README.md

# Unified European Applications Benchmark Suite

<img alt="PRACE" src="PRACE_logo.png" width="150px">

The Unified European Application Benchmark Suite (UEABS) is a set of currently 13 application codes taken from the pre-existing PRACE and DEISA application benchmark suites, and extended with the PRACE Accelerator Benchmark Suite. The objective is providing a single benchmark suite of scalable, currently relevant and publicly available application codes and datasets, of a size which can realistically be run on large systems, and maintained into the future.

The UEABS activity was started during the PRACE-PP project and was publicly released by the PRACE-2IP project.
The PRACE "Accelerator Benchmark Suite" was a PRACE-4IP activity.
The UEABS has been and will be actively updated and maintained by the subsequent PRACE-IP projects.

Each application code has either one, or two input datasets. If there are two datasets, Test Case A is designed to run on Tier-1 sized systems (up to around 1,000 x86 cores, or equivalent) and Test Case B is designed to run on Tier-0 sized systems (up to around 10,000 x86 cores, or equivalent). If there is only one dataset (Test Case A), it is suitable for both sizes of system.

Contact: Walter Lioen <mailto:walter.lioen@surf.nl>

Current Release
---------------

The current release is Version 2.2 (December 20, 2022).
See also the [release notes and history](RELEASES.md).

Running the suite
-----------------

Instructions to run each test cases of each codes can be found in the subdirectories of this repository.

For more details of the codes and datasets, and sample results, please see the PRACE-6IP benchmarking deliverable [D7.5 "Evaluation of Benchmark Performance"](https://prace-ri.eu/wp-content/uploads/PRACE6IP-D7.4.pdf) (November 30, 2021).

