Hoppe, Fabian and Knechtges, Philipp and Rüttgers, Alexander (2023) Parallel Zolotarev-SVD for the analysis of rocket combustion data. SIAM Conference on Computational Science and Engineering (CSE23), 26. Feb. - 03. Mrz. 2023, Amsterdam.
![]() |
PDF
- Only accessible within DLR
1MB |
Abstract
Singular value decomposition (SVD), also known as principal component analysis (PCA), is one of the oldest and most fundamental, but also very powerful mathematical tools in data science. This poster is concerned with the application of modern high-performance SVD algorithms to problems arising in, e.g., the context of rocket combustion at the German Aerospace Center (DLR). We report on our implementation within the PyTorch- and mpi4py-based HPC-data analytics software HEAT (Helmholtz Analytics Toolkit) developed at DLR, JSC, and KIT (Götz et al., 2020 IEEE International Conference on Big Data, pp. 276-287). The core of our SVD implementation is formed by the highly parallelizable Zolotarev-SVD algorithm proposed by Y. Nakatsukasa and R.W. Freund (2016, SIAM Review, Vol. 58, No. 3, pp. 461-493). We present numerical experiments on the respective scaling behavior. Moreover, depending on the concrete problem type, other well-known techniques, such as randomized or incremental algorithms, are shown to allow for further reduction of the computational costs.
Item URL in elib: | https://elib.dlr.de/194222/ | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Document Type: | Conference or Workshop Item (Poster) | ||||||||||||||||
Title: | Parallel Zolotarev-SVD for the analysis of rocket combustion data | ||||||||||||||||
Authors: |
| ||||||||||||||||
Date: | 28 February 2023 | ||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||
Open Access: | No | ||||||||||||||||
Gold Open Access: | No | ||||||||||||||||
In SCOPUS: | No | ||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||
Status: | Published | ||||||||||||||||
Keywords: | SVD, PCA, Singular Value Decomposition, HPC, High Performance Computing, Data Analytics, Heat, Helmholtz Analytics Toolkit | ||||||||||||||||
Event Title: | SIAM Conference on Computational Science and Engineering (CSE23) | ||||||||||||||||
Event Location: | Amsterdam | ||||||||||||||||
Event Type: | international Conference | ||||||||||||||||
Event Dates: | 26. Feb. - 03. Mrz. 2023 | ||||||||||||||||
Organizer: | Society for Industrial and Applied Mathematics (SIAM) | ||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||
HGF - Program: | Space | ||||||||||||||||
HGF - Program Themes: | Space System Technology | ||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||
DLR - Program: | R SY - Space System Technology | ||||||||||||||||
DLR - Research theme (Project): | R - Basic research in the field of machine learning, R - HPDA implementation | ||||||||||||||||
Location: | Köln-Porz | ||||||||||||||||
Institutes and Institutions: | Institute for Software Technology > High-Performance Computing Institute for Software Technology | ||||||||||||||||
Deposited By: | Hoppe, Fabian | ||||||||||||||||
Deposited On: | 27 Mar 2023 13:51 | ||||||||||||||||
Last Modified: | 24 Nov 2023 08:18 |
Repository Staff Only: item control page