Herr M. Sc.

Markus Frank

Research Assistant
Institute for Software Engineering
Reliable Software Systems Research Group
[Foto: University of Stuttgart]

Kontakt

+49 711 685-88272
+49 711 685-88472

Website
Visitenkarte (VCF)

Universitätsstraße 38
70569 Stuttgart
Deutschland
Raum: 1.328

Sprechstunde

by appointment

Fachgebiet

Performance Prediction for Multicore Systems


Multicore systems are a permanent part of your daly life. Regardless whether we consider nowadays desktop pc's, notebooks or smart phones all devices running on multicore CPUs. To use these hardware features in an efficient way we need parallel enabled software. But the development of such software is more complex then developing sequential software.


To handle the rising complexity it is necessary to develop software in an engineer-like way. In such a process Software Architects plan and analyze software designs on a model level. 
Software Architects can use tools like Palladio to simulate and analyze early phase software designs. Unfortunately, current approaches and tools lack the ability to consider multicore systems.
Therefor, we aim in this project to find performace prediction methods for multicore systems.

Publications:
  1. 2019

    1. Frank, M., Becker, S., Kaplan, A., & Koziolek, A. (2019). Performance-influencing Factors for Parallel and Algorithmic Problems in Multicore Environments: Work-In-Progress Paper. Companion of the 2019 ACM/SPEC International Conference on Performance Engineering, 21--24. ACM.
  2. 2018

    1. Frank, M., Klinaku, F., & Becker, S. (2018). Challenges in Multicore Performance Predictions. Companion of the 2018 ACM/SPEC International Conference on Performance Engineering, 47--48. https://doi.org/10.1145/3185768.3185773
    2. Klinaku, F., Frank, M., & Becker, S. (2018). CAUS: An Elasticity Controller for a Containerized Microservice. Companion of the 2018 ACM/SPEC International Conference on Performance Engineering, 93--98. https://doi.org/10.1145/3185768.3186296
    3. Frank, M., & Hakamian, A. (2018). An Architectural Template for Parallel Loops and Sections. Proceedings of the Symposium on Software Performance 2018, 7-9 November 2018, Hildesheim, Germany. Presented at the Hildesheim. Retrieved from https://www.performance-symposium.org/fileadmin/user_upload/palladio-conference/2018/papers/FrankHakamian18.pdf
    4. Hilbrich, M., & Frank, M. (2018b). HPC and SPE Need to Learn from Each Other-Knowledgetransformation Patterns. The 18th International Symposium on Scientific Computing, Computer Arithmetic, and Verified Numerical Computations, 58–59. Tokyo, Japan.
    5. Hilbrich, M., & Frank, M. (2018a). Abstract Fog in the Bottle-Trends of Computing in History and Future. 2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 519--522. IEEE.
  3. 2017

    1. Hilbrich, M., & Frank, M. (2017d). Time-Aligned Similarity Calculations for Job-Centric Monitoring. IEEE 2017 CloudCom-Asia International Conference.
    2. Hilbrich, M., & Frank, M. (2017b). Enforcing Security and Privacy via a Cooperation of Security Experts and Software Engineers-a Model-based Vision. Proceedings of the 7th IEEE International Symposium on Cloud and Service Computing, 22-25 November 2017, Kanazawa, Japan. Presented at the Kanazawa. Kanazawa.
    3. Frank, M., Hilbrich, M., Lehrig, S., & Becker, S. (2017). Parallelization, Modeling, and Performance Prediction in the Multi-/Many Core Area: A Systematic Literature Review. Proceedings of the 7th IEEE International Symposium on Cloud and Service Computing, 22-25 November 2017, Kanazawa, Japan. Presented at the Kanazawa. Kanazawa.
    4. Hilbrich, M., & Frank, M. (2017a). Debugging a Complex Systems, the Long Way from Data to Knowledge. Proceedings of the Symposium on Software Performance 2017, 9-10 November 2017, Karlsruhe, Germany. Presented at the Karlsruhe. Retrieved from http://www.performance-symposium.org/2017/program/debugging-a-complex-systems-the-long-way-from-data-to-knowledge/
    5. Frank, M., Staude, S., & Hilbrich, M. (2017). Is the PCM Ready for ACTORs and Multicore CPUs? - A Use Case-based Evaluation. Proceedings of the Symposium on Software Performance 2017, 9-10 November 2017, Karlsruhe, Germany. Presented at the Karlsruhe. Retrieved from http://www.performance-symposium.org/fileadmin/user_upload/palladio-conference/2017/papers/Is_the_PCM_Ready_for_ACTORs_and_Multicore_CPUs_A_Use_Case-based_Evaluation.pdf
    6. Hilbrich, M., & Frank, M. (2017c). Analysis of Series of Measurements from Job-Centric Monitoring by Statistical Functions. Computer Science, 18(1), 2. Retrieved from https://journals.agh.edu.pl/csci/article/view/1791
  4. 2016

    1. Hilbrich, M., Lehrig, S., & Frank, M. (2016). Measured Values Lost in Time---or How I rose from a User to a Developer of Palladio.
    2. Richter, P., Frank, M., & Schlieter, H. (2016). Entwicklung eines Leitlinienmanagementsystems - Anforderungen und konzeptuelle Vorarbeiten. Multikonferenz Wirtschaftsinformatik (MKWI) 2016 : Technische Universit\ät Ilmenau, 09. - 11. M\ärz 2016; Band II, 679–690.
    3. Hilbrich, M., Frank, M., & Lehrig, S. (2016). Security Modeling with Palladio---Different Approaches. Proceedings of the Symposium on Software Performance 2016, 7-9 November 2016, Kiel, Germany. Retrieved from https://sdqweb.ipd.kit.edu/typo3/sdq/fileadmin/user_upload/palladio-conference/2016/papers/Security_Modeling_with_Palladio-Different_Approaches.pdf
    4. Frank, M., & Hilbrich, M. (2016). Performance Prediction for Multicore Environments---An Experiment Report. Proceedings of the Symposium on Software Performance 2016, 7-9 November 2016, Kiel, Germany. Retrieved from https://sdqweb.ipd.kit.edu/typo3/sdq/fileadmin/user_upload/palladio-conference/2016/papers/Performance_Prediction_for_Multicore_Environments_-_An_Experiment_Report.pdf
  5. 2015

    1. Hilbrich, M., & Frank, M. (2015a). Analysis of Series of Measurements from Job-Centric Monitoring by  Statistical Functions. In M. Bubak, M. Turala, & K. Wiatr (Eds.), CGW Workshop ’15 Proceedings (pp. 81–82; By M. Bubak, M. Turala, & K. Wiatr). ACC Cyfronet AGH.
    2. Hilbrich, M., & Frank, M. (2015b). Better Resource Usage by Job-Centric Monitoring.
  • M.Sc Wirtschaftsinformatik
  • 2012 - 2014
  • Research Assistent, TU Chemenitz
  • Prof. Dr. Steffen Becker
  • Faculty of Computer Science
  • Software Engineering Chair
  • June 2015 - September 2017
  • Research Assistent, Uni Stuttgart
  • Prof. Dr. Steffen Becker
  • Institute for Software Engineering
  • Reliable Software Systems Group
  • Since October 2017
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