Publications
| Title | Authors | Date | Link | Citation |
|---|---|---|---|---|
| Characterizing Deep-Learning I/O Workloads in TensorFlow | Steven W. D. Chien, Stefano Markidis, Chaitanya Prasad Sishtla, Luis Santos, Pawel Herman, Sai Narasimhamurthy, Erwin Laure | 6/10/2018 | DOI: 10.1109/PDSW-DISCS.2018.00011 | Chien, S. W., Markidis, S., Sishtla, C. P., Santos, L., Herman, P., Narasimhamurthy, S., & Laure, E. (2018, November). Characterizing deep-learning I/O workloads in TensorFlow. In 2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS) (pp. 54-63). IEEE. |
| TensorFlow Doing HPC | Steven W. D. Chien, Stefano Markidis, Vyacheslav Olshevsky, Yaroslav Bulatov, Erwin Laure, Jeffrey S. Vetter | 11/03/2019 | DOI: 10.1109/IPDPSW.2019.00092 | Chien, S. W., Markidis, S., Olshevsky, V., Bulatov, Y., Laure, E., & Vetter, J. (2019, May). TensorFlow doing HPC. In 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 509-518). IEEE. |
| Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code | Chaitanya Prasad Sishtla, Steven W. D. Chien, Vyacheslav Olshevsky, Erwin Laure, Stefano Markidis | 7/05/2019 | DOI: 10.1007/978-3-030-22750-0_58 | Sishtla, C. P., Chien, S. W., Olshevsky, V., Laure, E., & Markidis, S. (2019, June). Multi-GPU acceleration of the iPIC3D implicit particle-in-cell code. In International Conference on Computational Science (pp. 612-618). Springer, Cham. |
| Posit NPB: Assessing the Precision Improvement in HPC Scientific Applications | Steven W. D. Chien, Ivy B. Peng, Stefano Markidis | 12/07/2019 | DOI: 10.1007/978-3-030-43229-4_26 | Chien, S. W., Peng, I. B., & Markidis, S. (2019, September). Posit NPB: Assessing the precision improvement in HPC scientific applications. In International Conference on Parallel Processing and Applied Mathematics (pp. 301-310). Springer, Cham. |
| Automated classification of plasma regions using 3D particle energy distribution | Vyacheslav Olshevsky, Yuri V. Khotyaintsev, Andrey Divin, Gian Luca Delzanno, Sven Anderzen, Pawel Herman, Steven W.D. Chien, Levon Avanov, Stefano Markidis | 15/08/2019 | https://arxiv.org/abs/1908.05715 | Olshevsky, V., Khotyaintsev, Y. V., Lalti, A., Divin, A., Delzanno, G. L., Anderzén, S., ... & Markidis, S. (2021). Automated classification of plasma regions using 3D particle energy distributions. Journal of Geophysical Research: Space Physics, 126(10), e2021JA029620. |
| Exposition, Clarification, and Expansion of MPI Semantic Terms and Conventions | Purushotham V. Bangalore, Rolf Rabenseifner, Daniel J. Holmes, Julien Jaeger, Guillaume Mercier, Claudia Blaas-Schenner, Anthony Skjellum | 11/09/2019 | DOI: 10.1145/3343211.3343213 | Bangalore, P. V., Rabenseifner, R., Holmes, D. J., Jaeger, J., Mercier, G., Blaas-Schenner, C., & Skjellum, A. (2019, September). Exposition, clarification, and expansion of MPI semantic terms and conventions: is a nonblocking MPI function permitted to block?. In Proceedings of the 26th European MPI Users' Group Meeting (pp. 1-10). |
| MPI Sessions: Evaluation of an Implementation in Open MPI | Nathan Hjelm, Howard Pritchard, Samuel Guitiérrez, Daniel Holmes, Ralph Castain, Anthony Skjellum | 8/10/2019 | DOI: 10.1109/CLUSTER.2019.8891002 | Hjelm, N., Pritchard, H., Gutiérrez, S. K., Holmes, D. J., Castain, R., & Skjellum, A. (2019, September). MPI sessions: Evaluation of an implementation in open MPI. In 2019 IEEE International Conference on Cluster Computing (CLUSTER) (pp. 1-11). IEEE. |
| Performance Evaluation of Advanced Features in CUDA Unified Memory. | Steven W. D. Chien, Ivy Peng, & Stefano Markidis | 21/10/2019 | DOI: 10.1109/MCHPC49590.2019.00014 | Chien, S., Peng, I., & Markidis, S. (2019, November). Performance evaluation of advanced features in CUDA unified memory. In 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC) (pp. 50-57). IEEE. |
