- 04 11月, 2020 10 次提交
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由 Arnaldo Carvalho de Melo 提交于
If libbpf isn't selected, no need for a bunch of related code, that were not even being used, as code using these perf_env methods was also enclosed in HAVE_LIBBPF_SUPPORT. 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: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Arnaldo Carvalho de Melo 提交于
No need to include it otherwise. 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: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Arnaldo Carvalho de Melo 提交于
If either NO_LIBBPF=1 is passed, explicitely disabling it or if libbpf is not available due to some missing dependency, skip its tests, telling the user the feature isn't available. # perf test <SNIP> 40: LLVM search and compile : Skip (not compiled in) 41: Session topology : Ok 42: BPF filter : Skip (not compiled in) <SNIP> 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: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Arnaldo Carvalho de Melo 提交于
As it uses the 'deprecated' attribute in a way that breaks the build with old gcc compilers, so to continue being able to build in such systems where NO_LIBBPF=1 is being used, enclose it under HAVE_LIBBPF_SUPPORT. 1 centos:6 : FAIL gcc (GCC) 4.4.7 20120313 (Red Hat 4.4.7-23) 2 oraclelinux:6 : FAIL gcc (GCC) 4.4.7 20120313 (Red Hat 4.4.7-23.0.1) CC /tmp/build/perf/builtin-record.o In file included from util/bpf-loader.h:11, from builtin-record.c:39: /git/linux/tools/lib/bpf/libbpf.h:203: error: wrong number of arguments specified for 'deprecated' attribute 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: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Tommi Rantala 提交于
Currently reason for skipping the read only watchpoint test is only seen when running in verbose mode: $ perf test watchpoint 23: Watchpoint : 23.1: Read Only Watchpoint : Skip 23.2: Write Only Watchpoint : Ok 23.3: Read / Write Watchpoint : Ok 23.4: Modify Watchpoint : Ok $ perf test -v watchpoint 23: Watchpoint : 23.1: Read Only Watchpoint : --- start --- test child forked, pid 60204 Hardware does not support read only watchpoints. test child finished with -2 Implement skip_reason callback for the watchpoint tests, so that it's easy to see reason why the test is skipped: $ perf test watchpoint 23: Watchpoint : 23.1: Read Only Watchpoint : Skip (missing hardware support) 23.2: Write Only Watchpoint : Ok 23.3: Read / Write Watchpoint : Ok 23.4: Modify Watchpoint : Ok Signed-off-by: NTommi Rantala <tommi.t.rantala@nokia.com> Tested-by: NArnaldo Carvalho de Melo <acme@redhat.com> Acked-by: NNamhyung Kim <namhyung@kernel.org> Link: https://lore.kernel.org/r/20201016131650.72476-1-tommi.t.rantala@nokia.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
So far tsc is enabled on x86_64, i386 and Arm64 architectures, add checking helper to skip this testing for other architectures. Signed-off-by: NLeo Yan <leo.yan@linaro.org> Acked-by: NJiri Olsa <jolsa@redhat.com> Tested-by: NArnaldo Carvalho de Melo <acme@redhat.com> Link: https://lore.kernel.org/r/20201019100236.23675-3-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
x86 arch provides the testing for conversion between tsc and perf time, the testing is located in x86 arch folder. Move this testing out from x86 arch folder and place it into the common testing folder, so allows to execute tsc testing on other architectures (e.g. Arm64). This patch removes the inclusion of "arch-tests.h" from the testing code, this can avoid building failure if any arch has no this header file. Committer testing: $ perf test -v tsc Couldn't bump rlimit(MEMLOCK), failures may take place when creating BPF maps, etc 70: Convert perf time to TSC : --- start --- test child forked, pid 4032834 mmap size 528384B 1st event perf time 165409788843605 tsc 336578703793868 rdtsc time 165409788854986 tsc 336578703837038 2nd event perf time 165409788855487 tsc 336578703838935 test child finished with 0 ---- end ---- Convert perf time to TSC: Ok $ Signed-off-by: NLeo Yan <leo.yan@linaro.org> Acked-by: NJiri Olsa <jolsa@redhat.com> Tested-by: NArnaldo Carvalho de Melo <acme@redhat.com> Link: https://lore.kernel.org/r/20201019100236.23675-2-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
