Hunold, S., Xie, B., & Shu, K. (Eds.). (2024). Benchmarking, Measuring, and Optimizing : 15th BenchCouncil International Symposium, Bench 2023, Revised Selected Papers (Vol. 14521). Springer Singapore. https://doi.org/10.1007/978-981-97-0316-6, öffnet eine externe URL in einem neuen Fenster

Laso Rodriguez, R., Krupitza, D., & Hunold, S. (2024). pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations (arXiv:2402.06384). https://doi.org/10.48550/arXiv.2402.06384, öffnet eine externe URL in einem neuen Fenster

Salimi Beni, M., Hunold, S., & Cosenza, B. (2024). Analysis and prediction of performance variability in large-scale computing systems. Journal of Supercomputing, 80(10), 14978–15005. https://doi.org/10.1007/s11227-024-06040-w, öffnet eine externe URL in einem neuen Fenster

Hunold, S. (2023, December 8). Unveiling the Complexities of Performance Analysis and Optimization in HPC Systems. Universität Münster, Münster, Germany.

Hunold, S. (2023). Verifying Performance Guidelines for MPI Collectives at Scale. In Proceedings of 2023 SC23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC23 Workshops) (pp. 1264–1268). ACM. https://doi.org/10.1145/3624062.3625532, öffnet eine externe URL in einem neuen Fenster

Swartvagher, P., Hunold, S., Träff, J. L., & Vardas, I. (2023). Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures. In Proceedings of 2023 SC23 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis (SC 2023 Workshops) (pp. 405–415). ACM. https://doi.org/10.1145/3624062.3624109, öffnet eine externe URL in einem neuen Fenster

Laso Rodriguez, R., & Casado, F. E. (2023, November 3). The research career after the PhD. CiTIUS (USC), Santiago de Compostela, Spain.

Träff, J. L., & Vardas, I. (2023). Library Development with MPI: Attributes, Request Objects, Group Communicator Creation, Local Reductions, and Datatypes. In Proceedings of the 30th European MPI Users’ Group Meeting (EUROMPI 23). 30th European MPI Users’ Group Meeting (EuroMPI 2023), Bristol, United Kingdom of Great Britain and Northern Ireland (the). ACM. https://doi.org/10.1145/3615318.3615323, öffnet eine externe URL in einem neuen Fenster

Schuchart, J., Hunold, S., & Bosilca, G. (2023). Synchronizing MPI Processes in Space and Time. In EuroMPI “23: Proceedings of the 30th European MPI Users” Group Meeting (pp. 1–11). ACM. https://doi.org/10.1145/3615318.3615325, öffnet eine externe URL in einem neuen Fenster

Forsell, M., Roivainen, J., Leppänen, V., & Träff, J. L. (2023). Realizing multioperations and multiprefixes in Thick Control Flow processors. Microprocessors and Microsystems, 98, Article 104807. https://doi.org/10.1016/j.micpro.2023.104807, öffnet eine externe URL in einem neuen Fenster

Forsell, M., Roivainen, J., Leppänen, V., & Träff, J. L. (2023). Preliminary Performance and Memory Access Scalability Study of Thick Control Flow Processors. In J. Nurmi, M. Shen, P. Ellervee, P. Koch, & F. Moradi (Eds.), Proceedings 2023 IEEE Nordic Circuits and Systems Conference (NorCAS) (pp. 1–7). IEEE. https://doi.org/10.1109/NorCAS58970.2023.10305463, öffnet eine externe URL in einem neuen Fenster

Hunold, S., & Hagn, M. (2023). MPI is Good, Control is Better: Checking Performance Guidelines of Collectives. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 60–60). EuroCC Austria. https://doi.org/10.34726/5367, öffnet eine externe URL in einem neuen Fenster

Hunold, S., & Kraßnitzer, K. D. V. (2023). A Quantitative Analysis of OpenMP Task Runtime Systems. In A. Gainaru, C. Zhang, & C. Luo (Eds.), Benchmarking, Measuring, and Optimizing : 14th BenchCouncil International Symposium, Bench 2022, Virtual Event, November 7-9, 2022, Revised Selected Papers (pp. 3–18). Springer. https://doi.org/10.1007/978-3-031-31180-2_1, öffnet eine externe URL in einem neuen Fenster

Hunold, S., & Steiner, S. (2023). OMPICollTune: Autotuning MPI Collectives by Incremental Online Learning. In Proceedings of PMBS 2022: performance modeling, benchmarking and simulation of high performance computer systems (pp. 123–128). IEEE. https://doi.org/10.1109/PMBS56514.2022.00016, öffnet eine externe URL in einem neuen Fenster

