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Sascha Hunold

Associate Prof. Dr.rer.nat.

Research Focus

  • Computer Engineering: 100%

Research Areas

  • Scheduling, parallel computing, parallel programming, parallel algorithms, High performance computing
Sascha Hunold

Roles

  • Vice Dean of Academic Affairs
    Informatics Bachelor
    Office of the Dean, E199-01
  • Associate Professor
    Parallel Computing, E191-04
  • Curriculum Coordinator
    Master / Area / High Performance Computing

Contact

2024W

2025S

 

2024

2023

2022

  • An Overhead Analysis of MPI Profiling and Tracing Tools / Hunold, S., Ajanohoun, J. I., Vardas, I., & Träff, J. L. (2022). An Overhead Analysis of MPI Profiling and Tracing Tools. In C. Scully-Allison, R. Liem, & A. V. Solorzano (Eds.), PERMAVOST 2022: Proceedings of the 2nd Workshop on Performance Engineering, Modelling, Analysis, and Visualization Strategy (pp. 5–13). Association for Computing Machinery (ACM). https://doi.org/10.1145/3526063.3535353
    Download: Open Access (985 KB)
    Projects: Autotune (2021–2025) / Process Mapping (2019–2024)
  • Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia / Hunold, S., & Przybylski, B. (2022, May 18). Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia [Conference Presentation]. New Challenges in Scheduling Theory (Centre CNRS “Paul-Langevin”, Aussois, France), Aussois, France. http://hdl.handle.net/20.500.12708/153814
  • Performance Tuning of MPI Collectives - Status Quo and Open Problems / Hunold, S. (2022). Performance Tuning of MPI Collectives - Status Quo and Open Problems [Presentation]. CaSToRC HPC National Competence Center Fall Seminar Series 2022, Unknown. http://hdl.handle.net/20.500.12708/153709
    Project: Autotune (2021–2025)
  • MPI Performance Tools under the Microscope: A Thorough Overhead Analysis / Ajanohoun, J. I., Vardas, I., Träff, J. L., & Hunold, S. (2022). MPI Performance Tools under the Microscope: A Thorough Overhead Analysis. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2022 - ASHPC22 (p. 16). EuroCC Austria. http://hdl.handle.net/20.500.12708/55697
  • mpisee: MPI Profiling for Communication and Communicator Structure / Vardas, I., Hunold, S., Ajanohoun, J. I., & Träff, J. L. (2022). mpisee: MPI Profiling for Communication and Communicator Structure. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2022 - ASHPC22 (p. 15). EuroCC Austria. http://hdl.handle.net/20.500.12708/55696
  • mpisee: MPI Profiling for Communication and Communicator Structure / Vardas, I., Hunold, S., Ajanohoun, J. I., & Traff, J. L. (2022). mpisee: MPI Profiling for Communication and Communicator Structure. In 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops (IPDPSW 2022) (pp. 520–529). IEEE. https://doi.org/10.1109/IPDPSW55747.2022.00092
    Projects: Autotune (2021–2025) / Process Mapping (2019–2024)

2021

  • MicroBench Maker: Reproduce, Reuse, Improve / Hunold, S., Ajanohoun, J. I., & Carpen-Amarie, A. (2021). MicroBench Maker: Reproduce, Reuse, Improve. In 2021 International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS). 12th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS 2021) in conjunction with SC 2021, St. Louis, Missouri, United States of America (the). IEEE. https://doi.org/10.1109/pmbs54543.2021.00013
    Project: Autotune (2021–2025)
  • Teaching Complex Scheduling Algorithms / Hunold, S., & Przybylski, B. (2021). Teaching Complex Scheduling Algorithms. In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 11th NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar 2021) in conjunction with 35th IEEE IPDPS 2021 - Online Conference, Portland, Oregon, USA, United States of America (the). IEEE. https://doi.org/10.1109/ipdpsw52791.2021.00058
  • MPI collective communication through a single set of interfaces: A case for orthogonality / Träff, J. L., Hunold, S., Mercier, G., & Holmes, D. J. (2021). MPI collective communication through a single set of interfaces: A case for orthogonality. Parallel Computing: Systems & Applications, 107(102826), 102826. https://doi.org/10.1016/j.parco.2021.102826
    Project: Process Mapping (2019–2024)