Some archs (e.g. x86 and Arm64) don't enable the configuration CONFIG_MEMORY_HOTPLUG by default, if this configuration is not enabled when build the kernel image, the SysFS for memory nodes will be missed. This results in perf tool has no chance to catpure the memory nodes information, when perf tool reports the result and detects no memory nodes, it outputs "assertion failed at util/mem2node.c:99". The output log doesn't give out reason for the failure and users have no clue for how to fix it. This patch changes to use explicit way for warning: it tells user that detected no memory nodes and suggests to enable CONFIG_MEMORY_HOTPLUG for kernel building. Signed-off-by: NLeo Yan <leo.yan@linaro.org> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201019003613.8399-1-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Ian Rogers 提交于
If perf is built with libpfm4 (LIBPFM4=1) then advertise it in perf -vv. Signed-off-by: NIan Rogers <irogers@google.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> Cc: Stephane Eranian <eranian@google.com> Link: http://lore.kernel.org/lkml/20201019232545.4047264-1-irogers@google.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Dengcheng Zhu 提交于
Support the MIPS architecture using the ins_ops association method. With this patch, perf-annotate can work well on MIPS. Testing it with a perf.data file collected on a mips machine: $./perf annotate -i perf.data : Disassembly of section .text: : : 00000000000be6a0 <get_next_seq>: : get_next_seq(): 0.00 : be6a0: lw v0,0(a0) 0.00 : be6a4: daddiu sp,sp,-128 0.00 : be6a8: ld a7,72(a0) 0.00 : be6ac: gssq s5,s4,80(sp) 0.00 : be6b0: gssq s1,s0,48(sp) 0.00 : be6b4: gssq s8,gp,112(sp) 0.00 : be6b8: gssq s7,s6,96(sp) 0.00 : be6bc: gssq s3,s2,64(sp) 0.00 : be6c0: sd a3,0(sp) 0.00 : be6c4: move s0,a0 0.00 : be6c8: sd v0,32(sp) 0.00 : be6cc: sd a5,8(sp) 0.00 : be6d0: sd zero,8(a0) 0.00 : be6d4: sd a6,16(sp) 0.00 : be6d8: ld s2,48(a0) 8.53 : be6dc: ld s1,40(a0) 9.42 : be6e0: ld v1,32(a0) 0.00 : be6e4: nop 0.00 : be6e8: ld s4,24(a0) 0.00 : be6ec: ld s5,16(a0) 0.00 : be6f0: sd a7,40(sp) 10.11 : be6f4: ld s6,64(a0) ... The original patch link: https://lore.kernel.org/patchwork/patch/1180480/Signed-off-by: NDengcheng Zhu <dzhu@wavecomp.com> Cc: Dengcheng Zhu <dzhu@wavecomp.com> Cc: Jiaxun Yang <jiaxun.yang@flygoat.com> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Xuefeng Li <lixuefeng@loongson.cn> Cc: linux-mips@vger.kernel.org [ fanpeng@loongson.cn: Add missing "bgtzl", "bltzl", "bgezl", "blezl", "beql" and "bnel" for pre-R6processors ] Signed-off-by: NPeng Fan <fanpeng@loongson.cn> Signed-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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- 03 11月, 2020 12 次提交
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由 Namhyung Kim 提交于
It was missed to add a swap function for PERF_RECORD_CGROUP. Fixes: ba78c1c5 ("perf tools: Basic support for CGROUP event") Signed-off-by: NNamhyung Kim <namhyung@kernel.org> Acked-by: NJiri Olsa <jolsa@redhat.com> Cc: Alexander Shishkin <alexander.shishkin@linux.intel.com> Cc: Ian Rogers <irogers@google.com> Cc: Mark Rutland <mark.rutland@arm.com> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Stephane Eranian <eranian@google.com> Link: http://lore.kernel.org/lkml/20201102140228.303657-1-namhyung@kernel.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jiri Olsa 提交于
We are missing swap for ino_generation field. Fixes: 5c5e854b ("perf tools: Add attr->mmap2 support") Signed-off-by: NJiri Olsa <jolsa@kernel.org> Acked-by: NNamhyung Kim <namhyung@kernel.org> Link: https://lore.kernel.org/r/20201101233103.3537427-2-jolsa@kernel.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jiri Olsa 提交于
