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 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

9 Minutes, 3 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 Mon, 18 Jan 2021 15:01:31 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
bf16bf16bf1614.1%u8s8f3240.0%f3245.9%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 2.0

Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU

OpenBenchmarking.org metrics for this test profile configuration based on 387 public results since 9 December 2020 with the latest data as of 19 January 2021.

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)
97th
4
1434 +/- 7
96th
7
1483 +/- 20
95th
3
1560 +/- 4
94th
3
1610 +/- 296
94th
3
1612 +/- 1
92nd
6
1646 +/- 2
91st
3
2097 +/- 1
90th
4
2187 +/- 126
87th
6
2826 +/- 317
86th
3
2858 +/- 26
84th
6
2988 +/- 233
83rd
4
3042 +/- 46
82nd
10
3242 +/- 465
81st
3
3407 +/- 3
79th
8
3487 +/- 81
78th
3
3608 +/- 8
Mid-Tier
75th
> 3726
72nd
6
3786 +/- 51
71st
10
3815 +/- 138
71st
4
3837 +/- 31
69th
6
3894 +/- 36
67th
6
3960 +/- 523
65th
8
4000 +/- 2
63rd
3
4023 +/- 3
63rd
3
4038 +/- 19
61st
3
4187 +/- 48
59th
3
4478 +/- 29
58th
3
4530 +/- 4
57th
3
4695 +/- 232
57th
3
4763 +/- 3
56th
4
4808 +/- 11
53rd
3
5961 +/- 35
52nd
3
6058 +/- 14
52nd
3
6241 +/- 22
51st
4
6374 +/- 26
Median
50th
6383
49th
4
6702 +/- 25
48th
3
6761 +/- 1
47th
3
6772 +/- 3
46th
6
6867 +/- 32
46th
3
6877 +/- 13
44th
3
7161 +/- 7
43rd
3
7394 +/- 13
42nd
3
7400 +/- 4
41st
3
7484 +/- 9
39th
3
7717 +/- 74
38th
3
7743 +/- 2
37th
3
7909 +/- 11
35th
4
8249 +/- 141
34th
3
8451 +/- 43
32nd
7
8915 +/- 111
31st
3
8935 +/- 26
27th
9
9304 +/- 348
26th
3
9569 +/- 30
26th
6
9585 +/- 399
Low-Tier
25th
> 9786
24th
3
10525 +/- 140
24th
3
10598 +/- 246
22nd
6
11081 +/- 25
21st
3
12586 +/- 31
20th
3
12673 +/- 557
20th
4
12791 +/- 156
19th
3
12863 +/- 7
17th
7
13094 +/- 60
16th
3
13137 +/- 231
15th
3
13181 +/- 226
13th
3
13566 +/- 25
12th
3
14756 +/- 297
10th
3
20832 +/- 20
9th
3
21280 +/- 32
8th
3
22097 +/- 177
7th
7
31372 +/- 674
7th
3
31708 +/- 36
5th
4
44764 +/- 28
3rd
3
66778 +/- 8
3rd
4
68457 +/- 393
2nd
3
73528 +/- 27
1st
3
77508 +/- 465
OpenBenchmarking.orgDistribution Of Public Results - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU387 Results Range From 985 To 77853 ms9852523406155997137867510213117511328914827163651790319441209792251724055255932713128669302073174533283348213635937897394354097342511440494558747125486635020151739532775481556353578915942960967625056404365581671196865770195717337327174809763477788520406080100

Based on OpenBenchmarking.org data, the selected test / test configuration (oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU) has an average run-time of 7 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: Recurrent Neural Network Training - Data Type: f32 - Engine: CPURun-Time612182430Min: 2 / Avg: 6.92 / Max: 28

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.6%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsHarness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUDeviation3691215Min: 0 / Avg: 0.62 / Max: 10

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Most Popular Test Results

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Fedora 33 - 5.9.16-200.fc33.x86_64 - KDE Plasma 5.20.4

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