oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark onednn.

Project Site

github.com

Test Created

17 June 2020

Last Updated

20 December 2020

Test Maintainer

Michael Larabel

Test Type

Processor

Average Install Time

8 Minutes, 59 Seconds

Average Run Time

2 Minutes, 2 Seconds

Accolades

5k+ Downloads

Supported Platforms

Public Result UploadsReported Installs*Test Completions*OpenBenchmarking.orgEventsoneDNN Popularity Statisticspts/onednn2020.062020.072020.082020.092020.102020.112020.122021.014K8K12K16K20K
* Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
Data current as of Fri, 22 Jan 2021 18:34:28 GMT.
Deconvolution Batch shapes_3d11.4%Recurrent Neural Network Training15.9%IP Shapes 1D11.5%Convolution Batch Shapes Auto11.5%Matrix Multiply Batch Shapes Transformer11.3%Recurrent Neural Network Inference15.7%IP Shapes 3D11.5%Deconvolution Batch shapes_1d11.4%Harness Option PopularityOpenBenchmarking.org
bf16bf16bf1614.0%u8s8f3240.1%f3245.8%Data Type Option PopularityOpenBenchmarking.org

Revision History

pts/onednn-1.6.1   [View Source]   Sun, 20 Dec 2020 09:58:16 GMT
This test profile builds and works fine on macOS so enable it (MacOSX).

pts/onednn-1.6.0   [View Source]   Wed, 09 Dec 2020 13:47:31 GMT
Update against oneDNN 2.0 upstream.

pts/onednn-1.5.0   [View Source]   Wed, 17 Jun 2020 16:26:39 GMT
Initial commit of oneDNN test profile based on Intel oneDNN 1.5, forked from existing mkl-dnn test profile that is named from MKL-DNN before it was renamed to DNNL and then oneDNN. So create new test profile to match Intel naming convention.

Suites Using This Test

Multi-Core

Machine Learning

Intel oneAPI

CPU Massive

Server CPU Tests

Creator Workloads

HPC - High Performance Computing


Performance Metrics

Analyze Test Configuration:

oneDNN 1.5

Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU

OpenBenchmarking.org metrics for this test profile configuration based on 554 public results since 17 June 2020 with the latest data as of 8 December 2020.

Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.