We display garbage for undefined build_id objects, because we don't initialize the output buffer. Signed-off-by: NJiri Olsa <jolsa@kernel.org> Acked-by: NNamhyung Kim <namhyung@kernel.org> Link: https://lore.kernel.org/r/20201101233103.3537427-1-jolsa@kernel.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Song Liu 提交于
Making perf with gcc-9.1.1 generates the following warning: CC ui/browsers/hists.o ui/browsers/hists.c: In function 'perf_evsel__hists_browse': ui/browsers/hists.c:3078:61: error: '%d' directive output may be \ truncated writing between 1 and 11 bytes into a region of size \ between 2 and 12 [-Werror=format-truncation=] 3078 | "Max event group index to sort is %d (index from 0 to %d)", | ^~ ui/browsers/hists.c:3078:7: note: directive argument in the range [-2147483648, 8] 3078 | "Max event group index to sort is %d (index from 0 to %d)", | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/include/stdio.h:937, from ui/browsers/hists.c:5: IOW, the string in line 3078 might be too long for buf[] of 64 bytes. Fix this by increasing the size of buf[] to 128. Fixes: dbddf174 ("perf report/top TUI: Support hotkeys to let user select any event for sorting") Signed-off-by: NSong Liu <songliubraving@fb.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Cc: Jin Yao <yao.jin@linux.intel.com> Cc: stable@vger.kernel.org # v5.7+ Link: http://lore.kernel.org/lkml/20201030235431.534417-1-songliubraving@fb.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Arnaldo Carvalho de Melo 提交于
To avoid this: util/scripting-engines/trace-event-python.c: In function 'python_start_script': util/scripting-engines/trace-event-python.c:1595:2: error: 'visibility' attribute ignored [-Werror=attributes] 1595 | PyMODINIT_FUNC (*initfunc)(void); | ^~~~~~~~~~~~~~ That started breaking when building with PYTHON=python3 and these gcc versions (I haven't checked with the clang ones, maybe it breaks there as well): # export PERF_TARBALL=http://192.168.86.5/perf/perf-5.9.0.tar.xz # dm fedora:33 fedora:rawhide 1 107.80 fedora:33 : Ok gcc (GCC) 10.2.1 20201005 (Red Hat 10.2.1-5), clang version 11.0.0 (Fedora 11.0.0-1.fc33) 2 92.47 fedora:rawhide : Ok gcc (GCC) 10.2.1 20201016 (Red Hat 10.2.1-6), clang version 11.0.0 (Fedora 11.0.0-1.fc34) # Avoid that by ditching that 'initfunc' function pointer with its: #define Py_EXPORTED_SYMBOL _attribute_ ((visibility ("default"))) #define PyMODINIT_FUNC Py_EXPORTED_SYMBOL PyObject* And just call PyImport_AppendInittab() at the end of the ifdef python3 block with the functions that were being attributed to that initfunc. 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: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Peter Zijlstra 提交于
The GCC specific __attribute__((optimize)) attribute does not what is commonly expected and is explicitly recommended against using in production code by the GCC people. Unlike what is often expected, it doesn't add to the optimization flags, but it fully replaces them, loosing any and all optimization flags provided by the compiler commandline. The only guaranteed upon means of inhibiting tail-calls is by placing a volatile asm with side-effects after the call such that the tail-call simply cannot be done. Given the original commit wasn't specific on which calls were the problem, this removal might re-introduce the problem, which can then be re-analyzed and cured properly. Signed-off-by: NPeter Zijlstra <peterz@infradead.org> Acked-by: NArd Biesheuvel <ardb@kernel.org> Acked-by: NMiguel Ojeda <ojeda@kernel.org> Cc: Alexei Starovoitov <ast@kernel.org> Cc: Arnd Bergmann <arnd@arndb.de> Cc: Arvind Sankar <nivedita@alum.mit.edu> Cc: Daniel Borkmann <daniel@iogearbox.net> Cc: Geert Uytterhoeven <geert@linux-m68k.org> Cc: Ian Rogers <irogers@google.com> Cc: Josh Poimboeuf <jpoimboe@redhat.com> Cc: Kees Kook <keescook@chromium.org> Cc: Martin Liška <mliska@suse.cz> Cc: Nick Desaulniers <ndesaulniers@google.com> Cc: Randy Dunlap <rdunlap@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Link: http://lore.kernel.org/lkml/20201028081123.GT2628@hirez.programming.kicks-ass.netSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jin Yao 提交于
