Veröffentlichungen

[P24b] J. Posner: Resource Adaptivity at Task-Level. Supercomputing: Parallel Applications Workshop, Alternatives To MPI+X (PAW-ATM). Extended Abstract. To appear, 2024.

[P24a] J. Posner: The Impact of Evolving APGAS Programs on HPC Clusters. Proceedings Euro‐Par Parallel Processing Workshops (DynResHPC). To appear, 2024. Slides. Preprint.

[PP24c] J. Posner, P. Finnerty: Project Wagomu: Elastic HPC Resource Management. Poster. ISC High Performance Conference. 2024.

[PP24b] J. Posner, R. Goebel, P. Finnerty: Evolving APGAS Programs: Automatic and Transparent Resource Adjustments at Runtime. Proceedings Workshop on Asynchronous Many‑Task Systems and Applications (WAMTA). 2024. Slides.

[PP24a] P. Finnerty, J. Posner, J. Bürger, L. Takaoka, T. Kanzaki: On the Performance of Malleable APGAS Programs and Batch Job Schedulers. SN Computer Science. Springer, 2024.

[PP23b] J. Posner, F. Hupfeld, P. Finnerty: Enhancing Supercomputer Performance with Malleable Job Scheduling Strategies. Proceeding Euro‐Par Parallel Processing Workshops (PECS). Springer, 2023. Slides.

[PP23a] P. Finnerty, R. Takaoka, T. Kanzaki, J. Posner: Malleable APGAS Programs and their Support in Batch Job Schedulers. Proceeding Euro‐Par Parallel Processing Workshops (AMTE). Springer, 2023. Slides.

[P22a] J. Posner: Asynchronous Many-Tasking (AMT): Load Balancing, Fault Tolerance, Resource Elasticity. Poster. ISC High Performance Conference, 2022.

[PRF22a] J. Posner, L. Reitz, C. Fohry: Task-Level Resilience: Checkpointing vs. Supervision. Int. Journal of Networking and Computing, Vol. 12, No. 1, 2022.

[P21c] Jonas Posner: Load Balancing, Fault Tolerance, and Resource Elasticity for Asynchronous Many-Task Systems. Dissertation, Universität Kassel, 2021.

[PF21a] J. Posner,  C. Fohry: Transparent Resource Elasticity for Task-Based Cluster Environments with Work Stealing. Proc. Int. Conference on Parallel Processing (ICPP) Workshops (P2S2), 2021.

[P21b] J. Posner: Resource Elasticity at Task-Level; Poster, PhD Forum Int. Parallel and Distributed Processing Symposium, 2021, Extended Infos.

[PRF21a] J. Posner, L. Reitz, C. Fohry: Checkpointing vs. Supervision Resilience Approaches for Dynamic Independent Tasks. Proc. IEEE Int. Parallel and Distributed Processing Symp., Workshop on Advances in Parallel and Distributed Computational Models, 2021, pp. 556-565.

[P21a] J. Posner. Locality-Flexible and Cancelable Tasks for the APGAS Library. Poster. EuroHPC Summit Week, PRACEdays, 2021.

[P20a] J. Posner. System-Level vs. Application-Level Checkpointing. Poster Paper. Proc. IEEE Int. Conf. on Cluster Computing (CLUSTER), 2020.

[PRF19a] J. Posner, L. Reitz, C. Fohry. A Comparison of Application-Level Fault Tolerance Schemes for Task Pools. Future Generation Computer Systems (Special Issue), Vol. 105, April 2020.

[PRF18a] J. Posner, L. Reitz, C. Fohry: Comparison of the HPC and Big Data Java Libraries Spark, PCJ and APGAS; Supercomputing, Parallel Applications Workshop (PAW-ATM), 2018, pp. 11-22.

[FPR18a] C. Fohry, J. Posner, L. Reitz: A Selective and Incremental Backup Scheme for Task Pools; Proc. Int. Conf. on High Performance Computing & Simulation (HPCS), 2018, pp. 621-628.

[PF18b] J. Posner, C. Fohry: Hybrid Work Stealing of Locality-Flexible and Cancelable Tasks for the APGAS Library. The Journal of Supercomputing, Vol. 74, No. 4, 2018, pp. 1435–1448.

[PF18a] J. Posner, C. Fohry: A Java Task Pool Framework providing Fault Tolerant Global Load Balancing. Int. Journal of Networking and Computing, Vol. 8, No. 1, 2018, pp. 2–31.

[PF17b] J. Posner, C. Fohry: A Combination of Intra- and Inter-Place Work Stealing for the APGAS Library. Proc. Int. Conf. on Parallel Processing and Applied Mathematics, Workshop on Language-Based Parallel Programming Models, 2018, Springer LNCS 10778, pp. 234–243.

[P17a] J. Posner: A Generic Reusable Java Framework for Fault-Tolerant Parallelization with the Task Pool Pattern; Poster, PhD Forum Int. Parallel and Distributed Processing Symposium, 2017.

[PF17a] J. Posner, C. Fohry: Fault Tolerance for Cooperative Lifeline-Based Global Load Balancing in Java with APGAS and Hazelcast. Proc. IEEE Int. Parallel and Distributed Processing Symp., Workshop on Advances in Parallel and Distributed Computational Models, 2017, pp. 854–863. Source code

[PF16a] J. Posner, C. Fohry: Cooperation vs. Coordination for Lifeline-Based Global Load Balancing in APGAS. X10 Workshop, 2016, ACM, pp. 13–17.

[FBP15b] C. Fohry, M. Bungart, J. Posner: Fault Tolerance Schemes for Global Load Balancing in X10. Scalable Computing: Practice and Experience, Vol. 16, No. 2, 2015, pp. 169–185. Source code

[FBP15a] C. Fohry, M. Bungart, J. Posner: Towards an Efficient Fault-Tolerance Scheme for GLB. X10 Workshop, 2015, ACM, pp. 27–32.

[BFP14] M. Bungart, C. Fohry, J. Posner: Fault-Tolerant Global Load Balancing in X10. Proc. IEEE Int. Symp. on Symbolic and Numeric Algorithms for Scientific Computing, pp. 471–478. Source code

Source code

https://github.com/projectwagomu/