The application codes that constitute the UEABS are:
---------------------------------------------------
<table>
  <thead>
    <tr>
      <th rowspan="2">Application</th>
      <th rowspan="2">Lines of<br/>Code</th>
      <th colspan="3">Parallelism</th>
      <th colspan="4">Language</th>
      <th rowspan="2">Code Description/Notes</th>
    </tr>
    <tr>
      <th>MPI</th>
      <th>OpenMP/<br/>Pthreads</th>
      <th>GPU</th>
      <th>Fortran</th>
      <th>Python</th>
      <th>C</th>
      <th>C++</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Alya
        <ul>
          <li><a href="https://www.bsc.es/computer-applications/alya-system">website</a></li>
          <li><a href="https://gitlab.com/bsc-alya/open-alya">source</a></li>
          <li><a href="alya/README.md">instructions</a></li>
          <li><a href="https://gitlab.com/bsc-alya/benchmarks/sphere-16M">Test Case A</a></li>
          <li><a href="https://gitlab.com/bsc-alya/benchmarks/sphere-132M">Test Case B</a></li>
        </ul>
      </td>
      <td>600,000</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>The Alya System is a Computational Mechanics code capable of solving different physics, each one with its own modelization characteristics, in a coupled way. Among the problems it solves are: convection-diffusion reactions, incompressible flows, compressible flows, turbulence, bi-phasic flows and free surface, excitable media, acoustics, thermal flow, quantum mechanics (DFT) and solid mechanics (large strain).</td>
    </tr>
    <tr>
      <td>Code_Saturne
        <ul>
         <li><a href="https://www.code-saturne.org/cms/web">Code_Saturne website</a></li>
         <li><a href="https://www.code-saturne.org/cms/sites/default/files/releases/code_saturne-7.0.0.tar.gz">Source code</a></li>
         <li><a href="https://repository.prace-ri.eu/git/UEABS/ueabs/-/blob/r2.2-dev/code_saturne/README.md">Build instuctions</a></li>
         <li><a href="https://repository.prace-ri.eu/ueabs/Code_Saturne/2.2/CS_7.0.0_PRACE_UEABS_CAVITY_13M.tar.gz">Testcase A</a></li>
         <li><a href="https://repository.prace-ri.eu/ueabs/Code_Saturne/2.2/CS_7.0.0_PRACE_UEABS_CAVITY_XXXM.tar.gz">Testcase B</a></li>
        </ul>
      </td>
      <td>~350,000</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>The code solves the Navier-Stokes equations for incompressible/compressible flows using a predictor-corrector technique. The Poisson pressure equation is solved by a Conjugate Gradient preconditioned by a multi-grid algorithm, and the transport equations by Conjugate Gradient-like methods. Advanced gradient reconstruction is also available to account for distorted meshes.</td>
    </tr>
    <tr>
      <td>CP2K
        <ul>
          <li><a href="https://www.cp2k.org/">CP2K website</a></li>
          <li><a href="https://github.com/cp2k/cp2k/releases">Source code</a></li>
          <li><a href="./cp2k/README.md">Build instructions</a></li>
          <li><a href="./cp2k/benchmarks/TestCaseA_H2O-512">Testcase A</a></li>
          <li><a href="./cp2k/benchmarks/TestCaseB_LiH-HFX">Testcase B</a></li>
          <li><a href="./cp2k/benchmarks/TestCaseC_H2O-DFT-LS">Testcase C</a></li>
        </ul>
      </td>
      <td>~1,150,000</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>CP2K is a freely available quantum chemistry and solid-state physics software package for performing atomistic simulations. It can be run with MPI, OpenMP and CUDA. All of CP2K is MPI parallelised, with some routines making use of OpenMP, which can be used to reduce the memory footprint. In addition some linear algebra operations may be offloaded to GPUs using CUDA.</td>
    </tr>
    <tr>
      <td>GADGET
       <ul>
      		<li><a href="https://wwwmpa.mpa-garching.mpg.de/gadget4">GADET Website</a></li>
          <li><a href="https://gitlab.mpcdf.mpg.de/vrs/gadget4">GADET GitLab</a></li>
        	<li><a href="gadget/README.md#mechanics-of-building-benchmark">Build instructions</a>
          <li><a href="gadget/README.md#mechanics-of-running-benchmark">Run instructions</a>
          <li><a href="./gadget/gadget4-case-A.tar.gz">Test Case A</a></li>
          <li><a href="./gadget/gadget4-case-B.tar.gz">Test Case B</a></li>
       </ul>
       </td>
      <td>100,000+</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>X</td>
      <td>X</td>
      <td>GADGET-4 (GAlaxies with Dark matter and Gas intEracT), an evolved and improved version of GADGET-3, is a freely available code for cosmological N-body/SPH simulations on massively parallel computers with distributed memory. GADGET-4 supports collisionless simulations and smoothed particle hydrodynamics on massively parallel computers. All communication between concurrent execution processes is done either explicitly by means of the message passing interface (MPI), or implicitly through shared-memory accesses on processes on multi-core nodes. The code is mostly written in ISO C++ (assuming the C++11 standard), and should run on all parallel platforms that support at least MPI-3.</td>