Hunold, S., Vardas, I., Ibis, G., & Langer, T. (2023). Massively Scaling Molecular Screening Workloads on EuroHPC Supercomputers. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 51–51). EuroCC Austria. https://doi.org/10.34726/5366, öffnet eine externe URL in einem neuen Fenster

Swartvagher, P., Vardas, I., Hunold, S., & Träff, J. L. (2023). Rank Reordering within MPI Communicators to Exploit Deep Hierarchal Architectures of Supercomputers. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 61–61). EuroCC Austria. https://doi.org/10.34726/5368, öffnet eine externe URL in einem neuen Fenster

Träff, J. L., Hunold, S., Vardas, I., & Funk, N. M. (2023). Uniform Algorithms for Reduce-scatter and (most) other Collectives for MPI. In 2023 IEEE International Conference on Cluster Computing (CLUSTER) (pp. 284–294). IEEE. https://doi.org/10.1109/CLUSTER52292.2023.00031, öffnet eine externe URL in einem neuen Fenster

Vardas, I., Hunold, S., Swartvagher, P., & Träff, J. L. (2023). Effects of Mapping Strategies on Average Duration and Throughput of Colocated HPC Applications. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 10–10). EuroCC Austria. https://doi.org/10.34726/5330, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2022). Brief Announcement: Fast(er) Construction of Round-optimal n-Block Broadcast Schedules. In K. Agrawal & I.-T. A. Lee (Eds.), Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2022) (pp. 143–146). ACM. https://doi.org/10.1145/3490148.3538560, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Hunold, S., & Przybylski, B. (2022, May 18). Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia. New Challenges in Scheduling Theory (Centre CNRS “Paul-Langevin”, Aussois, France), Aussois, France.

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.

Forsell, M., Nikula, S., Roivainen, J., Leppänen, V., & Träff, J. L. (2022). Performance and programmability comparison of the thick control flow architecture and current multicore processors. The Journal of Supercomputing, 78(3), 3152–3183. https://doi.org/10.1007/s11227-021-03985-0, öffnet eine externe URL in einem neuen Fenster

Hunold, S. (2022). Performance Tuning of MPI Collectives - Status Quo and Open Problems. CaSToRC HPC National Competence Center Fall Seminar Series 2022, Unknown.

Träff, J. L. (2022). (Poly)Logarithmic Time Construction of Round-optimal n-Block Broadcast Schedules for Broadcast and irregular Allgather in MPI (2205.10072). arXiv. https://doi.org/10.48550/arXiv.2205.10072, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2022). Fast(er) Construction of Round-optimal n-Block Broadcast Schedules. In Proceedings IEEE International Conference on Cluster Computing (CLUSTER 2022) (pp. 142–151). IEEE. https://doi.org/10.1109/CLUSTER51413.2022.00028, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

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.

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, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2021). A Doubly-pipelined, Dual-root Reduction-to-all Algorithm and Implementation (2109.12626). arXiv. https://doi.org/10.48550/arXiv.2109.12626, öffnet eine externe URL in einem neuen Fenster

Träff, J. L., & Pöter, M. (2021). A more pragmatic implementation of the lock-free, ordered, linked list. In J. Lee & E. Petrank (Eds.), Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. ACM. https://doi.org/10.1145/3437801.3441579, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Faraj, M. F., van der Grinten, A., Meyerhenke, H., Träff, J. L., & Schulz, C. (2020). High-Quality Hierarchical Process Mapping (2001.07134). arXiv. https://doi.org/10.48550/arXiv.2001.07134, öffnet eine externe URL in einem neuen Fenster

Faraj, M. F., van der Grinten, A., Meyerhenke, H., Träff, J. L., & Schulz, C. (2020). High-Quality Hierarchical Process Mapping. In S. Faro & D. Cantone (Eds.), 18th International Symposium on Experimental Algorithms, SEA 2020 (pp. 4:1-4:15). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SEA.2020.4, öffnet eine externe URL in einem neuen Fenster

Forsell, M., Roivainen, J., & Träff, J. L. (2020). Optimizing Memory Access in TCF Processors with Compute-Update Operations. In 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 22nd Workshop on Advances in Parallel and Distributed Computational Models (APDCM 2020) in conjunction with IPDPS 2020 - Online Conference, New Orleans, United States of America (the). IEEE. https://doi.org/10.1109/ipdpsw50202.2020.00100, öffnet eine externe URL in einem neuen Fenster