Ian reports an issue that the metric DRAM_BW_Use often remains 0. The metric expression for DRAM_BW_Use on CLX/SKX: "( 64 * ( uncore_imc@cas_count_read@ + uncore_imc@cas_count_write@ ) / 1000000000 ) / duration_time" The counts of uncore_imc/cas_count_read/ and uncore_imc/cas_count_write/ are scaled up by 64, that is to turn a count of cache lines into bytes, the count is then divided by 1000000000 to give GB. However, the counts of uncore_imc/cas_count_read/ and uncore_imc/cas_count_write/ have been scaled yet. The scale values are from sysfs, such as /sys/devices/uncore_imc_0/events/cas_count_read.scale. It's 6.103515625e-5 (64 / 1024.0 / 1024.0). So if we use original metric expression, the result is not correct. But the difficulty is, for SKL client, the counts are not scaled. The metric expression for DRAM_BW_Use on SKL: "64 * ( arb@event\\=0x81\\,umask\\=0x1@ + arb@event\\=0x84\\,umask\\=0x1@ ) / 1000000 / duration_time / 1000" root@kbl-ppc:~# perf stat -M DRAM_BW_Use -a -- sleep 1 Performance counter stats for 'system wide': 190 arb/event=0x84,umask=0x1/ # 1.86 DRAM_BW_Use 29,093,178 arb/event=0x81,umask=0x1/ 1,000,703,287 ns duration_time 1.000703287 seconds time elapsed The result is expected. So the easy way is just change the metric expression for CLX/SKX. This patch changes the metric expression to: "( ( ( uncore_imc@cas_count_read@ + uncore_imc@cas_count_write@ ) * 1048576 ) / 1000000000 ) / duration_time" 1048576 = 1024 * 1024. Before (tested on CLX): root@lkp-csl-2sp5 ~# perf stat -M DRAM_BW_Use -a -- sleep 1 Performance counter stats for 'system wide': 765.35 MiB uncore_imc/cas_count_read/ # 0.00 DRAM_BW_Use 5.42 MiB uncore_imc/cas_count_write/ 1001515088 ns duration_time 1.001515088 seconds time elapsed After: root@lkp-csl-2sp5 ~# perf stat -M DRAM_BW_Use -a -- sleep 1 Performance counter stats for 'system wide': 767.95 MiB uncore_imc/cas_count_read/ # 0.80 DRAM_BW_Use 5.02 MiB uncore_imc/cas_count_write/ 1001900010 ns duration_time 1.001900010 seconds time elapsed Fixes: 038d3b53 ("perf vendor events intel: Update CascadelakeX events to v1.08") Fixes: b5ff7f27 ("perf vendor events: Update SkylakeX events to v1.21") Signed-off-by: NJin Yao <yao.jin@linux.intel.com> Acked-by: NIan Rogers <irogers@google.com> Cc: Alexander Shishkin <alexander.shishkin@linux.intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Kan Liang <kan.liang@linux.intel.com> Cc: Peter Zijlstra <peterz@infradead.org> Link: http://lore.kernel.org/lkml/20201023005334.7869-1-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Stanislav Ivanichkin 提交于
# ./perf trace -e sched:sched_switch -G test -a sleep 1 perf: Segmentation fault Obtained 11 stack frames. ./perf(sighandler_dump_stack+0x43) [0x55cfdc636db3] /lib/x86_64-linux-gnu/libc.so.6(+0x3efcf) [0x7fd23eecafcf] ./perf(parse_cgroups+0x36) [0x55cfdc673f36] ./perf(+0x3186ed) [0x55cfdc70d6ed] ./perf(parse_options_subcommand+0x629) [0x55cfdc70e999] ./perf(cmd_trace+0x9c2) [0x55cfdc5ad6d2] ./perf(+0x1e8ae0) [0x55cfdc5ddae0] ./perf(+0x1e8ded) [0x55cfdc5ddded] ./perf(main+0x370) [0x55cfdc556f00] /lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xe6) [0x7fd23eeadb96] ./perf(_start+0x29) [0x55cfdc557389] Segmentation fault # It happens because "struct trace" in option->value is passed to the parse_cgroups function instead of "struct evlist". Fixes: 9ea42ba4 ("perf trace: Support setting cgroups as targets") Signed-off-by: NStanislav Ivanichkin <sivanichkin@yandex-team.ru> Tested-by: NArnaldo Carvalho de Melo <acme@redhat.com> Acked-by: NNamhyung Kim <namhyung@kernel.org> Cc: Dmitry Monakhov <dmtrmonakhov@yandex-team.ru> Link: http://lore.kernel.org/lkml/20201027094357.94881-1-sivanichkin@yandex-team.ruSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Tommi Rantala 提交于
The addr in PERF_RECORD_KSYMBOL events for non-jited bpf progs points to the bpf interpreter, ie. within kernel text section. When processing the unregister event, this causes unexpected removal of vmlinux_map, crashing perf later in cleanup: # perf record -- timeout --signal=INT 2s /usr/share/bcc/tools/execsnoop PCOMM PID PPID RET ARGS [ perf record: Woken up 1 times to write data ] [ perf record: Captured and wrote 0.208 MB perf.data (5155 samples) ] perf: tools/include/linux/refcount.h:131: refcount_sub_and_test: Assertion `!(new > val)' failed. Aborted (core dumped) # perf script -D|grep KSYM 0 0xa40 [0x48]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b530 len 0 type 1 flags 0x0 name bpf_prog_f958f6eb72ef5af6 0 0xab0 [0x48]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b530 len 0 type 1 flags 0x0 name bpf_prog_8c42dee26e8cd4c2 0 0xb20 [0x48]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b530 len 0 type 1 flags 0x0 name bpf_prog_f958f6eb72ef5af6 108563691893 0x33d98 [0x58]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b3b0 len 0 type 1 flags 0x0 name bpf_prog_bc5697a410556fc2_syscall__execve 108568518458 0x34098 [0x58]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b3f0 len 0 type 1 flags 0x0 name bpf_prog_45e2203c2928704d_do_ret_sys_execve 109301967895 0x34830 [0x58]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b3b0 len 0 type 1 flags 0x1 name bpf_prog_bc5697a410556fc2_syscall__execve 109302007356 0x348b0 [0x58]: PERF_RECORD_KSYMBOL addr ffffffffa9b6b3f0 len 0 type 1 flags 0x1 name bpf_prog_45e2203c2928704d_do_ret_sys_execve perf: tools/include/linux/refcount.h:131: refcount_sub_and_test: Assertion `!(new > val)' failed. Here the addresses match the bpf interpreter: # grep -e ffffffffa9b6b530 -e ffffffffa9b6b3b0 -e ffffffffa9b6b3f0 /proc/kallsyms ffffffffa9b6b3b0 t __bpf_prog_run224 ffffffffa9b6b3f0 t __bpf_prog_run192 ffffffffa9b6b530 t __bpf_prog_run32 Fix by not allowing vmlinux_map to be removed by PERF_RECORD_KSYMBOL unregister event. Signed-off-by: NTommi Rantala <tommi.t.rantala@nokia.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Tested-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201016114718.54332-1-tommi.t.rantala@nokia.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Arnaldo Carvalho de Melo 提交于
To pick the changes from: ecb8ac8b ("mm/madvise: introduce process_madvise() syscall: an external memory hinting API") That addresses these perf build warning: Warning: Kernel ABI header at 'tools/include/uapi/asm-generic/unistd.h' differs from latest version at 'include/uapi/asm-generic/unistd.h' diff -u tools/include/uapi/asm-generic/unistd.h include/uapi/asm-generic/unistd.h Warning: Kernel ABI header at 'tools/perf/arch/x86/entry/syscalls/syscall_64.tbl' differs from latest version at 'arch/x86/entry/syscalls/syscall_64.tbl' diff -u tools/perf/arch/x86/entry/syscalls/syscall_64.tbl arch/x86/entry/syscalls/syscall_64.tbl Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Ian Rogers <irogers@google.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Signed-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Arnaldo Carvalho de Melo 提交于
To pick the changes in: 85367030 ("libbpf: Centralize poisoning and poison reallocarray()") 7d9c71e1 ("libbpf: Extract generic string hashing function for reuse") That don't entail any changes in tools/perf. This addresses this perf build warning: Warning: Kernel ABI header at 'tools/perf/util/hashmap.h' differs from latest version at 'tools/lib/bpf/hashmap.h' diff -u tools/perf/util/hashmap.h tools/lib/bpf/hashmap.h Not a kernel ABI, its just that this uses the mechanism in place for checking kernel ABI files drift. Cc: Adrian Hunter <adrian.hunter@intel.com> Cc: Alexei Starovoitov <ast@kernel.org> Cc: Andrii Nakryiko <andriin@fb.com> Cc: Ian Rogers <irogers@google.com> Cc: Jiri Olsa <jolsa@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Signed-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Justin M. Forbes 提交于