| Streaming Message Interface: High-performance distributed memory programming on reconfigurable hardware. | De Matteis, T., de Fine Licht, J., Beránek, J., & Hoefler, T. | 17/11/2019 | DOI: 10.1145/3295500.3356201 | De Matteis, T., de Fine Licht, J., Beránek, J., & Hoefler, T. (2019, November). Streaming Message Interface: High-performance distributed memory programming on reconfigurable hardware. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-33). |
| Data Movement Is All You Need: A Case Study on Optimizing Transformers | Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler | 30/6/2020 | DOI: Preprint | Ivanov, A., Dryden, N., Ben-Nun, T., Li, S., & Hoefler, T. (2021). Data movement is all you need: A case study on optimizing transformers. Proceedings of Machine Learning and Systems, 3, 711-732. |
| Why is MPI (perceived to be) so complex?: Part 1—Does strong progress simplify MPI? | Daniel J. Holmes, Anthony Skjellum, Derek Schafer | 21/9/2020 | DOI: 10.1145/3416315.3416318 | Holmes, D. J., Skjellum, A., & Schafer, D. (2020, September). Why is MPI (perceived to be) so complex? Part 1—Does strong progress simplify MPI?. In 27th European MPI Users' Group Meeting (pp. 21-30). |
| Communication and Timing Issues with MPI Virtualization | Alexandr Nigay, Lukas Mosimann, Timo Schneider, Torsten Hoefler | 21/9/2020 | DOI: 10.1145/3416315.3416317 | Nigay, A., Mosimann, L., Schneider, T., & Hoefler, T. (2020, September). Communication and Timing Issues with MPI Virtualization. In 27th European MPI Users' Group Meeting (pp. 11-20). |
| Neko: A Modern, Portable, and Scalable Framework for High-Fidelity Computational Fluid Dynamics | Niclas Jansson, Martin Karp, Artur Podobas, Stefano Markidis, Philipp Schlatter | 21/9/2020 | DOI: Preprint | Jansson, N., Karp, M., Podobas, A., Markidis, S., & Schlatter, P. (2021). Neko: A modern, portable, and scalable framework for high-fidelity computational fluid dynamics. arXiv preprint arXiv:2107.01243. |
| Collectives and Communicators: A Case for Orthogonality: (Or: How to get rid of MPI neighbor and enhance Cartesian collectives) | Jesper Larsson Träff, Sascha Hunold, Guillaume Mercier, Daniel J. Holmes | 21/9/2020 | DOI: 10.1145/3416315.3416319 | Träff, J. L., Hunold, S., Mercier, G., & Holmes, D. J. (2020, September). Collectives and Communicators: A Case for Orthogonality: (Or: How to get rid of MPI neighbor and enhance Cartesian collectives). In 27th European MPI Users' Group Meeting (pp. 31-38). |
| Learning representations in Bayesian Confidence Propagation neural networks | Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman | 28/9/2020 | DOI: 10.1109/IJCNN48605.2020.9207061 | Ravichandran, N. B., Lansner, A., & Herman, P. (2020, July). Learning representations in Bayesian Confidence Propagation neural networks. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE. |
| sputniPIC: an Implicit Particle-in-Cell Code for Multi-GPU Systems | Steven W. D. Chien, Jonas Nylund, Gabriel Bengtsson, Ivy B. Peng, Artur Podobas, Stefano Markidis | 22/10/2020 | DOI: 10.1109/SBAC-PAD49847.2020.00030 | Chien, S. W., Nylund, J., Bengtsson, G., Peng, I. B., Podobas, A., & Markidis, S. (2020, September). sputnipic: An implicit particle-in-cell code for multi-gpu systems. In 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) (pp. 149-156). IEEE. |
| Spectral Element Simulations on the NEC SX-Aurora TSUBASA | Niclas Jansson | 20/1/2021 | DOI: 10.1145/3432261.3432265 | Jansson, N. (2021, January). Spectral Element Simulations on the NEC SX-Aurora TSUBASA. In The International Conference on High Performance Computing in Asia-Pacific Region (pp. 32-39). |
