Nesrine Khouzami |
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Phone Fax Visitor's Address |
nesrine.khouzami@tu-dresden.de +49 (0)351 463 39925 +49 (0)351 463 39995 Helmholtzstrasse 18,3rd floor, BAR III57 |
Nesrine Khouzami received her bachelor and master degrees from the Superior National Engineering School of Tunis (Ensit) respectively in June 2010 and February 2013. Her master thesis was about designing a decentralized approach for resources reservation in desktop grids. Then, she joined the Barcelona Supercomputing Center (BSC) for about a year and a half, where she worked on leveraging high-performance in-memory key-value data stores to accelerate data intensive tasks. At the CC Chair, Nesrine works on domain specific languages (e.g, for computational biology) in the high-performance computing domain.
2021
- Nesrine Khouzami, Friedrich Michel, Pietro Incardona, Jeronimo Castrillon, Ivo F. Sbalzarini, "Model-based Autotuning of Discretization Methods in Numerical Simulations of Partial Differential Equations", In Journal of Computational Science, vol. 57, pp. 1–11, Dec 2021. [doi] [Bibtex & Downloads]
Model-based Autotuning of Discretization Methods in Numerical Simulations of Partial Differential Equations
×Reference
Nesrine Khouzami, Friedrich Michel, Pietro Incardona, Jeronimo Castrillon, Ivo F. Sbalzarini, "Model-based Autotuning of Discretization Methods in Numerical Simulations of Partial Differential Equations", In Journal of Computational Science, vol. 57, pp. 1–11, Dec 2021. [doi]
Abstract
We present an autotuning approach for compile-time optimization of numerical discretization methods in simulations of partial differential equations. Our approach is based on data-driven regression of performance models for numerical methods. We use these models at compile time to automatically determine the parameters (e.g., resolution, time step size, etc.) of numerical simulations of continuum spatio-temporal models in order to optimize the tradeoff between simulation accuracy and runtime. The resulting autotuner is developed for the compiler of a Domain-Specific Language (DSL) for numerical simulations. The abstractions in the DSL enable the compiler to automatically determine the performance models and know which discretization parameters to tune. We demonstrate that this high-level approach can explore a large space of possible simulations, with simulation runtimes spanning multiple orders of magnitude. We evaluate our approach in two test cases: the linear diffusion equation and the nonlinear Gray-Scott reaction–diffusion equation. The results show that our model-based autotuner consistently finds configurations that outperform those found by state-of-the-art general-purpose autotuners. Specifically, our autotuner yields simulations that are on average 4.2x faster than those found by the best generic exploration algorithms, while using 16x less tuning time. Compared to manual tuning by a group of researchers with varying levels of expertise, the autotuner was slower than the best users by not more than a factor of 2, whereas it was able to significantly outperform half of them.
Bibtex
@Article{khouzami_jocs21,
author = {Nesrine Khouzami and Friedrich Michel and Pietro Incardona and Jeronimo Castrillon and Ivo F. Sbalzarini},
date = {2021-12},
title = {Model-based Autotuning of Discretization Methods in Numerical Simulations of Partial Differential Equations},
doi = {10.1016/j.jocs.2021.101489},
issn = {1877-7503},
pages = {1--11},
url = {https://www.sciencedirect.com/science/article/pii/S1877750321001563},
volume = {57},
abstract = {We present an autotuning approach for compile-time optimization of numerical discretization methods in simulations of partial differential equations. Our approach is based on data-driven regression of performance models for numerical methods. We use these models at compile time to automatically determine the parameters (e.g., resolution, time step size, etc.) of numerical simulations of continuum spatio-temporal models in order to optimize the tradeoff between simulation accuracy and runtime. The resulting autotuner is developed for the compiler of a Domain-Specific Language (DSL) for numerical simulations. The abstractions in the DSL enable the compiler to automatically determine the performance models and know which discretization parameters to tune. We demonstrate that this high-level approach can explore a large space of possible simulations, with simulation runtimes spanning multiple orders of magnitude. We evaluate our approach in two test cases: the linear diffusion equation and the nonlinear Gray-Scott reaction–diffusion equation. The results show that our model-based autotuner consistently finds configurations that outperform those found by state-of-the-art general-purpose autotuners. Specifically, our autotuner yields simulations that are on average 4.2x faster than those found by the best generic exploration algorithms, while using 16x less tuning time. Compared to manual tuning by a group of researchers with varying levels of expertise, the autotuner was slower than the best users by not more than a factor of 2, whereas it was able to significantly outperform half of them.},