To avoid breaking the build by mixing files compiled with things coming from distro specific compiler options for perl with the rest of perf, i.e. to avoid this: `.gnu.debuglto_.debug_macro' referenced in section `.gnu.debuglto_.debug_macro' of /tmp/build/perf/util/scripting-engines/perf-in.o: defined in discarded section `.gnu.debuglto_.debug_macro[wm4.stdcpredef.h.19.8dc41bed5d9037ff9622e015fb5f0ce3]' of /tmp/build/perf/util/scripting-engines/perf-in.o Noticed on Fedora 33. Signed-off-by: NJustin M. Forbes <jforbes@fedoraproject.org> Bugzilla: https://bugzilla.redhat.com/show_bug.cgi?id=1593431 Cc: Jiri Olsa <jolsa@redhat.com> Link: https://src.fedoraproject.org/rpms/kernel-tools/c/589a32b62f0c12516ab7b34e3dd30d450145bfa4?branch=masterSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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- 15 10月, 2020 18 次提交
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由 Leo Yan 提交于
The output format for metrics has been reorganized, update documentation to reflect the changes for it. Signed-off-by: NLeo Yan <leo.yan@linaro.org> Cc: Al Grant <al.grant@arm.com> Cc: Alexander Shishkin <alexander.shishkin@linux.intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: David Ahern <dsahern@gmail.com> Cc: Don Zickus <dzickus@redhat.com> Cc: Ian Rogers <irogers@google.com> Cc: James Clark <james.clark@arm.com> Cc: Jiri Olsa <jolsa@redhat.com> Cc: Joe Mario <jmario@redhat.com> Cc: Kan Liang <kan.liang@linux.intel.com> Cc: Mark Rutland <mark.rutland@arm.com> Cc: Namhyung Kim <namhyung@kernel.org> Cc: Peter Zijlstra <peterz@infradead.org> Link: http://lore.kernel.org/lkml/20201015144548.18482-10-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
The metrics "LLC Ld Miss" and "Load Dram" overlap with each other for accouting items: "LLC Ld Miss" = "lcl_dram" + "rmt_dram" + "rmt_hit" + "rmt_hitm" "Load Dram" = "lcl_dram" + "rmt_dram" Furthermore, the metrics "LLC Ld Miss" is not directive to show statistics due to it contains summary value and cannot give out breakdown details. For this reason, add a new metrics "RMT Load Hit" which is used to present the remote cache hit; it contains two items: "RMT Load Hit" = remote hit ("rmt_hit") + remote hitm ("rmt_hitm") As result, the metrics "LLC Ld Miss" is perfectly divided into two metrics "RMT Load Hit" and "Load Dram". It's not necessary to keep metrics "LLC Ld Miss", so remove it. Before: # ----------- Cacheline ---------- Tot ------- Load Hitm ------- Total Total Total ---- Stores ---- ----- Core Load Hit ----- - LLC Load Hit -- LLC --- Load Dram ---- # Index Address Node PA cnt Hitm Total LclHitm RmtHitm records Loads Stores L1Hit L1Miss FB L1 L2 LclHit LclHitm Ld Miss Lcl Rmt # ..... .................. .... ...... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ........ ....... ....... ........ ........ # 0 0x55f07d580100 0 1499 85.89% 481 481 0 7243 3879 3364 2599 765 548 2615 66 169 481 0 0 0 1 0x55f07d580080 0 1 13.93% 78 78 0 664 664 0 0 0 187 361 27 11 78 0 0 0 2 0x55f07d5800c0 0 1 0.18% 1 1 0 405 405 0 0 0 131 0 10 263 1 0 0 0 After: # ----------- Cacheline ---------- Tot ------- Load Hitm ------- Total Total Total ---- Stores ---- ----- Core Load Hit ----- - LLC Load Hit -- - RMT Load Hit -- --- Load Dram ---- # Index Address Node PA cnt Hitm Total LclHitm RmtHitm records Loads Stores L1Hit L1Miss FB L1 L2 LclHit LclHitm RmtHit RmtHitm Lcl Rmt # ..... .................. .... ...... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ....... ........ ....... ........ ....... ........ ........ # 0 0x55f07d580100 0 1499 85.89% 481 481 0 7243 3879 3364 2599 765 548 2615 66 169 481 0 0 0 0 1 0x55f07d580080 0 1 13.93% 78 78 0 664 664 0 0 0 187 361 27 11 78 0 0 0 0 2 0x55f07d5800c0 0 1 0.18% 1 1 0 405 405 0 0 0 131 0 10 263 1 0 0 0 0 Signed-off-by: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Signed-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-9-leo.yan@linaro.org -
