OPTQ: Accurate quantization for generative pre-trained transformers E Frantar, S Ashkboos, T Hoefler, D Alistarh The Eleventh International Conference on Learning Representations, 2022 | 141* | 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 | 128 | 2019 |
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 | 31 | 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 | 27* | 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 | 21 | 2022 |
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 | 17 | 2023 |
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 | 12 | 2022 |
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 | 5 | 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 |
Torsten Hoe er. 2019. Sparcml: High-performance sparse communication for machine learning C Renggli, S Ashkboos, M Aghagolzadeh, D Alistarh Proceedings of the International Conference for High Performance Computing …, 0 | 3 | |
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 | 2 | 2022 |
An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees R Javadi, S Ashkboos arXiv preprint arXiv:1702.04739, 2017 | 2 | 2017 |
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 | 1 | 2023 |
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 |
Minimum cuts of distance-regular digraphs S Ashkboos, G Omidi, F Shafiei, K Tajbakhsh the electronic journal of combinatorics, P4. 2-P4. 2, 2017 | 1 | 2017 |
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 |