| Futhark: purely functional GPU-programming with nested parallelism and in-place array updates T Henriksen, NGW Serup, M Elsman, F Henglein, CE Oancea Proceedings of the 38th ACM SIGPLAN Conference on Programming Language …, 2017 | 209 | 2017 |
| Incremental flattening for nested data parallelism T Henriksen, F Thorøe, M Elsman, C Oancea Proceedings of the 24th Symposium on Principles and Practice of Parallel …, 2019 | 44 | 2019 |
| Design and implementation of the Futhark programming language T Henriksen University of Copenhagen, Faculty of Science [Department of Computer Science], 2017 | 38* | 2017 |
| Size slicing: a hybrid approach to size inference in Futhark T Henriksen, M Elsman, CE Oancea Proceedings of the 3rd ACM SIGPLAN workshop on Functional high-performance …, 2014 | 35 | 2014 |
| Finpar: A parallel financial benchmark C Andreetta, V Bégot, J Berthold, M Elsman, F Henglein, T Henriksen, ... ACM Transactions on Architecture and Code Optimization (TACO) 13 (2), 1-27, 2016 | 34 | 2016 |
| A T2 graph-reduction approach to fusion T Henriksen, CE Oancea Proceedings of the 2nd ACM SIGPLAN workshop on Functional high-performance …, 2013 | 34 | 2013 |
| Static interpretation of higher-order modules in Futhark: Functional GPU programming in the large M Elsman, T Henriksen, D Annenkov, CE Oancea Proceedings of the ACM on Programming Languages 2 (ICFP), 1-30, 2018 | 29 | 2018 |
| APL on GPUs: A TAIL from the Past, Scribbled in Futhark T Henriksen, M Dybdal, H Urms, AS Kiehn, D Gavin, H Abelskov, ... Proceedings of the 5th International Workshop on Functional High-Performance …, 2016 | 25 | 2016 |
| Design and GPGPU performance of Futhark's redomap construct T Henriksen, KF Larsen, CE Oancea Proceedings of the 3rd ACM SIGPLAN International Workshop on Libraries …, 2016 | 25 | 2016 |
| Compiling generalized histograms for gpu T Henriksen, S Hellfritzsch, P Sadayappan, C Oancea SC20: International Conference for High Performance Computing, Networking …, 2020 | 24 | 2020 |
| Bounds checking: An instance of hybrid analysis T Henriksen, CE Oancea Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages …, 2014 | 24 | 2014 |
| Strategies for regular segmented reductions on gpu RW Larsen, T Henriksen Proceedings of the 6th ACM SIGPLAN International Workshop on Functional High …, 2017 | 23 | 2017 |
| Massively-parallel change detection for satellite time series data with missing values F Gieseke, S Rosca, T Henriksen, J Verbesselt, CE Oancea 2020 IEEE 36th International Conference on Data Engineering (ICDE), 385-396, 2020 | 19 | 2020 |
| High-Performance Defunctionalisation in Futhark AK Hovgaard, T Henriksen, M Elsman International Symposium on Trends in Functional Programming, 136-156, 2018 | 17 | 2018 |
| Modular acceleration: tricky cases of functional high-performance computing T Henriksen, M Elsman, CE Oancea Proceedings of the 7th ACM SIGPLAN International Workshop on Functional High …, 2018 | 15 | 2018 |
| Data-parallel flattening by expansion M Elsman, T Henriksen, NGW Serup Proceedings of the 6th ACM SIGPLAN International Workshop on Libraries …, 2019 | 13 | 2019 |
| Towards size-dependent types for array programming T Henriksen, M Elsman Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries …, 2021 | 11 | 2021 |
| Parallel programming in Futhark M Elsman, T Henriksen, CE Oancea DIKU, November, 2018 | 11 | 2018 |
| Ad for an array language with nested parallelism R Schenck, O Rϕnning, T Henriksen, CE Oancea SC22: International Conference for High Performance Computing, Networking …, 2022 | 8 | 2022 |
| Exploiting functional invariants to optimise parallelism: a dataflow approach T Henriksen Master's thesis, DIKU, Denmark, 2014 | 7 | 2014 |
Cosmin OanceaDepartment of Computer Science (DIKU), University of CopenhagenVerified email at diku.edu