| On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal Matrix Factorizations | G. Kwasniewski, M. Kabić, T. Ben-Nun, A. Nikolaos Ziogas, J. Eirik Saethre, A. Gaillard, T. Schneider, M. Besta, A. Kozhevnikov, J. VandeVondele, T. Hoefler | 17/02/2021 | DOI: 10.1145/3458817.3476167 | Kwasniewski, G., Kabic, M., Ben-Nun, T., Ziogas, A. N., Saethre, J. E., Gaillard, A., ... & Hoefler, T. (2021, November). On the parallel I/O optimality of linear algebra kernels: near-optimal matrix factorizations. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-15). |
| FBLAS: Streaming Linear Algebra on FPGA | Tiziano De Matteis, Johannes de Fine Licht, Torsten Hoefler | 22/2/2021 | DOI: 10.1109/SC41405.2020.00063 | De Matteis, T., de Fine Licht, J., & Hoefler, T. (2020, November). FBLAS: Streaming linear algebra on FPGA. In SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-13). IEEE. |
| The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? | Stefano Markidis | 12/3/2021 | DOI: Preprint | Markidis, S. (2021). The old and the new: Can physics-informed deep-learning replace traditional linear solvers?. Frontiers in big Data, 92. |
| Automatic Particle Trajectory Classification in Plasma Simulations | Stefano Markidis, Ivy Peng, Artur Podobas, Itthinat Jongsuebchoke, Gabriel Bengtsson, Pawel Herman | 23/4/2021 | DOI: 10.1109/MLHPCAI4S51975.2020.00014 | Markidis, S., Peng, I., Podobas, A., Jongsuebchoke, I., Bengtsson, G., & Herman, P. (2020, November). Automatic particle trajectory classification in plasma simulations. In 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S) (pp. 64-71). IEEE. |
| RISC-V in-network accelerator for flexible high-performance low-power packet processing | S. Di Girolamo, A. Kurth, A. Calotoiu, T. Benz, T. Schneider, J. Beránek, L. Benini, T. Hoefler | 14/06/2021 | DOI: 10.1109/ISCA52012.2021.00079 | Di Girolamo, S., Kurth, A., Calotoiu, A., Benz, T., Schneider, T., Beránek, J., ... & Hoefler, T. (2021, June). A RISC-V in-network accelerator for flexible high-performance low-power packet processing. In 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA) (pp. 958-971). IEEE. |
| Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers | Martin Svedin, Steven W. D. Chien, Gibson Chikafa, Niclas Jansson, Artur Podobas | 21/6/2021 | DOI: 10.1145/3468044.3468053 | Svedin, M., Chien, S. W., Chikafa, G., Jansson, N., & Podobas, A. (2021, June). Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers. In Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (pp. 1-6). |
| StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs | Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis | 21/6/2021 | DOI: 10.1145/3468044.3468052 | Podobas, A., Svedin, M., Chien, S. W., Peng, I. B., Ravichandran, N. B., Herman, P., ... & Markidis, S. (2021, June). Streambrain: an hpc framework for brain-like neural networks on cpus, gpus and fpgas. In Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (pp. 1-6). |
| RFaaS: RDMA-Enabled FaaS Platform for Serverless High-Performance Computing | Marcin Copik, Konstantin Taranov, Alexandru Calotoiu, Torsten Hoefler | 25/6/2021 | DOI: Preprint | Copik, M., Taranov, K., Calotoiu, A., & Hoefler, T. (2021). rFaaS: RDMA-Enabled FaaS Platform for Serverless High-Performance Computing. arXiv preprint arXiv:2106.13859. |
| Semi-supervised learning with Bayesian Confidence Propagation Neural Network | Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman | 29/6/2021 | DOI: Preprint | Ravichandran, N. B., Lansner, A., & Herman, P. (2021). Semi-supervised learning with bayesian confidence propagation neural network. arXiv preprint arXiv:2106.15546. |
| Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines | Shigang Li, Torsten Hoefler | 14/07/2021 | https://arxiv.org/abs/2107.06925 | Li, S., & Hoefler, T. (2021, November). Chimera: efficiently training large-scale neural networks with bidirectional pipelines. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-14). |
