PlaidML

This test profile uses PlaidML deep learning framework for offering up various inference benchmarks.

Learn more about this test at the upstream project site: https://github.com/plaidml/plaidml.

This utility test profile is maintained by Michael Larabel. This OpenBenchmarking.org test profile was created on 10 January 2019 and last updated on 26 September 2019. To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark plaidml.

This test has an average install time of 16 seconds and an average run-time of 8 minutes, 22 seconds.

20k+ Downloads

Installation StatsTest Completion StatsPublic Result UploadsOpenBenchmarking.orgEventsPlaidML Popularitypts/plaidml2019.012019.022019.032019.042019.052019.062019.072019.082019.092019.102019.112019.122020.012020.022020.032020.042020.052020.062020.072020.082020.092020.102020.112004006008001000

* Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting.

No87.1%Yes12.9%FP16 Option PopularityOpenBenchmarking.org
Training6.1%Inference93.9%Mode Option PopularityOpenBenchmarking.org
Mobilenet26.5%VGG1911.7%Inception V310.3%DenseNet 2019.4%ResNet 5014.2%IMDB LSTM13.8%VGG1614.1%Network Option PopularityOpenBenchmarking.org
OpenCL52.1%CPU47.9%Device Option PopularityOpenBenchmarking.org

Revision History

pts/plaidml-1.0.4   [View Source]   26 Sep 2019 14:22 EDT
Fixes for latest upstream PlaidML working around configuration files and library issues.

pts/plaidml-1.0.3   [View Source]   27 Jan 2019 16:21 EST
Set RequiresDisplay = FALSE

pts/plaidml-1.0.2   [View Source]   11 Jan 2019 12:06 EST
Always set --user for pip3 to avoid issues on some distros.

pts/plaidml-1.0.1   [View Source]   10 Jan 2019 14:30 EST
Add --train option which works in some configurations.

pts/plaidml-1.0.0   [View Source]   10 Jan 2019 10:51 EST
Initial commit of PlaidML deep learning framework benchmark, plaidbench.

Suites Using This Test

Machine Learning

CPU Massive

NVIDIA GPU Compute

Performance Metrics

Analyze Test Configuration:

PlaidML

FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU

OpenBenchmarking.org metrics for this test profile configuration based on 403 public samples since 10 January 2019 with the latest data as of 1 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
FPS (Average)
Mid-Tier
75th
< 6.28
Median
50th
5.08
Low-Tier
25th
< 4.50
OpenBenchmarking.orgDistribution Of Public Results - FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU403 Results Range From 2 To 13 FPS22.9173.8344.7515.6686.5857.5028.4199.33610.25311.1712.08713.00420406080100

Based on OpenBenchmarking.org data, the selected test / test configuration (PlaidML - FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU) has an average run-time of 24 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 BenchmarkFP16: No - Mode: Inference - Network: ResNet 50 - Device: CPURun-Time816243240Min: 5 / Avg: 23.82 / Max: 40

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.3%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsFP16: No - Mode: Inference - Network: ResNet 50 - Device: CPUDeviation246810Min: 0 / Avg: 0.32 / Max: 2

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