| OPTQ: Accurate quantization for generative pre-trained transformers E Frantar, S Ashkboos, T Hoefler, D Alistarh The Eleventh International Conference on Learning Representations, 2022 | 352* | 2022 |
| SparCML: High-performance sparse communication for machine learning C Renggli, S Ashkboos, M Aghagolzadeh, D Alistarh, T Hoefler Proceedings of the International Conference for High Performance Computing …, 2019 | 131 | 2019 |
| Spqr: A sparse-quantized representation for near-lossless llm weight compression T Dettmers, R Svirschevski, V Egiazarian, D Kuznedelev, E Frantar, ... arXiv preprint arXiv:2306.03078, 2023 | 62 | 2023 |
| Flare: Flexible in-network allreduce D De Sensi, S Di Girolamo, S Ashkboos, S Li, T Hoefler Proceedings of the International Conference for High Performance Computing …, 2021 | 34 | 2021 |
| New bounds for distributed mean estimation and variance reduction P Davies, V Gurunathan, N Moshrefi, S Ashkboos, D Alistarh arXiv preprint arXiv:2002.09268, 2020 | 30* | 2020 |
| Motif prediction with graph neural networks M Besta, R Grob, C Miglioli, N Bernold, G Kwasniewski, G Gjini, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 27 | 2022 |
| Ens-10: A dataset for post-processing ensemble weather forecasts S Ashkboos, L Huang, N Dryden, T Ben-Nun, P Dueben, L Gianinazzi, ... Advances in Neural Information Processing Systems 35, 21974-21987, 2022 | 17 | 2022 |
| Slicegpt: Compress large language models by deleting rows and columns S Ashkboos, ML Croci, MG Nascimento, T Hoefler, J Hensman arXiv preprint arXiv:2401.15024, 2024 | 14 | 2024 |
| Probgraph: High-performance and high-accuracy graph mining with probabilistic set representations M Besta, C Miglioli, PS Labini, J Tětek, P Iff, R Kanakagiri, S Ashkboos, ... SC22: International Conference for High Performance Computing, Networking …, 2022 | 7 | 2022 |
| Towards end-to-end 4-bit inference on generative large language models S Ashkboos, I Markov, E Frantar, T Zhong, X Wang, J Ren, T Hoefler, ... arXiv preprint arXiv:2310.09259, 2023 | 6 | 2023 |
| The spatial computer: A model for energy-efficient parallel computation L Gianinazzi, T Ben-Nun, M Besta, S Ashkboos, Y Baumann, P Luczynski, ... arXiv preprint arXiv:2205.04934, 2022 | 4 | 2022 |
| Multi-way sparsest cut problem on trees with a control on the number of parts and outliers R Javadi, S Ashkboos Discrete Applied Mathematics 289, 281-291, 2021 | 3* | 2021 |
| Minimum cuts of distance-regular digraphs S Ashkboos, G Omidi, F Shafiei, K Tajbakhsh the electronic journal of combinatorics, P4. 2-P4. 2, 2017 | 2 | 2017 |
| An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees R Javadi, S Ashkboos arXiv preprint arXiv:1702.04739, 2017 | 2 | 2017 |
| Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication L Gianinazzi, AN Ziogas, L Huang, P Luczynski, S Ashkboosh, F Scheidl, ... Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and …, 2024 | 1 | 2024 |
| STen: Productive and Efficient Sparsity in PyTorch A Ivanov, N Dryden, T Ben-Nun, S Ashkboos, T Hoefler arXiv preprint arXiv:2304.07613, 2023 | 1 | 2023 |
| QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs S Ashkboos, A Mohtashami, ML Croci, B Li, M Jaggi, D Alistarh, T Hoefler, ... arXiv preprint arXiv:2404.00456, 2024 | | 2024 |
| Report on software performance benchmarking for ML solutions from deliverable D1. 3 N Dryden, T Ben-Nun, S Ashkboos, F Emmerich, J Jauch | | 2022 |
| First version of workflow tools published that allows to perform quarterly benchmarks of ML solutions M Abel, S Ashkboos, T Ben-Nun, M Chantry, G Denisenko, F Emmerich | | 2022 |
Torsten HoeflerProfessor of Computer Science at ETH ZurichVerified email at inf.ethz.ch
