Profiling oneDNN Performance¶
oneDNN uses JIT (just-in-time) code generation based on the primitive parameters and instruction set supported by the system. In order to correctly attribute performance event information, profilers must be notified about address ranges containing JIT-ed code. oneDNN supports two profilers: VTune(TM) Amplifier and Linux perf.
Build-Time Controls¶
At build-time, support for this feature is controlled via cmake option DNNL_ENABLE_JIT_PROFILING.
CMake Option |
Supported values (defaults in bold) |
Desc |
|---|---|---|
DNNL_ENABLE_JIT_PROFILING |
ON , OFF |
Enables performance profilers integration |
Run-Time Controls¶
When the feature is enabled at build-time, the DNNL_JIT_PROFILE environment variable can be used to manage integration with performance profilers.
Environment variable |
Value |
Description |
x64 |
AArc |
|---|---|---|---|---|
DNNL_JIT_PROFILE |
1 2 6 14 |
Enables VTune Amplifier integration Enables basic Linux perf integration Enables Linux perf integration with JIT dump output Enables Linux perf integration with JIT dump output and TSC timestamps |
x(default) x x x |
N/A x(default) x N/A |
Other valid values for DNNL_JIT_PROFILE include integer values representing a combination of flags accepted by the dnnl_set_jit_profiling_flags function.
The default setting of the profiling flags is to enable integration with VTune Amplifier; therefore it does not require any additional setup and works out of the box. Code integrating oneDNN may override this behavior.
This feature can also be managed at run-time with the following functions:
Function settings take precedence over environment variables.
Features for VTune Amplifier¶
ITT Tagging for Primitive Execution¶
oneDNN supports ITT tagging at primitive execution in order to provide performance information on the level of a oneDNN primitive. This feature is supported on both CPU and GPU.
ITT tagging in oneDNN during primitive execution provides more information from VTune Amplifier for the items below.
Get the primitives timeline chart from VTune Amplifier, and identify potential performance issues.
Get platform information such as an L1/L2 cache miss or level of FP vectorization on the primitive level.
Map primitive with related computation kernels.
Build-Time Controls¶
At build-time, support for this feature is controlled via cmake option DNNL_ENABLE_JIT_PROFILING.
CMake Option |
Supported values (defaults in bold) |
Desc |
|---|---|---|
DNNL_ENABLE_ITT_TASKS |
ON , OFF |
Enables ITT tagging for primitive execution |
Run-Time Controls¶
When the feature is enabled at build-time, the DNNL_ITT_TASK_LEVEL environment variable can be used to enable different level of ITT tagging.
Environment variable |
Value |
Desc |
|---|---|---|
DNNL_ITT_TASK_LEVEL |
0 1 2 |
no ITT event will be triggered ITT events are only triggered in master thread ITT events are triggered in all OMP/TBB threads |
Example: Profiling with VTune Amplifier¶
For this section, it is assumed that the performance profiling environment is already set up.
profiling for hotspots¶
Collect profiling data:
$ amplxe-cl -collect hotspots -q -no-summary -knob sampling-mode=hw -r dnnl-vtune ./benchdnn --mode=P --conv --batch=inputs/conv/shapes_alexnet amplxe: Warning: To enable hardware event-base sampling, VTune Amplifier has disabled the NMI watchdog timer. The watchdog timer will be re-enabled after collection completes. Output template: perf,%engine%,%impl%,%name%,%prb%,%Gops%,%Gfreq%,%-time%,%-Gflops%,%0time%,%0Gflops% perf,cpu,jit:avx512_common,"alexnet:conv1",--conv g1mb256ic3ih227oc96oh55kh11sh4ph0n"alexnet:conv1",53.9726,0,17.4285,3096.81,22.5851,2389.74 perf,cpu,jit:avx512_common,"alexnet:conv2",--conv g2mb256ic96ih27oc256oh27kh5ph2n"alexnet:conv2",104.696,0,20.2195,5177.98,21.9233,4775.56 perf,cpu,jit:avx512_common,"alexnet:conv3",--conv mb256ic256ih13oc384oh13kh3ph1n"alexnet:conv3",68.904,0,15.5134,4441.57,18.1391,3798.64 perf,cpu,jit:avx512_common,"alexnet:conv4",--conv g2mb256ic384ih13oc384oh13kh3ph1n"alexnet:conv4",51.678,0,11.7397,4401.97,12.4623,4146.76 perf,cpu,jit:avx512_common,"alexnet:conv5",--conv g2mb256ic384ih13oc256oh13kh3ph1n"alexnet:conv5",34.452,0,7.77148,4433.13,8.50435,4051.11 tests:5 passed:5 skipped:0 mistrusted:0 unimplemented:0 failed:0 listed:0 total perf: min(ms):72.6726 avg(ms):83.6142
Note
Here, it is not necessary to set the DNNL_JIT_PROFILE environment variable.