2020

  • Efficient Process-to-Node Mapping Algorithms for Stencil Computations / Hunold, S., von Kirchbach, K., Lehr, M., Schulz, C., & Träff, J. L. (2020). Efficient Process-to-Node Mapping Algorithms for Stencil Computations. arXiv. https://doi.org/10.48550/arXiv.2005.09521
    Project: Process Mapping (2019–2024)
  • Decomposing MPI Collectives for Exploiting Multi-lane Communication / Träff, J. L., & Hunold, S. (2020). Decomposing MPI Collectives for Exploiting Multi-lane Communication. In 2020 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing (IEEE Cluster 2020) - Online Conference, Kobe, Japan. IEEE. https://doi.org/10.1109/cluster49012.2020.00037
  • Predicting MPI Collective Communication Performance Using Machine Learning / Hunold, S., Bhatele, A., Bosilca, G., & Knees, P. (2020). Predicting MPI Collective Communication Performance Using Machine Learning. In 2020 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing (IEEE Cluster 2020) - Online Conference, Kobe, Japan. IEEE. https://doi.org/10.1109/cluster49012.2020.00036
  • Collectives and Communicators: A Case for Orthogonality / Träff, J. L., Hunold, S., Mercier, G., & Holmes, D. J. (2020). Collectives and Communicators: A Case for Orthogonality. In 27th European MPI Users’ Group Meeting. 27th European MPI Users’ Group Meeting (EuroMPI/USA 2020) - Online Conference, Austin, United States of America (the). IEEE. https://doi.org/10.1145/3416315.3416319
  • Efficient Process-to-Node Mapping Algorithms for Stencil Computations / von Kirchbach, K., Lehr, M., Hunold, S., Schulz, C., & Träff, J. L. (2020). Efficient Process-to-Node Mapping Algorithms for Stencil Computations. In 2020 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing (IEEE Cluster 2020) - Online Conference, Kobe, Japan. IEEE. https://doi.org/10.1109/cluster49012.2020.00011
    Project: Process Mapping (2019–2024)
  • Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia / Hunold, S., & Przybylski, B. (2020). Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia. arXiv. https://doi.org/10.48550/arXiv.2003.05217

2019

  • Cartesian Collective Communication / Träff, J. L., & Hunold, S. (2019). Cartesian Collective Communication. In Proceedings of the 48th International Conference on Parallel Processing. 48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan. ACM. https://doi.org/10.1145/3337821.3337848
  • On the Importance of Data Quality when Tuning MPI Libraries / Hunold, S., & Carpen-Amarie, A. (2019). On the Importance of Data Quality when Tuning MPI Libraries. In G. Haase (Ed.), Austrian HPC Meeting 2019 - AHPC19 (AHPC19 booklet of abstracts) (p. 15). Institut für Mathematik und wissenschaftliches Rechnen der Universität Graz. http://hdl.handle.net/20.500.12708/57798
  • LigandScout Remote: A New User-Friendly Interface for HPC and Cloud Resources / Kainrad, T., Hunold, S., Seidel, T., & Langer, T. (2019). LigandScout Remote: A New User-Friendly Interface for HPC and Cloud Resources. Journal of Chemical Information and Modeling, 59(1), 31–37. https://doi.org/10.1021/acs.jcim.8b00716
  • Benchmarking and scheduling on parallel machines / Hunold, S. (2019). Benchmarking and scheduling on parallel machines [Professorial Dissertation, Technische Universität Wien]. reposiTUm. http://hdl.handle.net/20.500.12708/159450

2018

  • Autotuning MPI Collectives using Performance Guidelines / Hunold, S., & Carpen-Amarie, A. (2018). Autotuning MPI Collectives using Performance Guidelines. In Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region. International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2018), Tokyo, Japan. ACM. https://doi.org/10.1145/3149457.3149461
  • Algorithm Selection of MPI Collectives Using Machine Learning Techniques / Hunold, S., & Carpen-Amarie, A. (2018). Algorithm Selection of MPI Collectives Using Machine Learning Techniques. In 2018 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS). 9th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS 2018) in conjunction with SC 2018, Dallas, United States of America (the). IEEE. https://doi.org/10.1109/pmbs.2018.8641622
  • Hierarchical Clock Synchronization in MPI / Hunold, S., & Carpen-Amarie, A. (2018). Hierarchical Clock Synchronization in MPI. In 2018 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing, CLUSTER 2018, Belfast, United Kingdom of Great Britain and Northern Ireland (the). IEEE. https://doi.org/10.1109/cluster.2018.00050