| MPI collective communication through a single set of interfaces: A case for orthogonality | Jesper Larsson, Träffa Sasch, Hunold Guillaume, Mercier, Daniel J.Holmes | 13/8/2021 | DOI: 10.1016/j.parco.2021.102826 | 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, 107, 102826. |
| A Deep Learning-Based Particle-in-Cell Method for Plasma Simulations | Xavier Aguilar, Stefano Markidis | 13/10/2021 | DOI: 10.1109/Cluster48925.2021.00103 | Aguilar, X., & Markidis, S. (2021, September). A Deep Learning-Based Particle-in-Cell Method for Plasma Simulations. In 2021 IEEE International Conference on Cluster Computing (CLUSTER) (pp. 692-697). IEEE. |
| Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain | Martin Svedin, Artur Podobas, Steven W. D. Chien, Stefano Markidis | 13/10/2021 | DOI: 10.1109/Cluster48925.2021.00105 | Svedin, M., Podobas, A., Chien, S. W., & Markidis, S. (2021, September). Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain. In 2021 IEEE International Conference on Cluster Computing (CLUSTER) (pp. 705-710). IEEE. |
| A Data-Centric Optimization Framework for Machine Learning | Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler | 20/10/2021 | DOI: Preprint | Rausch, O., Ben-Nun, T., Dryden, N., Ivanov, A., Li, S., & Hoefler, T. (2021). A Data-Centric Optimization Framework for Machine Learning. arXiv preprint arXiv:2110.10802. |
| Flare: Flexible In-Network Allreduce In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis | D. De Sensi, S. Di Girolamo, S. Ashkboos, S. Li, T. Hoefler | 14/11/ 2021 | DOI: 10.1145/3458817.3476178 | De Sensi, D., Di Girolamo, S., Ashkboos, S., Li, S., & Hoefler, T. (2021, November). Flare: flexible in-network allreduce. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-16). |
| Brain-Like Approaches to Unsupervised Learning of Hidden Representations - A Comparative Study | Ravichandran N.B., Lansner A., Herman P. | 07/09/2021 | DOI: 10.1007/978-3-030-86383-8_13 | Ravichandran, N. B., Lansner, A., & Herman, P. (2021, September). Brain-like approaches to unsupervised learning of hidden representations-a comparative study. In International Conference on Artificial Neural Networks (pp. 162-173). Springer, Cham. |
| Data Movement Is All You Need: A Case Study on Optimizing Transformers | Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler | 08/11/2021 | DOI: Preprint | Ivanov, A., Dryden, N., Ben-Nun, T., Li, S., & Hoefler, T. (2021). Data movement is all you need: A case study on optimizing transformers. Proceedings of Machine Learning and Systems, 3, 711-732. |
| Mamba: Portable Array-based Abstractions for Heterogeneous High-Performance Systems | Dykes, T., Foyer, C., Richardson, H., Svedin, M., Podobas, A., Jansson, N., Markidis, S., Tate, A., McIntosh-Smith, S | 14/11/2021 | DOI: 10.1109/P3HPC54578.2021.00005 | Dykes, T., Foyer, C., Richardson, H., Svedin, M., Podobas, A., Jansson, N., ... & McIntosh-Smith, S. (2021, November). Mamba: Portable Array-based Abstractions for Heterogeneous High-Performance Systems. In 2021 International Workshop on Performance, Portability and Productivity in HPC (P3HPC) (pp. 10-21). IEEE. |
Posters
| Title | Authors | Date - Event | Link |
|---|---|---|---|
| Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code | Chaitanya Prasad Sishtla, Steven W. D. Chien, Vyacheslav Olshevsky, Erwin Laure, Stefano Markidis | 12/06/2019 - ICCS 2019 | Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code |
| User-level schedules | Derek Schafer, Martin Ruefenacht, Anthony Skjellum, Daniel Holmes | 11/09/2019 - EuroMPI 2019 | User-level schedules |
| MPI Semantic Terms and Conventions Explained | Claudia Blaas-Schenner, Daniel Holmes, Rolf Rabenseifner, Anthony Skjellum, Guillaume Mercier, Julien Jaeger, Purushotham V. Bangalore | 11/09/2019 - EuroMPI 2019 | MPI Semantic Terms and Conventions Explained |