1 to 6 of 6 Results
Jul 30, 2024 - Visualisierungsinstitut der Universität Stuttgart
Gralka, Patrick; Müller, Christoph; Heinemann, Moritz; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes"", https://doi.org/10.18419/DARUS-4256, DaRUS, V1, UNF:6:+e/WFL9E6WB+2FvGNOvcGA== [fileUNF]
Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes". Contains the aggregated energy consumption data from the experiments in the paper. The application under test was MegaMol with two OpenGL-based sphere rasterization rendering methods (data static on G... |
Mar 1, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Becher, Michael; Müller, Christoph; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Your visualisations are going places: Performance data for scientific visualisation on gaming consoles", https://doi.org/10.18419/DARUS-4003, DaRUS, V1
The data set contains performance data (mainly frame times) for rendering spherical glyphs and scalar fields on Xbox Series consoles, mobile game consoles and a reference PC with different GPUs. |
Feb 26, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph; Ertl, Thomas, 2024, "Performance Data for the Visualisation of Time-Dependent Particles using DirectStorage", https://doi.org/10.18419/DARUS-4017, DaRUS, V1
Results of a series of performance measurements (frame times) to determine the impact of using the DirectStorage API for rendering time-dependent particle data sets in contrast to using traditional POSIX-style I/O APIs. |
Aug 24, 2022 - SFB-TRR 161 A02 "Quantifying Visual Computing Systems"
Müller, Christoph; Heinemann, Moritz; Weiskopf, Daniel; Ertl, Thomas, 2022, "Energy consumption of scientific visualisation and data visualisation algorithms", https://doi.org/10.18419/DARUS-3044, DaRUS, V1, UNF:6:dEyIoAgP890tWqA/WShryw== [fileUNF]
This data set comprises a series of measurements of GPU power consumption when raycasting spherical glyphs, raycasting scalar fields and when showing web-based data visualisation on Observable HQ. The data sets for sphere rendering were: pos_rad_intensity : 500000 : 0 : 10 10 10... |
May 20, 2022 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Müller, Christoph; Klein, Karsten; Ertl, Thomas; Schreiber, Falk; Task-Force A, 2022, "Guidelines on Replication and Research Data Management", https://doi.org/10.18419/DARUS-2843, DaRUS, V1
This document summarises guidelines for reproducibility in SFB/Transregio 161 by Task Force A (TF-A). It builds upon the data management plan (version 1.0, 2020, https://doi.org/10.18419/darus-632) and focusses on three main points: Provide clear definitions of reproducibility an... |
May 28, 2020 - SFB-TRR 161 A02 "Quantifying Visual Computing Systems"
Bruder, Valentin; Müller, Christoph; Frey, Steffen; Ertl, Thomas, 2020, "Runtime performance measurements of interactive visualisation algorithms", https://doi.org/10.18419/DARUS-810, DaRUS, V1
Runtime performance measurements for GPU-based direct volume rendering and GPU-based raycasting of spherical particles on ten different discrete graphics processing units from AMD and NVIDIA. The data set at hand systematically evaluates typical factors influencing performance of... |