2017

  • Autotuning MPI Collectives using Performance Guidelines / Hunold, S., & Carpen-Amarie, A. (2017). Autotuning MPI Collectives using Performance Guidelines. LIG - Bâtiment IMAG, St Martin d’Hères, France. http://hdl.handle.net/20.500.12708/86599
  • Tuning MPI Collectives by Verifying Performance Guidelines / Hunold, S., & Carpen-Amarie, A. (2017). Tuning MPI Collectives by Verifying Performance Guidelines. arXiv. https://doi.org/10.48550/arXiv.1707.09965
  • On expected and observed communication performance with MPI derived datatypes / Carpen-Amarie, A., Hunold, S., & Träff, J. L. (2017). On expected and observed communication performance with MPI derived datatypes. Parallel Computing: Systems & Applications, 69, 98–117. https://doi.org/10.1016/j.parco.2017.08.006
    Projects: EPiGRAM (2013–2016) / MPI (2013–2018)
  • Scheduling Independent Moldable Tasks on Multi-Cores with GPUs / Bleuse, R., Hunold, S., Kedad-Sidhoum, S., Monna, F., Mounie, G., & Trystram, D. (2017). Scheduling Independent Moldable Tasks on Multi-Cores with GPUs. IEEE Transactions on Parallel and Distributed Systems, 28(9), 2689–2702. https://doi.org/10.1109/tpds.2017.2675891
  • Euro-Par 2016: Parallel Processing Workshops / Desprez, F., Dutot, P.-F., Kaklamanis, C., Marchal, L., Molitorisz, K., Ricci, L., Scarano, V., Vega-Rodriguez, M. A., Varbanescu, A. L., Hunold, S., Scott, S. L., Lankes, S., & Weidendorfer, J. (Eds.). (2017). Euro-Par 2016: Parallel Processing Workshops. Springer Nature Switzerland AG 2021. https://doi.org/10.1007/978-3-319-58943-5
  • Predicting the Energy-Consumption of MPI Applications at Scale Using Only a Single Node / Heinrich, F. C., Cornebize, T., Degomme, A., Legrand, A., Carpen-Amarie, A., Hunold, S., Orgerie, A.-C., & Quinson, M. (2017). Predicting the Energy-Consumption of MPI Applications at Scale Using Only a Single Node. In 2017 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing (CLUSTER 2017), Honolulu, Hawaii, USA, Non-EU. IEEE. https://doi.org/10.1109/cluster.2017.66
  • Introduction to REPPAR Workshop / Hunold, S., Legrand, A., & Nussbaum, L. (2017). Introduction to REPPAR Workshop. In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE. https://doi.org/10.1109/ipdpsw.2017.221