Hunold, S., & Przybylski, B. (2020). Scheduling.jl - Collaborative and Reproducible Scheduling Research with Julia. arXiv. https://doi.org/10.48550/arXiv.2003.05217, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Hunold, S., von Kirchbach, K., Lehr, M., Schulz, C., & Träff, J. L. (2020). Efficient Process-to-Node Mapping Algorithms for Stencil Computations (2005.09521). arXiv. https://doi.org/10.48550/arXiv.2005.09521, öffnet eine externe URL in einem neuen Fenster

Kirchbach, K. V., Schulz, C., & Träff, J. L. (2020). Better Process Mapping and Sparse Quadratic Assignment. ACM Journal on Experimental Algorithmics, 25, 1–19. https://doi.org/10.1145/3409667, öffnet eine externe URL in einem neuen Fenster

Lehr, M., & von Kirchbach, K. (2020). Improved Cartesian Topology Mapping in MPI. In A. Schlögl, J. Kiss, & S. Elefante (Eds.), Austrian High-Performance-Computing Meeting (AHPC 2020) (p. 27). IST Austria. https://doi.org/10.15479/AT:ISTA:7474, öffnet eine externe URL in einem neuen Fenster

Pachajoa, C., Levonyak, M., Pacher, C., Träff, J. L., & Gansterer, W. (2020). Classical and pipelined preconditioned conjugate gradient methods with node-failure resilience. In A. Schlögl, J. Kiss, & S. Elefante (Eds.), Austrian High-Performance-Computing Meeting (AHPC 2020) (p. 13). IST Austria. https://doi.org/10.15479/AT:ISTA:7474, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2020). Decomposing MPI Collectives for Exploiting Multi-lane Communication. SPCL_Bcast, ETH Zürich, Zürich, Switzerland.

Träff, J. L. (2020). k-ported vs. k-lane Broadcast, Scatter, and Alltoall Algorithms (2008.12144). arXiv. https://doi.org/10.48550/arXiv.2008.12144, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2020). Exploiting Multi-lane Communication in MPI Collectives. In A. Schlögl, J. Kiss, & S. Elefante (Eds.), Austrian High-Performance-Computing Meeting (AHPC 2020) (p. 30). IST Austria. https://doi.org/10.15479/AT:ISTA:7474, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2020). Signature Datatypes for Type Correct Collective Operations, Revisited. 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/10.1145/3416315.3416324, öffnet eine externe URL in einem neuen Fenster

Träff, J. L., & Hoefler, T. (2020). Special issue: Selected papers from EuroMPI 2019. Parallel Computing, 99, Article 102695. https://doi.org/10.1016/j.parco.2020.102695, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Träff, J. L., & Pöter, M. (2020). A more Pragmatic Implementation of the Lock-free, Ordered, Linked List. arXiv. https://doi.org/10.48550/arXiv.2010.15755, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2019). On Optimal Trees for Irregular Gather and Scatter Collectives. IEEE Transactions on Parallel and Distributed Systems, 30(9), 2060–2074. https://doi.org/10.1109/tpds.2019.2899843, öffnet eine externe URL in einem neuen Fenster

Hoefler, T., & Träff, J. L. (Eds.). (2019). Proceedings of the 26th European MPI Users’ Group Meeting, EuroMPI 2019. ACM.

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.

Kainer, M., & Träff, J. L. (2019). More Parallelism in Dijkstra’s Single-Source Shortest Path Algorithm (1903.12085). arXiv. https://doi.org/10.48550/arXiv.1903.12085, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Kang, Q., Träff, J. L., Al-Bahrani, R., Agrawal, A., Choudhary, A., & Liao, W. (2019). Scalable Algorithms for MPI Intergroup Allgather and Allgatherv. Parallel Computing: Systems & Applications, 85, 220–230. https://doi.org/10.1016/j.parco.2019.04.015, öffnet eine externe URL in einem neuen Fenster

Pachajoa, C., Levonyak, M., Gansterer, W. N., & Träff, J. L. (2019). How to Make the Preconditioned Conjugate Gradient Method Resilient Against Multiple Node Failures. In Proceedings of the 48th International Conference on Parallel Processing. 48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan. ACM. https://doi.org/10.1145/3337821.3337849, öffnet eine externe URL in einem neuen Fenster

Pachajoa, C., Levonyak, M., Gansterer, W., & Träff, J. L. (2019). How to Make the Preconditioned Conjugate Gradient Method Resilient Against Multiple Node Failures (1907.13077). arXiv. https://doi.org/10.48550/arXiv.1907.13077, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2019). Cartesian Collective Communication: “Advice to users”, “Advice to implementers”, and “Advice to Standardizers.” University of Bordeaux, Bordeaux, France.