Below are the top 10 function hotspots using the command-line interface:
$ amplxe-cl -report hotspots -q -r dnnl-vtune -format csv -csv-delimiter ';' -group-by process,module,function -column 'CPU Time:Self' | head -n 10 | column -t -s';' Column filter is ON. Process Module Function CPU Time benchdnn [Dynamic code] _jit_avx512_common_conv_fwd_kernel 300.128503 benchdnn [Dynamic code] _jit_avx512_common_conv_fwd_kernel 293.946143 benchdnn [Dynamic code] _jit_avx512_common_conv_fwd_kernel 285.549830 benchdnn [Dynamic code] _jit_avx512_common_conv_fwd_kernel 268.868599 benchdnn [Dynamic code] _jit_avx512_common_conv_fwd_kernel 256.715527 benchdnn libgomp.so.1.0.0 func@0x194f0 186.604226 benchdnn libgomp.so.1.0.0 func@0x19370 82.609694 benchdnn libdnnl.so.1.8 dnnl::impl::cpu::x64::jit_avx512_co.. 35.682241 benchdnn vmlinux [vmlinux] 10.763433
The JIT-ed function _jit_avx512_common_conv_fwd_kernel is shown as belonging to the [Dynamic code] module.
Below are the top 10 primitive type hotspots using the command-line interface:
$ amplxe-cl -report hotspots -q -r dnnl-vtune -format csv -csv-delimiter ';' -group-by task -column 'CPU Time:Self' | head -n 10 | column -t -s';' Column filter is ON. Task Type CPU Time convolution 1451.459338 [Outside any task] 280.489764 reorder 10.434821 10.763433
Profiling for Micro-architecture Information¶
Collect profiling data:
$ amplxe-cl -collect uarch-exploration -knob sampling-interval=1 -data-limit=2000 -q -no-summary -r dnnl-vtune-ue ./benchdnn --mode=P --conv --batch=inputs/conv/shapes_alexnet amplxe: Warning: To enable hardware event-base sampling, VTune Amplifier has disabled the NMI watchdog timer. The watchdog timer will be re-enabled after collection completes. Output template: perf,%engine%,%impl%,%name%,%prb%,%Gops%,%Gfreq%,%-time%,%-Gflops%,%0time%,%0Gflops% perf,cpu,jit:avx512_common,"alexnet:conv1",--conv g1mb256ic3ih227oc96oh55kh11sh4ph0n"alexnet:conv1",53.9726,0,17.2344,3131.68,24.1246,2237.24 perf,cpu,jit:avx512_common,"alexnet:conv2",--conv g2mb256ic96ih27oc256oh27kh5ph2n"alexnet:conv2",104.696,0,20.2988,5157.74,22.6731,4617.63 perf,cpu,jit:avx512_common,"alexnet:conv3",--conv mb256ic256ih13oc384oh13kh3ph1n"alexnet:conv3",68.904,0,15.5369,4434.87,17.1371,4020.75 perf,cpu,jit:avx512_common,"alexnet:conv4",--conv g2mb256ic384ih13oc384oh13kh3ph1n"alexnet:conv4",51.678,0,11.428,4522.06,12.7986,4037.79 perf,cpu,jit:avx512_common,"alexnet:conv5",--conv g2mb256ic384ih13oc256oh13kh3ph1n"alexnet:conv5",34.452,0,7.64233,4508.05,8.99841,3828.68 tests:5 passed:5 skipped:0 mistrusted:0 unimplemented:0 failed:0 listed:0 total perf: min(ms):72.1404 avg(ms):85.7318
Below are L1 Data Cache issues among primitive types using the command-line interface:
$ amplxe-cl -report hotspots -q -r dnnl-vtune-ue -format csv -csv-delimiter ';' -group-by task -column 'L1 Bound' | head -n 10 | column -t -s';' Column filter is ON. Task Type Back-End Bound:Memory Bound:L1 Bound(%) Back-End Bound:Memory Bound:L1 Bound:DTLB Overhead(%) Back-End Bound:Memory Bound:L1 Bound:Loads Blocked by Store Forwarding(%) Back-End Bound:Memory Bound:L1 Bound:Lock Latency(%) Back-End Bound:Memory Bound:L1 Bound:Split Loads(%) Back-End Bound:Memory Bound:L1 Bound:4K Aliasing(%) Back-End Bound:Memory Bound:L1 Bound:FB Full(%) convolution 8.2 0.0 0.0 0.0 0.0 0.2 26.6 [Outside any task] 4.4 0.0 0.0 0.0 0.0 0.0 2.6 reorder 16.0 0.0 0.0 0.0 0.0 0.1
Below are issues with Instruction Cache misses among primitive types using the command-line interface:
$ amplxe-cl -report hotspots -q -r dnnl-vtune-ue -format csv -csv-delimiter ';' -group-by task -column 'ICache Misses' | head -n 10 | column -t -s';' Column filter is ON. Task Type Front-End Bound:Front-End Latency:ICache Misses(%) convolution 0.2 [Outside any task] 0.1 reorder 0.3
Here are some column names within micro-architecture profiling results. You could replace ‘ICache Misses’ with another column name.
