Univ.-Prof. Dipl.-Ing. Dr. Siegfried Benkner
1090 Wien
Raum : 6.21
Lehrveranstaltungen
Wintersemester 2026
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051030 VU Programmiersprachen und -konzepte
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051080 LP Softwarepraktikum mit Bachelorarbeit
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052511 VU Cloud Computing
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052800 VU Parallel Computing
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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
Sommersemester 2026
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051080 LP Softwarepraktikum mit Bachelorarbeit
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052800 VU Parallel Computing
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052812 VU High Performance Computing
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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
Wintersemester 2025
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051030 VU Programmiersprachen und -konzepte
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051080 LP Softwarepraktikum mit Bachelorarbeit
-
052511 VU Cloud Computing
-
052800 VU Parallel Computing
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053021 LP Praktikum Informatik 1
-
053031 LP Praktikum Informatik 2
-
053049 SE Masterseminar
-
500500 SE Doktoranden Forschungsseminar - Algorithms and Computing
Publikationen
The OCR-Vx experience: lessons learned from designing and implementing a task-based runtime system. / Dokulil, Jiri; Benkner, Siegfried (Korresp. Autor*in).
in: Journal of Supercomputing: an international journal of supercomputing design, analysis and use, Band 78, 07.2022, S. 12344-12379.
Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
Matching Program Implementations and Heterogeneous Computing Systems. / Sandrieser, Martin; Benkner, Siegfried.
2021. Beitrag in The 22nd International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), Guangzhou, China.
Veröffentlichungen: Beitrag zu Konferenz › Paper › Peer Reviewed
Task-Based Performance Portability in HPC: Maximising long-term investments in a fast evolving, complex and heterogeneous HPC landscape. / Aumage, Olivier; Carpenter, Paul; Benkner, Siegfried.
2021. Beitrag in European Technology Platform for High Performance Computing (ETP4HPC), Unbekannt/undefiniert.
Veröffentlichungen: Beitrag zu Konferenz › Paper › Peer Reviewed
A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit. / Petrovic, Filip; Strelak, David; Hozzova, Jana et al.
in: Future Generation Computer Systems: the international journal of grid computing, Band 108, 07.2020, S. 161-177.
Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
NUMA-aware CPU core allocation in cooperating dynamic applications. / Dokulil, Jiri; Benkner, Siegfried.
2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020. Institute of Electrical and Electronics Engineers Inc., 2020. S. 950-957 9150478.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Automatic placement of tasks to NUMA nodes in iterative applications. / Dokulil, Jiri; Benkner, Siegfried.
2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2020. Institute of Electrical and Electronics Engineers Inc., 2020. S. 192-195 9092212.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Programming Languages for Data-Intensive HPC Applications: a Systematic Mapping Study. / Amarala, Vasco; Norberto, Beatriz; Goulao, Miguel et al.
in: Parallel Computing, Band 91, 102584, 03.2020.
Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
Exploring the performance of fine-grained synchronization and data exchange across process boundaries on modern multi-core architectures. / Dokulil, Jiri; Benkner, Siegfried.
Computational Science - ICCS 2019 - 19th International Conference, 2019, Proceedings. Hrsg. / João M.F. Rodrigues; Pedro J.S. Cardoso; Jânio Monteiro; Roberto Lam; Valeria V. Krzhizhanovskaya; Michael H. Lees; Jack J. Dongarra; Peter M.A. Sloot. Cham: Springer, 2019. S. 514-520 (Lecture Notes in Computer Science, Band 11540 LNCS).
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Big Data Processing, Analysis and Applications in Mobile Cellular Networks. / Brdar, Sanja; Novovic, Olivera; Grujic, Nastasija et al.
High-Performance Modelling and Simulation for Big Data Applications. Hrsg. / Johanna Kolodzej; Horacio Gonzalez-Velez. Springer, 2019. S. 163-185 (Lecture Notes in Computer Science, Band 11400).
Veröffentlichungen: Beitrag in Buch › Beitrag in Buch/Sammelband › Peer Reviewed
Pipeline Patterns on top of Task-Based Runtimes. / Bajrovic, Enes; Benkner, Siegfried; Dokulil, Jiri.
Parallel and Distributed Computing, Applications and Technologies - 19th International Conference, PDCAT 2018, Revised Selected Papers. Hrsg. / Hong Shen; Yunsick Sung; Jong Hyuk Park; Hui Tian. 2019. S. 100-110.
Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed
Projekte
Resilienter Betrieb kritischer Infrastrukturen
Innovative Algorithms for Applications on European Exascale Supercomputers
Offline- und Online-Autotuning von Parallelen Programmen
Dynamisches Laufzeitsystem für zukünftige Parallelrechner
AutoTune
VPH-Share
PEPPHER
My Science
ANEURIST
Vorträge
CBM4Scale: Compressed Binary Matrices for Scaling
Future Directions in Programming Support for Parallel and Distributed Systems
Programming Support for Future Parallel Architectures
OCR Developments at the University of Vienna
OCR-Vx An alternative Implementation of OCR
Towards an Adaptive Data Analytics Framework
Implementing the Open Community Runtime for Shared-Memory and Distributed-Memory Systems
Tuning OpenCL Applications with the Periscope Tuning Framework
Programming Support for Future Parallel Architectures
Recent and Future Activities in High-Performance Computing and Scientific Data Management
Recent and Future Activities in HPC and Scientific Data Management
VPH-Share - Collaborative Platform for Medical Research
The AutoTune Project
Introduction to MuCoCoS-2014
Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures
Automatic Performance Tuning for Parallel Architectures
The European Autotune Project
Programming Support for Heterogeneous Many-core Architectures
An Overview of the European AutoTune Project
Performance Portability and Programmability for Heterogeneous Many-core Architectures
Performance Portability and Programmability for Heterogeneous Many-core Architectures
Hybrid Execution - Easier Than Ever
High-Level Support for Pipeline Parallelism on Manycore Architectures
Programmability and Performance Portability for Heterogeneous Many-Core Systems
The PEPPHER Component System and Coordination Language for Performance-Portable Programming of Heterogeneous Multi-/Manycore Systems
High-Level Language Support for Heterogeneous Manycore Architectures
Language Support for Pipelined Applications on Heterogeneous Many-Core Architectures
Improving Programmability of Heterogeneous Many-Core Systems via Explicit Platform Descriptions
Programmability and Portability for Heterogeneous Parallel Systems
Virtualizing Scientific Applications and Data Sources as Grid Services
The @neurIST Grid Infrastructure for Biomedical Data and Compute Services
A Service-oriented Grid Infrastructure for Biomedical Data and Compute Services
Supporting SLA Negotiation for Grid-based Medical Simulation Services
Semantic Description of Data Services within the @neurIST Grid Architecture
A Generic QoS Infrastructure for Grid Web Applications and Services
Parallel Cholesky Factorization on Clusters of SMPs
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