load() already. But I'd like to change it in the following commit. Acked-by:
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