Institute for Computational Physics

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

181 to 190 of 1,092 Results

custom_resnet18.py Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores" Python Source Code - 9.6 KB - MD5: 394999544b73013cf9c2e7a2d98bdf41
generate_reference_data.py Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores" Python Source Code - 5.3 KB - MD5: 5c5990970a221cf5bfda43564c1d0270
prune_plotting.py Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores" Python Source Code - 2.8 KB - MD5: fe5da6074e6d32dc1a4a262c2279d697
quantization_table.py Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores" Python Source Code - 3.1 KB - MD5: def488fcb660e6e0219943cbc2d9cc8b
results-plots.py Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores" Python Source Code - 8.3 KB - MD5: 4e4b9248fd6e965803f90332f7da1b11
Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions Jun 3, 2026 - Holm group Grad, Jean-Noël; Tischler, Ingo; Reinauer, Alexander; Kobayashi, Hideki; Kuron, Michael; Hennig, Frederik; Holzer, Markus; Santos Neves, Pedro Miguel; Kamath, Satish Santhosh; Holm, Christian; Weeber, Rudolf, 2026, "Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions", https://doi.org/10.18419/DARUS-5827, DaRUS, V2, UNF:6:hKxT8PVDSE8OaAEZRK6tuQ== [fileUNF] Build scripts, benchmark scripts, raw data, and analysis scripts accompanying the paper "Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions" (doi:10.1016/j.procs.2026.08.022).
ek_gpu_coupling.csv Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions Tabular Data - 5.4 KB - 27 Variables, 37 Observations - UNF:6:RDJvQfTdWKLuQKnDYhiiyA== Benchmark results for EK simulations (job_coupling_ek.py).
espresso_500_build.sh Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions Unknown - 3.0 KB - MD5: c9a03a9b02557c336e9715bd598abe76 Build commands for ESPResSo 5.0.0 and waLBerla using the Nvidia HPC SDK 25.7 toolchain and the EESSI foss/2025a toolchain. Network connections to the MareNostrum supercomputer must be done through SSH, therefore the building of software requires extra steps.
espresso_501_build.sh Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions Unknown - 3.0 KB - MD5: 62b8d1a87ebd5013036b4fb37746812d Build commands for ESPResSo 5.0.1 and waLBerla using the Nvidia HPC SDK 25.7 toolchain and the EESSI foss/2025a toolchain. Network connections to the MareNostrum supercomputer must be done through SSH, therefore the building of software requires extra steps.
espresso_fetch.sh Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions Unknown - 993 B - MD5: 4fcb0b2dbec408de955aae210f7e1d63 Download commands for the ESPResSo software and third-party libraries included via the CMake FetchContent mechanism. Network connections to the MareNostrum supercomputer must be done through SSH, therefore software must be downloaded locally and uploaded to the supercomputer via SSH.

custom_resnet18.py

Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores"

Python Source Code - 9.6 KB -

generate_reference_data.py

Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores"

Python Source Code - 5.3 KB -

prune_plotting.py

Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores"

Python Source Code - 2.8 KB -

quantization_table.py

Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores"

Python Source Code - 3.1 KB -

results-plots.py

Jun 18, 2026 - Replication Script for "Deep Learning-Driven Peptide Classification in Biological Nanopores"

Python Source Code - 8.3 KB -

Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions

Jun 3, 2026 - Holm group

Grad, Jean-Noël; Tischler, Ingo; Reinauer, Alexander; Kobayashi, Hideki; Kuron, Michael; Hennig, Frederik; Holzer, Markus; Santos Neves, Pedro Miguel; Kamath, Satish Santhosh; Holm, Christian; Weeber, Rudolf, 2026, "Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions", https://doi.org/10.18419/DARUS-5827, DaRUS, V2, UNF:6:hKxT8PVDSE8OaAEZRK6tuQ== [fileUNF]

Build scripts, benchmark scripts, raw data, and analysis scripts accompanying the paper "Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions" (doi:10.1016/j.procs.2026.08.022).

ek_gpu_coupling.csv

Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions

Tabular Data - 5.4 KB - 27 Variables, 37 Observations -

Benchmark results for EK simulations (job_coupling_ek.py).

espresso_500_build.sh

Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions

Unknown - 3.0 KB -

Build commands for ESPResSo 5.0.0 and waLBerla using the Nvidia HPC SDK 25.7 toolchain and the EESSI foss/2025a toolchain. Network connections to the MareNostrum supercomputer must be done through SSH, therefore the building of software requires extra steps.

espresso_501_build.sh

Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions

Unknown - 3.0 KB -

Build commands for ESPResSo 5.0.1 and waLBerla using the Nvidia HPC SDK 25.7 toolchain and the EESSI foss/2025a toolchain. Network connections to the MareNostrum supercomputer must be done through SSH, therefore the building of software requires extra steps.

espresso_fetch.sh

Jun 3, 2026 - Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions

Unknown - 993 B -

Download commands for the ESPResSo software and third-party libraries included via the CMake FetchContent mechanism. Network connections to the MareNostrum supercomputer must be done through SSH, therefore software must be downloaded locally and uploaded to the supercomputer via SSH.

Add Data

Share Dataverse

Link Dataverse

Reset Modifications