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Krzysztof Rojek
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2020 – today
- 2024
- [j14]Kamil Halbiniak
, Norbert Meyer, Krzysztof Rojek
Single- and multi-GPU computing on NVIDIA- and AMD-based server platforms for solidification modeling application. Concurr. Comput. Pract. Exp. 36(9) (2024) - [c12]Kamil Halbiniak
Unleashing the Potential of Mixed Precision in AI-Accelerated CFD Simulation on Intel CPU/GPU Architectures. ICCS (6) 2024: 203-217 - 2023
- [j13]Pawel Rosciszewski, Adam Krzywaniak, Sergio Iserte
Optimizing throughput of Seq2Seq model training on the IPU platform for AI-accelerated CFD simulations. Future Gener. Comput. Syst. 147: 149-162 (2023) - [j12]Sergio Iserte
A study on the performance of distributed training of data-driven CFD simulations. Int. J. High Perform. Comput. Appl. 37(5): 503-515 (2023) - [c11]Krzysztof Rojek
Chemical Mixing Simulations with Integrated AI Accelerator. ICCS (2) 2023: 494-508 - 2022
- [c10]Krzysztof Rojek
Performance and Scalability Analysis of AI-Accelerated CFD Simulations Across Various Computing Platforms. Euro-Par Workshops 2022: 223-234 - [c9]Pawel Rosciszewski, Adam Krzywaniak, Sergio Iserte, Krzysztof Rojek, Pawel Gepner
Adaptation of AI-Accelerated CFD Simulations to the IPU Platform. PPAM (2) 2022: 223-235 - 2021
- [j11]Krzysztof Rojek
CFD code adaptation to the FPGA architecture. Int. J. High Perform. Comput. Appl. 35(1) (2021) - [c8]Krzysztof Rojek
AI-Accelerated CFD Simulation Based on OpenFOAM and CPU/GPU Computing. ICCS (2) 2021: 373-385 - 2020
- [j10]Sergio Iserte
An study of the effect of process malleability in the energy efficiency on GPU-based clusters. J. Supercomput. 76(1): 255-274 (2020)
2010 – 2019
- 2019
- [j9]Krzysztof Rojek
Machine learning method for energy reduction by utilizing dynamic mixed precision on GPU-based supercomputers. Concurr. Comput. Pract. Exp. 31(6) (2019) - 2017
- [j8]Krzysztof Rojek
Energy-aware mechanism for stencil-based MPDATA algorithm with constraints. Concurr. Comput. Pract. Exp. 29(8) (2017) - [j7]Krzysztof Rojek
Systematic adaptation of stencil-based 3D MPDATA to GPU architectures. Concurr. Comput. Pract. Exp. 29(9) (2017) - [j6]Krzysztof Rojek
Performance modeling of 3D MPDATA simulations on GPU cluster. J. Supercomput. 73(2): 664-675 (2017) - [j5]Krzysztof Rojek
Modeling power consumption of 3D MPDATA and the CG method on ARM and Intel multicore architectures. J. Supercomput. 73(10): 4373-4389 (2017) - 2015
- [j4]Krzysztof Andrzej Rojek, Milosz Ciznicki, Bogdan Rosa, Piotr Kopta, Michal Kulczewski, Krzysztof Kurowski, Zbigniew Pawel Piotrowski
Adaptation of fluid model EULAG to graphics processing unit architecture. Concurr. Comput. Pract. Exp. 27(4): 937-957 (2015) - [j3]Lukasz Szustak
Adaptation of MPDATA Heterogeneous Stencil Computation to Intel Xeon Phi Coprocessor. Sci. Program. 2015: 642705:1-642705:14 (2015) - [c7]Krzysztof Rojek
Parallelization of 3D MPDATA Algorithm Using Many Graphics Processors. PaCT 2015: 445-457 - 2014
- [j2]Roman Wyrzykowski
Parallelization of 2D MPDATA EULAG algorithm on hybrid architectures with GPU accelerators. Parallel Comput. 40(8): 425-447 (2014) - 2013
- [c6]Roman Wyrzykowski
Towards Efficient Decomposition and Parallelization of MPDATA on Hybrid CPU-GPU Cluster. LSSC 2013: 457-464 - [c5]Krzysztof Rojek
Performance Analysis for Stencil-Based 3D MPDATA Algorithm on GPU Architecture. PPAM (1) 2013: 145-154 - [c4]Lukasz Szustak
Using Intel Xeon Phi Coprocessor to Accelerate Computations in MPDATA Algorithm. PPAM (1) 2013: 582-592 - 2012
- [j1]Roman Wyrzykowski
Model-driven adaptation of double-precision matrix multiplication to the Cell processor architecture. Parallel Comput. 38(4-5): 260-276 (2012) - 2011
- [c3]Roman Wyrzykowski
Using Blue Gene/P and GPUs to Accelerate Computations in the EULAG Model. LSSC 2011: 670-677 - [c2]Krzysztof Rojek
Parallelization of EULAG Model on Multicore Architectures with GPU Accelerators. PPAM (2) 2011: 391-400
2000 – 2009
- 2009
- [c1]Krzysztof Rojek
Adaptation of Double-Precision Matrix Multiplication to the Cell Broadband Engine Architecture. PPAM (1) 2009: 535-546
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