Univ.-Prof. Dipl.-Ing. Dr. Wilfried Gansterer, M.Sc.
1090 Wien
Raum : 6.33
Lehrveranstaltungen
Wintersemester 2026
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051080 LP Softwarepraktikum mit Bachelorarbeit
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051132 VO Einführung in Numerical Computing
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052101 VU Numerical Algorithms
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052112 VU Numerical High Performance Algorithms
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053021 LP Praktikum Informatik 1
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053031 LP Praktikum Informatik 2
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053049 SE Masterseminar
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500500 SE Doktoranden Forschungsseminar - Algorithms and Computing
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500501 SE Doktoranden Forschungsseminar - Data and Knowledge
Sommersemester 2026
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051080 LP Softwarepraktikum mit Bachelorarbeit
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052101 VU Numerical Algorithms
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053021 LP Praktikum Informatik 1
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053031 LP Praktikum Informatik 2
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053049 SE Masterseminar
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500500 SE Doktoranden Forschungsseminar - Algorithms and Computing
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500501 SE Doktoranden Forschungsseminar - Data and Knowledge
Wintersemester 2025
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051080 LP Softwarepraktikum mit Bachelorarbeit
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051132 VO Einführung in Numerical Computing
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052101 VU Numerical Algorithms
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053021 LP Praktikum Informatik 1
-
053031 LP Praktikum Informatik 2
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500500 SE Doktoranden Forschungsseminar - Algorithms and Computing
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500501 SE Doktoranden Forschungsseminar - Data and Knowledge
Publikationen
On the Two Sides of Redundancy in Graph Neural Networks. / Bause, Franka (Korresp. Autor*in); Moustafa, Samir; Langguth, Johannes et al.
Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2024. Hrsg. / Albert Bifet; Jesse Davis; Tomas Krilavičius; Meelis Kull; Eirini Ntoutsi; Indrė Žliobaitė. Band 14946 Springer Cham, 2024. S. 371-388 (Lecture Notes in Computer Science, Band 14946).
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
A New Exact State Reconstruction Strategy for Conjugate Gradient Methods with Arbitrary Preconditioners. / Mayer, Viktoria; Gansterer, Wilfried (Korresp. Autor*in).
2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2024. S. 1150-1152 (IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)).
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Adaptive Precision Training (AdaPT): A dynamic quantized training approach for DNNs. / Kummer, Lorenz; Sidak, Kevin; Reichmann, Tabea et al.
2023. 559 Beitrag in SIAM International Conference on Data Mining (SDM23), Minneapolis, USA / Vereinigte Staaten.
Veröffentlichungen: Beitrag zu Konferenz › Paper › Peer Reviewed
Removing Redundancy in Graph Neural Networks. / Bause, Franka; Moustafa, Samir; Gansterer, Wilfried et al.
2023. Beitrag in 20th International Workshop on Mining and Learning with Graphs, Torino, Italien.
Veröffentlichungen: Beitrag zu Konferenz › Paper › Peer Reviewed
Accuracy vs. Cost in Parallel Fixed-Precision Low-Rank Approximations of Sparse Matrices. / Ernstbrunner, Robert; Mayer, Viktoria; Gansterer, Wilfried (Korresp. Autor*in).
Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium, IPDPS 2022. 2022. S. 459-469.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Resiliency in numerical algorithm design for extreme scale simulations. / Agullo, Emmanuel; Altenbernd, Mirco; Anzt, Hartwig et al.
in: International Journal of High Performance Computing Applications (S A H P C), Band 36, Nr. 2, 03.2022, S. 251-285.
Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
Algorithm-Based Checkpoint-Recovery for the Conjugate Gradient Method. / Pachajoa, Carlos; Pacher, Christina; Levonyak, Markus et al.
Proceedings of the 49th International Conference on Parallel Processing (ICPP 2020). 2020. S. 1-11 14 (Proceedings of the International Conference on Parallel Processing).