Träff, J. L. (2019). Decomposing Collectives for Exploiting Multi-lane Communication (1910.13373). arXiv. https://doi.org/10.48550/arXiv.1910.13373, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2019). On Optimal Trees for Irregular Gather and Scatter Collectives. Kolloquium Mathematische Informatik, Goethe-Universität Frankfurt am Main, Frankfurt am Main, Germany.

Träff, J. L. (2019). On optimal Trees for irregular gather and scatter collectives? FernUniversität in Hagen, Prof. Dr. Jörg Keller, Hagen, Germany.

Träff, J. L. (2019). On optimal Trees for irregular gather and scatter collectives? Humboldt-Universität zu Berlin, Research Group on Modeling and Analysis of Complex Systems, Berlin, Germany.

Träff, J. L., & Hoefler, T. (2019). Foreword EuroMPI 2019. In T. Hoefler & J. L. Träff (Eds.), Proceedings of the 26th European MPI Users’ Group Meeting on  - EuroMPI ’19. ACM. https://doi.org/10.1145/3343211.3343212, öffnet eine externe URL in einem neuen Fenster

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, öffnet eine externe URL in einem neuen Fenster

Forsell, M., Roivainen, J., Leppänen, V., & Träff, J. L. (2018). Implementation of Multioperations in Thick Control Flow Processors. In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 20th Workshop on Advances in Parallel and Distributed Computational Models (APDCM 2018) in conjunction with IPDPS 2018, Vancouver, British Columbia, Canada, Non-EU. IEEE. https://doi.org/10.1109/ipdpsw.2018.00121, öffnet eine externe URL in einem neuen Fenster

Forsell, M., Roivainen, J., Leppänen, V., & Träff, J. L. (2018). Supporting concurrent memory access in TCF processor architectures. Microprocessors and Microsystems, 63, 226–236. https://doi.org/10.1016/j.micpro.2018.09.013, öffnet eine externe URL in einem neuen Fenster

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, Texas, USA, Non-EU. IEEE. https://doi.org/10.1109/pmbs.2018.8641622, öffnet eine externe URL in einem neuen Fenster

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, Non-EU. ACM. https://doi.org/10.1145/3149457.3149461, öffnet eine externe URL in einem neuen Fenster

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, EU. IEEE. https://doi.org/10.1109/cluster.2018.00050, öffnet eine externe URL in einem neuen Fenster

Kang, Q., Träff, J. L., Al-Bahrani, R., Agrawal, A., Choudhary, A., & Liao, W. (2018). Full-Duplex Inter-Group All-to-All Broadcast Algorithms with Optimal Bandwidth. In Proceedings of the 25th European MPI Users’ Group Meeting. 25th European MPI Users’ Group Meeting (EuroMPI 2018), Barcelona, Spain, EU. ACM. https://doi.org/10.1145/3236367.3236374, öffnet eine externe URL in einem neuen Fenster

Pöter, M., & Träff, J. L. (2018). Memory Models for C/C++ Programmers (1803.04432). arXiv. https://doi.org/10.48550/arXiv.1803.04432, öffnet eine externe URL in einem neuen Fenster

Pöter, M., & Träff, J. L. (2018). Stamp-it: A more Thread-efficient, Concurrent Memory Reclamation Scheme in the C++ Memory Model (1805.08639). arXiv. https://doi.org/10.48550/arXiv.1805.08639, öffnet eine externe URL in einem neuen Fenster

Pöter, M., & Träff, J. L. (2018). Stamp-it            , amortized constant-time memory reclamation in comparison to five other schemes. In Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. 23rd Symposium on Principles and Practice of Parallel Programming (PPoPP 2018), Vienna, Austria, Austria. ACM. https://doi.org/10.1145/3178487.3178532, öffnet eine externe URL in einem neuen Fenster

Pöter, M., & Träff, J. L. (2018). Brief Announcement. In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures. 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2018), Vienna, Austria, Austria. ACM. https://doi.org/10.1145/3210377.3210661, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2018). On Optimal trees for Irregular Gather and Scatter Collectives. Uppsala University, Uppsala, Sweden, EU.

Träff, J. L. (2018). Parallel Quicksort without Pairwise Element Exchange (1804.07494). arXiv. https://doi.org/10.48550/arXiv.1804.07494, öffnet eine externe URL in einem neuen Fenster

Träff, J. L. (2018). Practical, distributed, low overhead algorithms for irregular gather and scatter collectives. Parallel Computing: Systems & Applications, 75, 100–117. https://doi.org/10.1016/j.parco.2018.04.003, öffnet eine externe URL in einem neuen Fenster