Self-tuning, gpu-accelerated kernel density models for multidimensional selectivity estimation M Heimel, M Kiefer, V Markl Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 120 | 2015 |
Estimating join selectivities using bandwidth-optimized kernel density models M Kiefer, M Heimel, S Breß, V Markl Proceedings of the VLDB Endowment 10 (13), 2085-2096, 2017 | 91 | 2017 |
Scotch: Generating fpga-accelerators for sketching at line rate M Kiefer, I Poulakis, S Breß, V Markl Proceedings of the VLDB Endowment 14 (3), 281-293, 2020 | 16 | 2020 |
Optimistic data parallelism for fpga-accelerated sketching M Kiefer, I Poulakis, ET Zacharatou, V Markl Proceedings of the VLDB Endowment 16 (5), 1113-1125, 2023 | 13 | 2023 |
In the land of data streams where synopses are missing, one framework to bring them all R Poepsel-Lemaitre, M Kiefer, J Von Hein, JA Quiané-Ruiz, V Markl Proceedings of the VLDB Endowment 14 (10), 1818-1831, 2021 | 12 | 2021 |
Demonstrating transfer-efficient sample maintenance on graphics cards M Kiefer, M Heimel, V Markl Proceedings of the 18th International Conference on Extending Database …, 2015 | 3 | 2015 |
Accelerating approximate data analysis with parallel processors M Kiefer Technische Universität Berlin, 2023 | | 2023 |
Investigating GPU-Accelerated Kernel Density Estimators for Join Selectivity Estimation M Kiefer | | 2016 |