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Fault-tolerant least squares solvers for wireless sensor networks based on gossiping. / Prikopa, Karl E.; Gansterer, Wilfried (Korresp. Autor*in).
in: Journal of Parallel and Distributed Computing, Band 136, 02.2020, S. 52-62.
Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
Scalable Resilience Against Node Failures for Communication-Hiding Preconditioned Conjugate Gradient and Conjugate Residual Methods. / Levonyak, Markus; Pacher, Christina; Gansterer, Wilfried (Korresp. Autor*in).
Proceedings of the 2020 SIAM Conference on Parallel Processing for Scientific Computing. 2020. S. 81-92.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
A Generic Strategy for Node-Failure Resilience for Certain Iterative Linear Algebra Methods. / Pachajoa Mejia, Carlos Andres; Ernstbrunner, Robert; Gansterer, Wilfried (Korresp. Autor*in).
Proceedings of FTXS 2020: Fault Tolerance for HPC at eXtreme Scale. 2020. S. 41-50.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Projekte
Algorithmic Data Science for Computational Drug Discovery
Resilience versus Performance in Numerical Linear Algebra
Vorträge
Algorithm-based Resilience in Scalable Conjugate Gradient Methods
A Generic Strategy for Node-Failure Resilience for Certain Iterative Linear Algebra Methods
Algorithm-based checkpoint-recovery for the conjugate gradient method
Node-Failure-Resistant Preconditioned Conjugate Gradient Method
Resilience for Large-Scale Iterative Linear Solvers
Scalable Resilience Against Node Failures for Communication-Hiding Preconditioned Conjugate Gradient and Conjugate Residual Methods
Node-failure-resistant preconditioned conjugate gradient method without replacement nodes
Extending a Preconditioned Conjugate Gradient Method Endowed with Resilience to Multiple Node Failures
How to Make the Preconditioned Conjugate Gradient Method Resilient Against Multiple Node Failures
Comparing Randomized and Deterministic Approaches for Computing Low-rank Approximations
Fast Recovery from Node Failures for the Parallel Preconditioned Conjugate Gradient Method
Some Notes on Divide-and-Conquer Eigensolvers
Silent Data Corruption in Reduction and Matrix Multiplication
Silent Data Corruption in BLAS Kernels
Resilience Properties of Gossip-Style Algorithms
Analysis and Comparison of Truly Distributed Solvers for Linear Least Squares Problems on Wireless Sensor Networks
A Truly Distributed Iterative Refinement Linear Least Squares Solver
Resiliency and Reliability in Distributed Aggregation: From Theory to Practice
Improving Fault Tolerance and Accuracy of Distributed Reduction Algorithms
Distributed Reduction and Matrix Computations
Randomized Distributed Matrix Computations based on Gossiping
New Developments for the Block Divide-and-Conquer Eigensolver
A Fast Solver for Modeling the Evolution of Virus Populations
Scalable and Fault Tolerant Orthogonalization Based on Randomized Aggregation
Towards Distributed Matrix Computations Across Wireless Networks
Distributed Linear Solvers for Field Reconstruction
On Modelling the Evolution of Virus Populations
The EU Data Retentrion Directive 2006/24/EC from a Technical Perspective : general assembly of the Internet Service Provicers Austria
Grid Application Projects in CPAMMS : Status and Perspectives COST D37 Multi Working Group Meeting
Ab initio photodynamics calculations on the Grid: approaches and applications
A Reliable Component-Based Architecture for E-Mail Filtering : Second International Conference on Availability
High Performance Computing Challenges in Drug Design : Computational Life Sciences Seminar
Grid Computing - Middleware and other Central Aspects : Working group meeting of COST D37/001/06 PHOTODYN: Computational photochemistry and photobiology
Self-Learning and Fully Transparent UCE Prevention
Project Spam Defense - Status and Directions : presentation invited by the Internet Service Providers Austria
Project Spam Defense - Status and Outlook : presentation invited by the Internet Service Providers Austria
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