Efficient sparse-matrix multi-vector product on gpus C Hong, A Sukumaran-Rajam, B Bandyopadhyay, J Kim, SE Kurt, I Nisa, ... Proceedings of the 27th International Symposium on High-Performance Parallel …, 2018 | 78* | 2018 |
Sampled dense matrix multiplication for high-performance machine learning I Nisa, A Sukumaran-Rajam, SE Kurt, C Hong, P Sadayappan 2018 IEEE 25th International Conference on High Performance Computing (HiPC …, 2018 | 40 | 2018 |
Efficient tiled sparse matrix multiplication through matrix signatures SE Kurt, A Sukumaran-Rajam, F Rastello, P Sadayyapan SC20: International Conference for High Performance Computing, Networking …, 2020 | 23 | 2020 |
Characterization of data movement requirements for sparse matrix computations on GPUs SE Kurt, V Thumma, C Hong, A Sukumaran-Rajam, P Sadayappan High Performance Computing (HiPC), 2017 IEEE 24th International Conference …, 2017 | 12 | 2017 |
Sparsity-aware tensor decomposition SE Kurt, S Raje, A Sukumaran-Rajam, P Sadayappan 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022 | 6 | 2022 |
Communication Optimization for Distributed Execution of Graph Neural Networks SE Kurt, J Yan, A Sukumaran-Rajam, P Pandey, P Sadayappan 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2023 | 2 | 2023 |
BOA: A Partitioned View of Genome Assembly P Ghosh, X An, P Keppler, SE Kurt, ÜV Çatalyürek, S Krishnamoorthy, ... bioRxiv, 2022.05. 22.492973, 2022 | 1 | 2022 |
BOA: A partitioned view of genome assembly X An, P Ghosh, P Keppler, SE Kurt, S Krishnamoorthy, P Sadayappan, ... Iscience 25 (11), 2022 | | 2022 |
Modeling Data Movement for Sparse Matrix and Tensor Computations SE Kurt The University of Utah, 2022 | | 2022 |
Finding hidden hierarchy in social networks SE Kurt PQDT-Global, 2016 | | 2016 |