ECP-CANDLE

The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales.

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

Source Repository

github.com

Test Created

12 August 2020

Last Updated

2 August 2021

Test Maintainer

Michael Larabel 

Test Type

System

Average Install Time

3 Minutes, 34 Seconds

Average Run Time

10 Minutes, 19 Seconds

Test Dependencies

Python

Accolades

10k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsECP-CANDLE Popularity Statisticspts/ecp-candle2020.082020.092020.102020.112020.122021.012021.022021.032021.042021.052021.062021.072021.082021.092021.102021.112021.122022.012022.022022.032022.042022.052022.062022.072022.082022.092022.102022.112022.122023.012023.022023.032023.042023.052023.062023.072023.082023.092023.102023.112023.122024.012024.022024.039001800270036004500
* 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 26 March 2024.
P3B226.8%P3B132.7%P1B240.5%Benchmark Option PopularityOpenBenchmarking.org

Revision History

pts/ecp-candle-1.1.0   [View Source]   Mon, 02 Aug 2021 15:13:15 GMT
Update against ECP-CANDLE Benchmarks v0.4 upstream.

pts/ecp-candle-1.0.1   [View Source]   Sun, 23 Aug 2020 14:20:46 GMT
Drop P2B1 option as it seems borked for some systems.

pts/ecp-candle-1.0.0   [View Source]   Wed, 12 Aug 2020 18:15:02 GMT
Initial commit of CANDLE cancer deep learning benchmark.

Suites Using This Test

Machine Learning

HPC - High Performance Computing


Performance Metrics

Analyze Test Configuration:

ECP-CANDLE 0.4

Benchmark: P1B2

OpenBenchmarking.org metrics for this test profile configuration based on 219 public results since 2 August 2021 with the latest data as of 4 August 2022.

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
# Compatible Public Results
Seconds (Average)
86th
12
30 +/- 3
Mid-Tier
75th
> 32
Median
50th
38
48th
3
38 +/- 1
46th
6
39 +/- 2
Low-Tier
25th
> 45
24th
4
45 +/- 1
23rd
3
46 +/- 1
17th
3
47 +/- 1
16th
4
48 +/- 1
OpenBenchmarking.orgDistribution Of Public Results - Benchmark: P1B2219 Results Range From 20 To 358 Seconds2038567492110128146164182200218236254272290308326344362306090120150

Based on OpenBenchmarking.org data, the selected test / test configuration (ECP-CANDLE 0.4 - Benchmark: P1B2) has an average run-time of 2 minutes. By default this test profile is set to run at least 1 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 BenchmarkBenchmark: P1B2Run-Time246810Min: 1 / Avg: 1.01 / Max: 2

Does It Scale Well With Increasing Cores?

No, based on the automated analysis of the collected public benchmark data, this test / test settings does not generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.

IntelAMDOpenBenchmarking.orgRelative Core Scaling To BaseECP-CANDLE CPU Core ScalingBenchmark: P1B246832641280.41880.83761.25641.67522.094

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 - 304 Benchmark Results

AMD A4-5300 APU - ASRock FM2A88M-HD+ R3.0 - AMD 15h

Ubuntu 20.04 - 5.15.0-89-generic - GNOME Shell 3.36.9

1 System - 301 Benchmark Results

AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C+6G - ASRock A320M-HDV R4.0 - AMD 15h

Ubuntu 20.04 - 5.15.0-89-generic - GNOME Shell 3.36.9

1 System - 307 Benchmark Results

Intel Core i3-10100 - ASRock H510M-HVS - Intel Device 43ef

Ubuntu 20.04 - 5.15.0-88-generic - GNOME Shell 3.36.9

1 System - 264 Benchmark Results

Intel Pentium Gold G6405 - ASRock H510M-HDV/M.2 SE - Intel Comet Lake PCH

Ubuntu 20.04 - 5.15.0-88-generic - GNOME Shell 3.36.9

1 System - 264 Benchmark Results

Intel Pentium Gold G6400 - ASRock H510M-HDV/M.2 SE - Intel Comet Lake PCH

Ubuntu 20.04 - 5.15.0-86-generic - GNOME Shell 3.36.9

1 System - 279 Benchmark Results

Intel Core i3-10105 - ASRock H510M-HDV/M.2 SE - Intel Comet Lake PCH

Ubuntu 20.04 - 5.15.0-83-generic - GNOME Shell 3.36.9

1 System - 279 Benchmark Results

Intel Core i3-10105 - ASRock H510M-HDV/M.2 SE - Intel Comet Lake PCH

Ubuntu 20.04 - 5.15.0-83-generic - GNOME Shell 3.36.9

1 System - 279 Benchmark Results

Intel Core i3-10105 - ASRock H510M-HDV/M.2 SE - Intel Comet Lake PCH

Ubuntu 20.04 - 5.15.0-83-generic - GNOME Shell 3.36.9

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