GPAW

GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE).

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

Project Site

wiki.fysik.dtu.dk

Source Repository

gitlab.com

Test Created

19 September 2020

Last Updated

18 June 2023

Test Maintainer

Michael Larabel 

Test Type

System

Average Install Time

1 Minute, 27 Seconds

Average Run Time

24 Minutes, 37 Seconds

Test Dependencies

OpenMPI + FFTW + CMake + C/C++ Compiler Toolchain + Python Numpy + Python + Python Scipy + BLAS (Basic Linear Algebra Sub-Routine)

Accolades

20k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsGPAW Popularity Statisticspts/gpaw2020.092020.112021.012021.032021.052021.072021.092021.112022.012022.032022.052022.072022.092022.112023.012023.032023.052023.072023.092023.112024.012024.032024.052024.072024.0912002400360048006000
* 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 10 October 2024.

Revision History

pts/gpaw-1.2.0   [View Source]   Sun, 18 Jun 2023 09:51:08 GMT
Update against latest GPAW upstream.

pts/gpaw-1.1.0   [View Source]   Tue, 18 Jan 2022 18:04:24 GMT
Update against GPAW 22.1 upstream.

pts/gpaw-1.0.0   [View Source]   Sat, 19 Sep 2020 09:25:55 GMT
Initial commit of GPAW>

Suites Using This Test

HPC - High Performance Computing

Scientific Computing

MPI Benchmarks

Quantum Mechanics


Performance Metrics

Analyze Test Configuration:

GPAW 23.6

Input: Carbon Nanotube

OpenBenchmarking.org metrics for this test profile configuration based on 561 public results since 18 June 2023 with the latest data as of 7 October 2024.

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)
Mid-Tier
75th
> 41
74th
16
41 +/- 1
Median
50th
87
49th
15
89 +/- 3
39th
4
143 +/- 1
31st
8
178 +/- 18
Low-Tier
25th
> 193
22nd
4
209 +/- 6
17th
5
249 +/- 34
16th
4
265 +/- 18
10th
4
319 +/- 1
3rd
5
524 +/- 21
2nd
4
557 +/- 2
OpenBenchmarking.orgDistribution Of Public Results - Input: Carbon Nanotube533 Results Range From 19 To 7285 Seconds191653114576037498951041118713331479162517711917206322092355250126472793293930853231337735233669381539614107425343994545469148374983512952755421556757135859600561516297644365896735688170277173731980160240320400

Based on OpenBenchmarking.org data, the selected test / test configuration (GPAW 23.6 - Input: Carbon Nanotube) has an average run-time of 8 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 BenchmarkInput: Carbon NanotubeRun-Time918273645Min: 1 / Avg: 8.2 / Max: 46

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 RunsInput: Carbon NanotubeDeviation246810Min: 0 / Avg: 0.32 / Max: 4

Does It Scale Well With Increasing Cores?

Yes, based on the automated analysis of the collected public benchmark data, this test / test settings does 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.

OpenBenchmarking.orgRelative Core Scaling To BaseGPAW CPU Core ScalingInput: Carbon Nanotube681216326496128510152025

Notable Instruction Set Usage

Notable instruction set extensions supported by this test, based on an automatic analysis by the Phoronix Test Suite / OpenBenchmarking.org analytics engine.

Instruction Set
Support
Instructions Detected
SSE2 (SSE2)
Used by default on supported hardware.
 
MOVDQA MOVDQU PUNPCKLQDQ PADDQ CVTSS2SD UCOMISD CVTSD2SS MOVD CVTSI2SD ADDSD MULSD XORPD COMISD DIVSD SUBSD CVTTSD2SI MOVAPD SHUFPD ANDPD UNPCKLPD MULPD UNPCKHPD SUBPD ADDPD PUNPCKHQDQ PSUBQ PSHUFD PSRLDQ ORPD SQRTSD ANDNPD CMPNLESD MINSD MAXSD MOVMSKPD MOVUPD CMPLTSD DIVPD
Last automated analysis: 24 June 2023

This test profile binary relies on the shared libraries libm.so.6, libexpat.so.1, libz.so.1, libc.so.6.

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)
ARMv8 64-bit
aarch64
ARMv8 Neoverse-N1, ARMv8 Neoverse-N1 128-Core, ARMv8 Neoverse-V1, ARMv8 Neoverse-V2, AmpereOne 128-Core, AmpereOne 160-Core, AmpereOne 192-Core, AmpereOne 32-Core, AmpereOne 64-Core, AmpereOne 72-Core, AmpereOne 96-Core

Recent Test Results

OpenBenchmarking.org Results Compare

1 System - 336 Benchmark Results

AmpereOne - Supermicro ARS-211M-NR R13SPD v1.02 - Ampere Computing LLC Device e208

Ubuntu 24.04 - 6.8.0-39-generic-64k - GCC 13.2.0

5 Systems - 531 Benchmark Results

AMD EPYC 7702 64-Core - Supermicro Super Server H12SSL-NT v1.02 - AMD Starship

Debian 12 - 6.8.8-2-pve - NVIDIA

2 Systems - 413 Benchmark Results

AMD Ryzen 7 4700U - LENOVO IdeaPad 5 14ARE05 LNVNB161216 - AMD Renoir

Ubuntu 24.04 - 6.10.0-phx - GNOME Shell 46.0

1 System - 1002 Benchmark Results

1 System - 999 Benchmark Results

1 System - 57 Benchmark Results

AMD Ryzen 9 7950X3D 16-Core - ASUS TUF GAMING X670E-PLUS WIFI - AMD Device 14d8

Ubuntu 22.04 - 6.5.0-44-generic - GNOME Shell 42.9

1 System - 60 Benchmark Results

AMD Ryzen Threadripper PRO 5975WX 32-Cores - Supermicro M12SWA-TF v1.01 - AMD Starship

Ubuntu 22.04 - 6.5.0-41-generic - GNOME Shell 42.9

1 System - 57 Benchmark Results

AMD Ryzen 9 3900XT 12-Core - ASUS PRIME X570-P - AMD Starship

Ubuntu 22.04 - 6.5.0-41-generic - Xfce 4.16

2 Systems - 1012 Benchmark Results

1 System - 1012 Benchmark Results

22 Systems - 263 Benchmark Results

2 x INTEL XEON PLATINUM 8592+ - Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS - Intel Device 1bce

Ubuntu 24.04 - 6.9.0-060900rc3-generic - GCC 13.2.0

6 Systems - 87 Benchmark Results

2 x Intel Xeon Silver 4208 - Dell Precision 7920 Rack 0DY2X0 - Intel Sky Lake-E DMI3 Registers

Debian 11 - 5.10.0-28-amd64 - X Server

1 System - 1 Benchmark Result

2 x AMD EPYC 7742 64-Core - Supermicro H12DSI-NT6 v1.02 - AMD Starship

Ubuntu 20.04 - 5.4.0-91-generic - GNOME Shell 3.36.9

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