由 Leo Yan 提交于
"rmt_hit" is accounted into two metrics: one is accounted into the metrics "LLC Ld Miss" (see the function llc_miss() for calculation "llcmiss"); and it's accounted into metrics "LLC Load Hit". Thus, for the literal meaning, it is contradictory that "rmt_hit" is accounted for both "LLC Ld Miss" (LLC miss) and "LLC Load Hit" (LLC hit). Thus this is easily to introduce confusion: "LLC Load Hit" gives impression that all items belong to it are LLC hit; in fact "rmt_hit" is LLC miss and remote cache hit. To give out clear semantics for metric "LLC Load Hit", "rmt_hit" is moved out from it and changes "LLC Load Hit" to contain two items: LLC Load Hit = LLC's hit ("ld_llchit") + LLC's hitm ("lcl_hitm") For output alignment, adjusts the header for "LLC Load Hit". Signed-off-by: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-8-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Leo Yan 提交于
Replace the header string "Lcl" with "LclHit", which is more explicit to express the event type is LLC local hit. Signed-off-by: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-7-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
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: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-6-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
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: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-5-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
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: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-4-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Leo Yan 提交于
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: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-3-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Leo Yan 提交于
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: NLeo Yan <leo.yan@linaro.org> Tested-by: NJoe Mario <jmario@redhat.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/20201014050921.5591-2-leo.yan@linaro.orgSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Ian Rogers 提交于
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: NIan Rogers <irogers@google.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Tested-by: NArnaldo Carvalho de Melo <acme@redhat.com> Link: https://lore.kernel.org/r/20201012161611.366482-1-irogers@google.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 John Garry 提交于
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: NJohn Garry <john.garry@huawei.com> Reviewed-By: Kajol Jain<kjain@linux.ibm.com> Acked-by: NJiri Olsa <jolsa@redhat.com> Link: https://lore.kernel.org/r/1602170368-11892-1-git-send-email-john.garry@huawei.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-8-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-7-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-6-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-5-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-4-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com> -
由 Jin Yao 提交于
In previous patch, we have created evsel_streams array. This patch returns the specified evsel_streams according to the evsel_idx. Signed-off-by: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-3-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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由 Jin Yao 提交于
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: NJin Yao <yao.jin@linux.intel.com> Acked-by: NJiri Olsa <jolsa@kernel.org> Link: https://lore.kernel.org/r/20201009022845.13141-2-yao.jin@linux.intel.comSigned-off-by: NArnaldo Carvalho de Melo <acme@redhat.com>
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