2016

  • Message-Combining Algorithms for Isomorphic, Sparse Collective Communication / Träff, J. L., Carpen-Amarie, A., Hunold, S., & Rougier, A. (2016). Message-Combining Algorithms for Isomorphic, Sparse Collective Communication. arXiv. https://doi.org/10.48550/arXiv.1606.07676
  • PGMPI: Automatically Verifying Self-Consistent MPI Performance Guidelines / Hunold, S., Carpen-Amarie, A., Lübbe, F. D., & Träff, J. L. (2016). PGMPI: Automatically Verifying Self-Consistent MPI Performance Guidelines. arXiv. https://doi.org/10.48550/arXiv.1606.00215
    Projects: MPI (2013–2018) / ReproPC (2013–2016)
  • MPI Derived Datatypes: Performance Expectations and Status Quo / Carpen-Amarie, A., Hunold, S., & Träff, J. L. (2016). MPI Derived Datatypes: Performance Expectations and Status Quo. arXiv. https://doi.org/10.48550/arXiv.1607.00178
    Projects: EPiGRAM (2013–2016) / MPI (2013–2018)
  • The art of benchmarking MPI libraries / Hunold, S. (2016). The art of benchmarking MPI libraries. Austrian HPC Meeting 2016 - AHPC16, Grundlsee, Austria. http://hdl.handle.net/20.500.12708/86269
  • The Art of MPI Benchmarking / Hunold, S. (2016). The Art of MPI Benchmarking. 45th SPEEDUP Workshop on High-Performance Computing, Basel, Switzerland, Non-EU. http://hdl.handle.net/20.500.12708/86310
  • The Art of MPI Benchmarking / Hunold, S. (2016). The Art of MPI Benchmarking. Lunchtime Seminar, Department of Computer Science, University of Innsbruck, Innsbruck, Austria, Austria. http://hdl.handle.net/20.500.12708/86282
  • Clock Synchronization Algorithms and SimGrid / Hunold, S. (2016). Clock Synchronization Algorithms and SimGrid. SimGrid User Days, CNRS center Villa Clythia, Fréjus, France, EU. http://hdl.handle.net/20.500.12708/86260
  • The art of benchmarking MPI libraries / Hunold, S., Carpen-Amarie, A., & Träff, J. L. (2016). The art of benchmarking MPI libraries. In I. Reichl, C. Blaas-Schenner, & J. Zabloudil (Eds.), Austrian HPC Meeting 2016 - AHPC 2016 (p. 45). Vienna Scientific Cluster (VSC). http://hdl.handle.net/20.500.12708/56921
  • On the Expected and Observed Communication Performance with MPI Derived Datatypes / Carpen-Amarie, A., Hunold, S., & Träff, J. L. (2016). On the Expected and Observed Communication Performance with MPI Derived Datatypes. In D. Holmes, A. Collis, J. L. Träff, & L. Smith (Eds.), Proceedings of the 23rd European MPI Users’ Group Meeting. ACM. https://doi.org/10.1145/2966884.2966905
    Projects: EPiGRAM (2013–2016) / MPI (2013–2018)
  • Automatic Verification of Self-consistent MPI Performance Guidelines / Hunold, S., Carpen-Amarie, A., Lübbe, F. D., & Träff, J. L. (2016). Automatic Verification of Self-consistent MPI Performance Guidelines. In P.-F. Dutot & D. Trystram (Eds.), Euro-Par 2016: Parallel Processing (pp. 433–446). Springer International Publishing. https://doi.org/10.1007/978-3-319-43659-3_32
    Projects: MPI (2013–2018) / ReproPC (2013–2016)