*”ICache Misses”,”ITLB Overhead”,”Bad Speculation”,”L1 Bound”,”L2 Bound”,”L3 Bound”,”DRAM Bound”,”Average CPU Frequency”,”Task Time”,”Task Count”, etc*
For getting all column names within your profiling results, you could use the command below to get more detailed information.
$ amplxe-cl -report hotspots -q -r dnnl-vtune-ue -format csv -csv-delimiter ';' -group-by task -column=? Available values for '-column' option are: CPU Time:Self Clockticks:Self Instructions Retired:Self CPI Rate:Self Retiring:Self Retiring:General Retirement:Self Retiring:General Retirement:FP Arithmetic:Self Retiring:General Retirement:FP Arithmetic:FP x87:Self Retiring:General Retirement:FP Arithmetic:FP Scalar:Self Retiring:General Retirement:FP Arithmetic:FP Vector:Self Retiring:General Retirement:Other:Self Retiring:Microcode Sequencer:Self Retiring:Microcode Sequencer:Assists:Self Front-End Bound:Self Front-End Bound:Front-End Latency:Self Front-End Bound:Front-End Latency:ICache Misses:Self
See more examples in the VTune Amplifier User Guide
Example: Profiling with Linux perf¶
The following command instructs oneDNN to enable both jitdump and perfmap profiling modes and write jitdump files into the .debug directory in the current directory by setting environment variable JITDUMPDIR to point to the current directory.
$ JITDUMPDIR=. DNNL_JIT_PROFILE=6 perf record -k1 ./tests/benchdnn/benchdnn --conv --mode=P mb1ic32ih14oc32oh14kh3ph1n"resnet_50:res4a_branch2b*6" Output template: perf,%engine%,%name%,%desc%,%Gops%,%Gfreq%,%-time%,%-Gflops%,%0time%,%0Gflops% perf,cpu,resnet_50:res4a_branch2b*6,--conv mb1ic32ih14oc32oh14kh3ph1nresnet_50:res4a_branch2b*6,0.0032768,0,0.0131836,248.551,0.0262988,124.599 tests:1 passed:0 skipped:0 mistrusted:0 unimplemented:0 failed:0 listed:0 total perf: min(ms):0.0131836 avg(ms):0.0262988 [ perf record: Woken up 1 times to write data ] [ perf record: Captured and wrote 0.884 MB perf.data (23102 samples) ]
The following command injects the information from the jitdump files into the performance data:
$ perf inject -j -i perf.data -o perf.data.j
The following command displays the top hotspots:
$ perf report -i perf.data.j --stdio | head -n20 # To display the perf.data header info, please use --header/--header-only options. # # # Total Lost Samples: 0 # # Samples: 23K of event 'cpu-clock:uhH' # Event count (approx.): 5775500000 # # Overhead Command Shared Object Symbol # 39.33% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d8ba 29.41% benchdnn jitted-31475-0.so [.] jit_avx2_conv_fwd_kernel_f32 20.49% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d712 3.47% benchdnn libdnnl.so.1.1 [.] dnnl::impl::cpu::jit_avx2_convolution_fwd_t::execute_forward(dnnl::impl::exec_ctx_t const&) const::{lambda(int, int)#1}::operator() 1.52% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d8be 0.93% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d716 0.75% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d8c5 0.55% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d8c3 0.46% benchdnn libgomp.so.1.0.0 [.] 0x000000000001d71d
Note
Not every kernel/distribution supports displaying detailed profiling information. Symbol resolution (usually) works as long as the perfmap mode is enabled, but annotating a JIT-ed functions disassembly, which requires jitdump, seems to often fail on kernels before 5.x.
See more on Brendan Gregg’s excellent perf examples page