PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks.

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

Project Site

github.com

Test Created

10 January 2019

Last Updated

26 September 2019

Test Maintainer

Michael Larabel 

Test Type

Graphics

Average Install Time

15 Seconds

Average Run Time

8 Minutes, 22 Seconds

Test Dependencies

Python + OpenCL

Accolades

30k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsPlaidML Popularity Statisticspts/plaidml2019.012019.032019.052019.072019.092019.112020.012020.032020.052020.072020.092020.112021.012021.032021.052021.072021.092021.112022.012022.032022.052022.072022.092022.112023.012023.032023.052023.072023.092023.112024.012024.032K4K6K8K10K
* Uploading of benchmark result data to OpenBenchmarking.org is always optional (opt-in) via the Phoronix Test Suite for users wishing to share their results publicly.
** 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.
*** Test profile page view reporting began March 2021.
Data updated weekly as of 21 April 2024.
No88.1%Yes11.9%FP16 Option PopularityOpenBenchmarking.org
Training6.1%Inference93.9%Mode Option PopularityOpenBenchmarking.org
Mobilenet20.9%VGG1917.3%Inception V37.4%DenseNet 2018.5%ResNet 5015.9%IMDB LSTM10.0%VGG1620.0%Network Option PopularityOpenBenchmarking.org
OpenCL52.9%CPU47.1%Device Option PopularityOpenBenchmarking.org

Revision History

pts/plaidml-1.0.4   [View Source]   Thu, 26 Sep 2019 14:22:09 GMT
Fixes for latest upstream PlaidML working around configuration files and library issues.

pts/plaidml-1.0.3   [View Source]   Sun, 27 Jan 2019 16:21:22 GMT
Set RequiresDisplay = FALSE

pts/plaidml-1.0.2   [View Source]   Fri, 11 Jan 2019 12:06:07 GMT
Always set --user for pip3 to avoid issues on some distros.

pts/plaidml-1.0.1   [View Source]   Thu, 10 Jan 2019 14:30:27 GMT
Add --train option which works in some configurations.

pts/plaidml-1.0.0   [View Source]   Thu, 10 Jan 2019 10:51:47 GMT
Initial commit of PlaidML deep learning framework benchmark, plaidbench.

Suites Using This Test

Machine Learning

HPC - High Performance Computing

CPU Massive

NVIDIA GPU Compute


Performance Metrics

Analyze Test Configuration:

PlaidML

FP16: No - Mode: Inference - Network: VGG16 - Device: CPU

OpenBenchmarking.org metrics for this test profile configuration based on 17 public results since 10 January 2019 with the latest data as of 31 January 2019.

Additional benchmark metrics will come after OpenBenchmarking.org has collected a sufficient data-set.

OpenBenchmarking.orgDistribution Of Public Results - FP16: No - Mode: Inference - Network: VGG16 - Device: CPU17 Results Range From 3 To 8 Examples Per Second33.4173.8344.2514.6685.0855.5025.9196.3366.7537.177.5878.004246810

Based on OpenBenchmarking.org data, the selected test / test configuration (PlaidML - FP16: No - Mode: Inference - Network: VGG16 - Device: CPU) has an average run-time of 21 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: VGG16 - Device: CPURun-Time714212835Min: 14 / Avg: 20.88 / Max: 31

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.1%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsFP16: No - Mode: Inference - Network: VGG16 - Device: CPUDeviation246810Min: 0 / Avg: 0.07 / Max: 1

Tested CPU Architectures

This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.

CPU Architecture
Kernel Identifier
Verified On
Intel / AMD x86 64-bit
x86_64
(Many Processors)

Recent Test Results

OpenBenchmarking.org Results Compare

1 System - 341 Benchmark Results

AMD Ryzen 9 7950X 16-Core - ASUS ProArt X670E-CREATOR WIFI - AMD Device 14d8

Pop 22.04 - 6.6.10-76060610-generic - GNOME Shell 42.5

2 Systems - 390 Benchmark Results

ARMv8 Cortex-A76 - BCM2835 Raspberry Pi 5 Model B Rev 1.0 - 8GB

Ubuntu 23.10 - 6.5.0-1011-raspi - GNOME Shell 45.2

5 Systems - 66 Benchmark Results

2 x Intel Xeon Gold 6244 - Dell 060K5C - 128GB

Ubuntu 20.04.6 LTS - 3.10.0-1160.95.1.el7.x86_64 - NVIDIA

1 System - 379 Benchmark Results

ARMv8 Cortex-A76 - Mixtile Blade 3 v1.0.1 - 16GB

Ubuntu 22.04 - 5.10.160-rockchip - GNOME Shell 42.9

1 System - 295 Benchmark Results

AMD Ryzen 9 7950X3D 16-Core - ASUS PRIME X670E-PRO WIFI - AMD Device 14d8

Ubuntu 22.04 - 6.2.0-39-generic - GNOME Shell 42.9

1 System - 145 Benchmark Results

Apple M2 Pro - Apple Mac mini - 16GB

macOS 13.5 - 22.6.0 - GCC 14.0.3 + Clang 17.0.6 + LLVM 17.0.6 + Xcode 14.3.1

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