2015

2014

  • Stepping Stones to Reproducible Research: A Study of Current Practices in Parallel Computing / Carpen-Amarie, A., Rougier, A., & Lübbe, F. D. (2014). Stepping Stones to Reproducible Research: A Study of Current Practices in Parallel Computing. In L. Lopes, J. Zilinskas, A. Costan, R. G. Cascella, G. Kecskemeti, E. Jeannot, M. Cannataro, L. Ricci, S. Benkner, S. Petit, V. Scarano, J. Gracia, S. Hunold, S. L. Scott, S. Lankes, C. Lengauer, J. Carretero, J. Breitbart, & M. Alexander (Eds.), Euro-Par 2014: Parallel Processing Workshops Euro-Par 2014 International Workshops, Porto, Portugal, August 25-26, 2014, Revised Selected Papers, Part I (pp. 499–510). Springer International Publishing. https://doi.org/10.1007/978-3-319-14325-5_43
  • Reproducible MPI Micro-Benchmarking Isn't As Easy As You Think / Hunold, S., Carpen-Amarie, A., & Träff, J. L. (2014). Reproducible MPI Micro-Benchmarking Isn’t As Easy As You Think. Research Group Theory and Applications of Algorithms, University of Vienna, Vienna, Austria, Austria. http://hdl.handle.net/20.500.12708/85872
    Projects: MPI (2013–2018) / ReproPC (2013–2016)
  • One Step towards Bridging the Gap between Theory and Practice in Moldable Task Scheduling with Precedence Constraints / Hunold, S. (2014). One Step towards Bridging the Gap between Theory and Practice in Moldable Task Scheduling with Precedence Constraints. AIT Austrian Institute of Technology, Seibersdorf, Austria, Austria. http://hdl.handle.net/20.500.12708/85871
    Project: ReproPC (2013–2016)
  • Moldable Task Scheduling: Theory and Practice / Hunold, S. (2014). Moldable Task Scheduling: Theory and Practice. Workshop on New Challenges in Scheduling Theory, Aussois, France, EU. http://hdl.handle.net/20.500.12708/85817
  • Reproducibility of Experiments: It's about the WHO and less the HOW / Hunold, S. (2014). Reproducibility of Experiments: It’s about the WHO and less the HOW. Panel on reproducible research methodologies and new publication models, 4th International Workshop on Adaptive Self-tuning Computing Systems (ADAPT 2014) co-located with HiPEAC 2014, Vienna, Austria, Austria. http://hdl.handle.net/20.500.12708/85814
    Project: ReproPC (2013–2016)
  • One Step towards Bridging the Gap between Theory and Practice in Moldable Task Scheduling with Precedence Constraints / Hunold, S. (2014). One Step towards Bridging the Gap between Theory and Practice in Moldable Task Scheduling with Precedence Constraints. 9th Scheduling for Large Scale Systems Workshop, Lyon, France, EU. http://hdl.handle.net/20.500.12708/85812
  • Euro-Par 2014: Parallel Processing Workshops / Lopes, L., Zilinskas, J., Costan, A., Cascella, R. G., Kecskemeti, G., Jeannot, E., Cannataro, M., Ricci, L., Benkner, S., Petit, S., Scarano, V., Gracia, J., Hunold, S., Scott, S. L., Lankes, S., Lengauer, C., Carretero, J., Breitbart, J., & Alexander, M. (Eds.). (2014). Euro-Par 2014: Parallel Processing Workshops. Springer. https://doi.org/10.1007/978-3-319-14313-2
  • Euro-Par 2014: Parallel Processing Workshops / Lopes, L., Zilinskas, J., Costan, A., Cascella, R. G., Kecskemeti, G., Jeannot, E., Cannataro, M., Ricci, L., Benkner, S., Petit, S., Scarano, V., Gracia, J., Hunold, S., Scott, S. L., Lankes, S., Lengauer, C., Carretero, J., Breitbart, J., & Alexander, M. (Eds.). (2014). Euro-Par 2014: Parallel Processing Workshops. Springer. https://doi.org/10.1007/978-3-319-14325-5
  • Reproducible MPI Micro-Benchmarking Isn't As Easy As You Think / Hunold, S., Carpen-Amarie, A., & Träff, J. L. (2014). Reproducible MPI Micro-Benchmarking Isn’t As Easy As You Think. In J. Dongarra, Y. Ishikawa, & A. Hori (Eds.), Proceedings of the 21st European MPI Users’ Group Meeting. ACM. https://doi.org/10.1145/2642769.2642785
    Projects: MPI (2013–2018) / ReproPC (2013–2016)
  • Scheduling Moldable Tasks with Precedence Constraints and Arbitrary Speedup Functions on Multiprocessors / Hunold, S. (2014). Scheduling Moldable Tasks with Precedence Constraints and Arbitrary Speedup Functions on Multiprocessors. In R. Wyrzykowski, J. Dongarra, K. Karczewski, & J. Wasniewski (Eds.), Parallel Processing and Applied Mathematics (pp. 13–25). Springer. https://doi.org/10.1007/978-3-642-55195-6_2
  • Implementing a classic / Träff, J. L., Rougier, A., & Hunold, S. (2014). Implementing a classic. In M. Gerndt, P. Stenström, L. Rauchwerger, B. Miller, & M. Schulz (Eds.), Proceedings of the 28th ACM international conference on Supercomputing - ICS ’14. ACM. https://doi.org/10.1145/2597652.2597662

2013

2012

 

  • Best Short Paper / PMBS@Supercomputing
    2022 / USA
  • Best Paper Award IEEE CLUSTER 2020
    2020 / Japan
  • Best Paper Award EuroMPI/Asia
    2014 / Japan

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Sascha Hunold’s research profile in TISS .