    </tr>
    <tr>
      <td>GPAW
        <ul>
          <li><a href="https://wiki.fysik.dtu.dk/gpaw/">website</a></li>
          <li><a href="https://gitlab.com/gpaw/gpaw">GPAW GitLab</a></li>
          <li><a href="https://gitlab.com/mlouhivu/gpaw/tree/cuda">GPAW GPU development (cuda branch)</a></li>
          <li><a href="gpaw/README.md#mechanics-of-building-the-benchmark">Build instructions</a>
          <li><a href="gpaw/README.md#mechanics-of-running-the-benchmark">Run instructions</a>
          <li><a href="gpaw/benchmark/A_carbon-nanotube/input.py">Test Case A</a>
          <li><a href="gpaw/benchmark/B_copper-filament/input.py">Test Case B</a>
          <li><a href="gpaw/benchmark/C_silicon-cluster/input.py">Test Case C</a>
        </ul>
      </td>
      <td>132,000</td>
      <td>X</td>
      <td></td>
      <td>(X)</td>
      <td></td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td>
        GPAW is a density-functional theory (DFT)
        program for ab initio electronic structure calculations using the projector
        augmented wave method. It uses a uniform real-space grid representation of the
        electronic wavefunctions that allows for excellent computational scalability
        and systematic converge properties.
        The GPAW benchmark tests MPI parallelization and the quality of the provided mathematical
        libraries, including BLAS, LAPACK, ScaLAPACK, and FFTW-compatible library. There is
        also an experimental CUDA-based implementation for GPU systems, but it is not covered
        by this UEABS release.
      </td>
    </tr>
    <tr>
      <td>GROMACS
      <ul>
      <li><a href="http://www.gromacs.org">website</a></li>
      <li><a href="http://www.gromacs.org/Downloads">Source code</a></li>
      <li><a href="https://repository.prace-ri.eu/git/UEABS/ueabs/-/tree/r2.2-dev/gromacs">Build and Run Instructions</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/GROMACS/2.2/GROMACS_TestCaseA.tar.xz">Test Case A</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/GROMACS/2.2/GROMACS_TestCaseB.tar.xz">Test Case B</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/GROMACS/2.2/GROMACS_TestCaseC.tar.xz">Test Case C</a></li>
      </ul>
      </td>
      <td>862,079</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td>X</td>
      <td>X</td>
      <td>GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.</td>
    </tr>
    <tr>
      <td>NAMD
        <ul>
      <li><a href="http://www.ks.uiuc.edu/Research/namd/">website</a></li>
      <li><a href="http://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=NAMD">Source code</a></li>
      <li><a href="https://repository.prace-ri.eu/git/UEABS/ueabs/-/tree/r2.2-dev/namd">Build and Run Instructions</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/NAMD/2.2/NAMD_TestCaseA.tar.gz">Test Case A</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/NAMD/2.2/NAMD_TestCaseB.tar.gz">Test Case B</a></li>
      <li><a href="https://repository.prace-ri.eu/ueabs/NAMD/2.2/NAMD_TestCaseC.tar.gz">Test Case C</a></li>
      </ul>
      </td>
      <td>887,547</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>X</td>
      <td>NAMD is a widely used molecular dynamics application designed to simulate bio-molecular systems on a wide variety of compute platforms.
      </td>
    </tr>
    <tr>
      <td>NEMO
      <ul>
          <li><a href="https://www.nemo-ocean.eu/">website</a></li>
          <li><a href="https://forge.ipsl.jussieu.fr/nemo/chrome/site/doc/NEMO/guide/html/install.html#download-and-install-the-nemo-code">source</a></li>
          <li><a href="nemo/README.md">instructions</a></li>
          <li><a href="nemo/README.md#verification-of-results">Test Case A</a></li>
          <li><a href="nemo/README.md#verification-of-results">Test Case B</a></li>
        </ul>
      </td>
      <td>154,240</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td>X</td>
      <td></td>
      <td></td>
      <td>X</td>
      <td>NEMO (Nucleus for European Modelling of the Ocean) is a mathematical modelling framework for research activities and prediction services in ocean and climate sciences developed by a European consortium. It is intended to be a tool for studying the ocean and its interaction with the other components of the earth climate system over a large number of space and time scales. It comprises of the core engines namely OPA (ocean dynamics and thermodynamics), SI3 (sea ice dynamics and thermodynamics), TOP (oceanic tracers) and PISCES (biogeochemical process).</td>
    </tr>
    <tr>
      <td>PFARM
	<ul>
	  <li><a href="https://www.ccpq.ac.uk/node/4">website</a></li>
          <li><a href="https://repository.prace-ri.eu/git/UEABS/ueabs/-/tree/r2.2-dev/pfarm">source</a></li>
          <li><a href="pfarm/PFARM_Build_Run_README.txt">instructions</a></li>
          <li><a href="https://repository.prace-ri.eu/ueabs/PFARM/2.2/test_case_1_atom.tar.gz">Test Case 1</a></li>