Component
Percentile Rank
# Matching Public Results
ms (Average)
2 x Intel Xeon Gold 6258R
98th
4
0.32 +/- 0.03
2 x Intel Xeon Gold 6230R
97th
3
0.38 +/- 0.02
AMD Ryzen Threadripper 3970X 32-Core
97th
5
0.39
2 x Intel Xeon Gold 6138
94th
4
0.43 +/- 0.01
AMD Ryzen Threadripper 3990X 64-Core
94th
3
0.44 +/- 0.06
2 x Intel Xeon Platinum 8280
94th
9
0.44
AMD Ryzen Threadripper 3960X 24-Core
92nd
7
0.50 +/- 0.14
2 x AMD EPYC 7542 32-Core
92nd
4
0.51
2 x AMD EPYC 7402 24-Core
91st
3
0.51
AMD EPYC 7662 64-Core
90th
5
0.51
2 x AMD EPYC 7F72 24-Core
89th
4
0.51 +/- 0.01
2 x Intel Xeon Gold 6250
89th
4
0.51 +/- 0.01
2 x AMD EPYC 7452 32-Core
86th
4
0.53
2 x AMD EPYC 7F52 16-Core
85th
8
0.53 +/- 0.02
2 x AMD EPYC 7502 32-Core
84th
3
0.54
AMD EPYC 7542 32-Core
84th
4
0.54
2 x AMD EPYC 7532 32-Core
83rd
4
0.54
AMD EPYC 7F72 24-Core
82nd
6
0.55
2 x AMD EPYC 7352 24-Core
81st
3
0.56
2 x AMD EPYC 7282 16-Core
80th
6
0.57
AMD EPYC 7502P 32-Core
79th
10
0.61 +/- 0.10
2 x AMD EPYC 7742 64-Core
79th
16
0.62
AMD EPYC 7502 32-Core
79th
6
0.62 +/- 0.11
2 x AMD EPYC 7642 48-Core
78th
3
0.62
AMD EPYC 7702 64-Core
78th
5
0.62
Mid-Tier
75th
> 0.64
AMD EPYC 7532 32-Core
75th
5
0.64
2 x AMD EPYC 7272 12-Core
75th
3
0.66
2 x AMD EPYC 7552 48-Core
74th
5
0.67 +/- 0.09
AMD Ryzen 9 5950X 16-Core
74th
7
0.67
AMD EPYC 7552 48-Core
73rd
5
0.68
AMD EPYC 7F52 16-Core
72nd
5
0.69
2 x AMD EPYC 7F32 8-Core
69th
6
0.71
AMD EPYC 7452 32-Core
66th
5
0.74
AMD EPYC 7642 48-Core
61st
5
0.80
AMD Ryzen 9 3900X 12-Core
59th
7
0.82 +/- 0.03
2 x AMD EPYC 7252 8-Core
59th
5
0.83 +/- 0.01
AMD EPYC 7402P 24-Core
59th
11
0.84
AMD EPYC 7352 24-Core
58th
5
0.86
AMD Ryzen 9 5900X 12-Core
56th
12
0.92
2 x Intel Xeon Silver 4214R
56th
4
0.93 +/- 0.01
AMD EPYC 7302P 16-Core
56th
10
0.94 +/- 0.16
2 x AMD EPYC 7262 8-Core
54th
6
1.00 +/- 0.21
Intel Xeon Gold 6226R
53rd
6
1.09 +/- 0.32
AMD EPYC 7282 16-Core
53rd
5
1.18
Median
50th
1.23
2 x Intel Xeon Silver 4210R
50th
3
1.25
AMD EPYC 7272 12-Core
49th
3
1.32
Intel Xeon Gold 5218
49th
5
1.34 +/- 0.26
AMD Ryzen 9 3950X 16-Core
49th
3
1.36
2 x Intel Xeon Silver 4210
49th
3
1.38
2 x Intel Xeon Silver 4215R
46th
4
1.44 +/- 0.06
Intel Core i9-10980XE
45th
19
1.45 +/- 0.09
AMD EPYC 7F32 8-Core
44th
5
1.50
Intel Xeon Silver 4216
41st
7
1.55 +/- 0.02
AMD EPYC 7262 8-Core
41st
3
1.66
AMD EPYC 7252 8-Core
40th
3
1.71
Intel Xeon Silver 4214R
38th
4
1.80 +/- 0.04
AMD Ryzen 9 3900XT 12-Core
36th
5
2.01
Intel Core i7-7900X
36th
3
2.09 +/- 0.01
Intel Xeon Gold 5217
34th
9
2.11
2 x Intel Xeon Gold 5220R
34th
9
2.11
AMD EPYC 7232P 8-Core
34th
11
2.17 +/- 0.45
AMD Ryzen 5 5600X 6-Core
33rd
5
2.32 +/- 0.03
AMD Ryzen 7 5800X 8-Core
32nd
6
2.43 +/- 0.07
Intel Xeon Silver 4215R
30th
4
2.76 +/- 0.16
Intel Core i5-10600K
27th
9
3.62 +/- 0.68
Intel Core i7-5775C
26th
4
3.77 +/- 0.39
Low-Tier
25th
> 3.85
Intel Xeon E-2288G
24th
7
3.97 +/- 0.06
Intel Core i7-7700K
21st
3
4.16 +/- 0.04
AMD Ryzen 3 3100 4-Core
21st
6
4.28 +/- 0.35
Intel Core i7-9700TE
20th
4
4.38 +/- 0.02
Intel Core i9-10900K
18th
17
4.70
AMD Ryzen 7 3700X 8-Core
17th
4
4.78 +/- 0.11
AMD Ryzen 7 3800XT 8-Core
16th
3
4.94 +/- 0.36
Intel Xeon E3-1245 v5
15th
3
5.08 +/- 0.06
AMD Ryzen 7 2700 Eight-Core
15th
3
5.12 +/- 0.09
AMD Ryzen 7 1700 Eight-Core
12th
4
5.42 +/- 0.36
Intel Xeon E3-1280 v5
12th
3
5.46 +/- 0.06
Intel Xeon E3-1270 v5
12th
3
5.69 +/- 0.02
AMD Ryzen 5 4500U
11th
6
5.81 +/- 0.44
Intel Xeon E3-1260L v5
11th
3
5.92 +/- 0.06
Intel Core i7-6700HQ
10th
3
6.13 +/- 0.13
AMD Ryzen 3 1300X
9th
3
6.26 +/- 0.04
Intel Core i7-4790K
6th
4
8.36 +/- 1.53
Intel Core i7-4960X
6th
3
8.73 +/- 0.01
Intel Core i7-4558U
4th
3
9.85 +/- 0.47
Intel Core i5-5300U
4th
3
10.70 +/- 0.41
AMD Ryzen 3 3200U
2nd
3
16.26 +/- 0.73
Intel Core i5-2520M
1st
3
29.71
Ampere eMAG ARMv8 32-Core
1st
3
37.02
OpenBenchmarking.orgDistribution Of Public Results - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU554 Results Range From 0 To 96 ms081624324048566472808896110220330440550

Based on OpenBenchmarking.org data, the selected test / test configuration (oneDNN 1.5 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU) has an average run-time of 2 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.

OpenBenchmarking.orgMinutesTime Required To Complete BenchmarkHarness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPURun-Time246810Min: 1 / Avg: 1.25 / Max: 3

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.8%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsHarness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPUDeviation3691215Min: 0 / Avg: 0.81 / Max: 9

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