| Automated instruction stream throughput prediction for intel and amd microarchitectures J Laukemann, J Hammer, J Hofmann, G Hager, G Wellein 2018 IEEE/ACM performance modeling, benchmarking and simulation of high …, 2018 | 35 | 2018 |
| Execution‐Cache‐Memory modeling and performance tuning of sparse matrix‐vector multiplication and Lattice quantum chromodynamics on A64FX C Alappat, N Meyer, J Laukemann, T Gruber, G Hager, G Wellein, ... Concurrency and Computation: Practice and Experience 34 (20), e6512, 2022 | 28 | 2022 |
| Alto: Adaptive linearized storage of sparse tensors AE Helal, J Laukemann, F Checconi, JJ Tithi, T Ranadive, F Petrini, ... Proceedings of the ACM International Conference on Supercomputing, 404-416, 2021 | 27 | 2021 |
| Automatic throughput and critical path analysis of x86 and arm assembly kernels J Laukemann, J Hammer, G Hager, G Wellein 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High …, 2019 | 25 | 2019 |
| Performance modeling of streaming kernels and sparse matrix-vector multiplication on A64FX C Alappat, J Laukemann, T Gruber, G Hager, G Wellein, N Meyer, ... 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High …, 2020 | 19 | 2020 |
| Automated instruction stream throughput prediction for intel and amd microarchitectures. In 2018 IEEE/ACM performance modeling, benchmarking and simulation of high performance … J Laukemann, J Hammer, J Hofmann, G Hager, G Wellein IEEE, 121¶131, 2018 | 19 | 2018 |
| Efficient, out-of-memory sparse MTTKRP on massively parallel architectures A Nguyen, AE Helal, F Checconi, J Laukemann, JJ Tithi, Y Soh, ... Proceedings of the 36th ACM International Conference on Supercomputing, 1-13, 2022 | 8 | 2022 |
| Design and Implementation of a Framework for Predicting Instruction Throughput J Laukemann | 2 | 2017 |
| Dynamic Tensor Linearization and Time Slicing for Efficient Factorization of Infinite Data Streams Y Soh, AE Helal, F Checconi, J Laukemann, JJ Tithi, T Ranadive, F Petrini, ... 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2023 | 1 | 2023 |
| Core-level performance engineering with the open-source architecture code analyzer (osaca) and the compiler explorer J Laukemann, G Hager Companion of the 2023 ACM/SPEC International Conference on Performance …, 2023 | 1 | 2023 |
| Cross-Architecture Automatic Critical Path Detection For In-Core Performance Analysis J Laukemann Friedrich-Alexander-Universität Erlangen-Nürnberg, 2020 | 1 | 2020 |
| Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation J Laukemann, AE Helal, S Anderson, F Checconi, Y Soh, JJ Tithi, ... arXiv preprint arXiv:2403.06348, 2024 | | 2024 |
| MD-Bench: A performance-focused prototyping harness for state-of-the-art short-range molecular dynamics algorithms RRL Machado, J Eitzinger, J Laukemann, G Hager, H Köstler, G Wellein Future Generation Computer Systems 149, 25-38, 2023 | | 2023 |
| CloverLeaf on Intel Multi-Core CPUs: A Case Study in Write-Allocate Evasion J Laukemann, T Gruber, G Hager, D Oryspayev, G Wellein arXiv preprint arXiv:2311.04797, 2023 | | 2023 |
| MD-Bench: Engineering the in-core performance of short-range molecular dynamics kernels from state-of-the-art simulation packages RRL Machado, J Eitzinger, J Laukemann, G Hager, H Köstler, G Wellein arXiv preprint arXiv:2302.14660, 2023 | | 2023 |
| MD-Bench: Engineering the in-core performance of short-range molecular dynamics kernels from state-of-the-art simulation packages R Ravedutti Lucio Machado, J Eitzinger, J Laukemann, G Hager, ... arXiv e-prints, arXiv: 2302.14660, 2023 | | 2023 |
| Reproducibility report: Team SegFAUlt@ SCC 2016 A Ditter, J Laukemann, B Oehlrich Parallel Computing 70, 41-45, 2017 | | 2017 |
| PMBS 2019 J Laukemann, J Hammer, G Hager, N Ding, S Williams, J Salmon, ... | | |
Georg HagerFriedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