          <li><a href="https://repository.prace-ri.eu/ueabs/PFARM/2.2/test_case_2_mol.tar.gz">Test Case 2</a></li>
	</ul>
      </td>
      <td>21,434</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>PFARM uses an R-matrix ab-initio approach to calculate electron-atom and electron-molecule collisions data for a wide range of applications including atrophysics and nuclear fusion. It is written in modern Fortran/MPI/OpenMP and exploits highly-optimised dense linear algebra numerical library routines.</td>
    </tr>
    <tr>
      <td>QCD
        <ul>
        <li><a href='qcd/README.md'>see for more details</a></li>
        </ul>
      </td>
      <td>100,000+</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td>X</td>
      <td>X</td>
      <td>The QCD benchmark is, unlike the other benchmarks in the PRACE application benchmark suite, not a full application but a set of 3 parts which are representative of some of the most compute-intensive parts of QCD calculations. The major application of the different parts consists of a Conjugate Gradient solver involving Wilson Dirac stencil in 4 dimension. Keywords of the QCD bencharmks kernels are: Domain Decomposition, Memory bandwidth, strong scaling, MPI latency.</td>
    </tr>
    <tr>
      <td>Quantum&nbsp;ESPRESSO
      <ul>
      <li><a href='https://www.quantum-espresso.org/'>Website</a></li>
      <li><a href='https://www.quantum-espresso.org/download-page/'>Source</a></li>
      <li><a href='quantum_espresso/README.md#installation-and-requirements'>Build and Run instructions</a></li>
      <li><a href='https://repository.prace-ri.eu/ueabs/Quantum_Espresso/QuantumEspresso_TestCaseA.tar.gz'>Test Case A</a></li>
      <li><a href='https://repository.prace-ri.eu/ueabs/Quantum_Espresso/QuantumEspresso_TestCaseB.tar.gz'>Test Case B</a></li>
      </ul>
      </td>
      <td>92,996</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td></td>
      <td></td>
      <td>Quantum Espresso is an integrated suite of Open-Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. It is written in MPI and OpenMP with a CUDA Fortran version
      available for Nvidia GPUs. In the benchmark suite we consider only the most used program, PWscf. </td>
    </tr>
    <tr>
      <td>SPECFEM3D
        <ul>
          <li><a href="https://geodynamics.org/cig/software/specfem3d_globe/">Website</a></li>
          <li><a href="https://github.com/geodynamics/specfem3d_globe.git">Source</a></li>
          <li><a href="specfem3D/README.md">Run and build instructions</a></li>
          <li><a href="specfem3D/test_case/SPECFEM3D_TestCase_A">Test Case A</a></li>
          <li><a href="specfem3D/test_case/SPECFEM3D_TestCase_B">Test Case B</a></li>
          <li><a href="https://github.com/geodynamics/specfem3d_globe/tree/master/EXAMPLES/small_benchmark_run_to_test_more_complex_Earth">Test Case C</a></li>
        </ul>
      </td>
      <td> ~120,000 (100k Fortran & 20k C)</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td>X</td>
      <td></td>
      <td>The software package SPECFEM3D simulates three-dimensional global and regional seismic wave propagation based upon the spectral-element method (SEM).</td>
    </tr>
    <tr>
      <td>TensorFlow
        <ul>
          <li><a href="https://www.tensorflow.org/">website</a></li>
          <li><a href="https://github.com/maxwelltsai/DeepGalaxy">source</a></li>
          <li><a href="tensorflow/README.md">instructions</a></li>
          <li><a href="tensorflow/Testcase_A">Test Case A</a></li>
          <li><a href="tensorflow/Testcase_B">Test Case B</a></li>
          <li><a href="tensorflow/Testcase_C">Test Case C</a></li>
        </ul>
      </td>
      <td>~3,000,000</td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td></td>
      <td>X</td>
      <td>X</td>
      <td>X</td>
      <td>TensorFlow is a popular open-source library for symbolic math and linear algebra, with particular optimisation for neural-networks-based machine learning workflow. Maintained by Google, it is widely used for research and production in both the academia and the industry.</td>
    </tr>
  </tbody>
</table>

License
-------
All UEABS application codes are covered by their own respective licenses. Code modificiations required by the UEABS might inherit the originating application's license.

<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />Unless stated otherwise, all work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.

Acknowledgements
----------------
<img alt="Co-Funded by the European Union" src="EN_Co-Funded_by_the_EU_POS.png" width="300px">

This project has received funding from the European Union’s
Seventh Framework Programme (FP7/2007-2013) under grant agreements
n° 211528 (PRACE-PP), n° 261557 (PRACE-1IP), n° 283493 (PRACE-2IP), n° 312763 (PRACE-3IP);
and from the
Horizon 2020 research and innovation programme under grant agreements
No 653838 (PRACE-4IP), No 730913 (PRACE-5IP), No 823767 (PRACE-6IP).