journal = {Journal of Computational Science},
month = dec,
numpages = {15},
project = {openpme},
year = {2021},
}Downloads
2111_Khouzami_JOCS [PDF]
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- Nesrine Khouzami, Lars Schütze, Pietro Incardona, Landfried Kraaz, Tina Subic, Jeronimo Castrillon, Ivo F. Sbalzarini, "The OpenPME Problem Solving Environment for Numerical Simulations", In Proceeding: International Conference on Computational Science (ICCS'21) (Paszynski, Maciej and Kranzlmüller, Dieter and Krzhizhanovskaya, Valeria V. and Dongarra, Jack J. and Sloot, Peter M. A.), Springer International Publishing, pp. 614–627, Cham, Jun 2021. [doi] [Bibtex & Downloads]
The OpenPME Problem Solving Environment for Numerical Simulations
×Reference
Nesrine Khouzami, Lars Schütze, Pietro Incardona, Landfried Kraaz, Tina Subic, Jeronimo Castrillon, Ivo F. Sbalzarini, "The OpenPME Problem Solving Environment for Numerical Simulations", In Proceeding: International Conference on Computational Science (ICCS'21) (Paszynski, Maciej and Kranzlmüller, Dieter and Krzhizhanovskaya, Valeria V. and Dongarra, Jack J. and Sloot, Peter M. A.), Springer International Publishing, pp. 614–627, Cham, Jun 2021. [doi]
Abstract
We introduce OpenPME, the Open Particle-Mesh Environment, a problem solving environment that provides a Domain Specific Language (DSL) for numerical simulations in scientific computing. It is built atop a domain metamodel that is general enough to cover the main types of numerical simulations: simulations using particles, meshes, and hybrid combinations of particles and meshes. Using model-to-model transformations, OpenPME generates code against the state-of-the-art C++ parallel computing library OpenFPM. This effectively lowers the programming barrier and enables users to implement scalable simulation codes for high-performance computing (HPC) systems using high-level abstractions. Plenty of recent research has shown that higher-level abstractions and problem solving environments are well suited to alleviate low-level implementation overhead. We demonstrate this for OpenPME and its compiler on three different test cases—particle-based, mesh-based, and hybrid particle-mesh—showing up to 7-fold reduction in the number of lines of code compared to a direct OpenFPM implementation in C++.
Bibtex
@InProceedings{khouzami_iccs21,
author = {Nesrine Khouzami and Lars Sch{\"u}tze and Pietro Incardona and Landfried Kraaz and Tina Subic and Jeronimo Castrillon and Ivo F. Sbalzarini},
booktitle = {International Conference on Computational Science (ICCS'21)},
title = {The OpenPME Problem Solving Environment for Numerical Simulations},
doi = {10.1007/978-3-030-77961-0_49},
editor = {Paszynski, Maciej and Kranzlm{\"u}ller, Dieter and Krzhizhanovskaya, Valeria V. and Dongarra, Jack J. and Sloot, Peter M. A.},
isbn = {978-3-030-77961-0},
location = {Krakow (virtual), Poland},
organization = {Springer},
pages = {614--627},
publisher = {Springer International Publishing},
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-77961-0_49},
abstract = {We introduce OpenPME, the Open Particle-Mesh Environment, a problem solving environment that provides a Domain Specific Language (DSL) for numerical simulations in scientific computing. It is built atop a domain metamodel that is general enough to cover the main types of numerical simulations: simulations using particles, meshes, and hybrid combinations of particles and meshes. Using model-to-model transformations, OpenPME generates code against the state-of-the-art C++ parallel computing library OpenFPM. This effectively lowers the programming barrier and enables users to implement scalable simulation codes for high-performance computing (HPC) systems using high-level abstractions. Plenty of recent research has shown that higher-level abstractions and problem solving environments are well suited to alleviate low-level implementation overhead. We demonstrate this for OpenPME and its compiler on three different test cases---particle-based, mesh-based, and hybrid particle-mesh---showing up to 7-fold reduction in the number of lines of code compared to a direct OpenFPM implementation in C++.},
address = {Cham},
month = jun,
numpages = {14},
year = {2021},
}Downloads
2106_Khouzami_ICCS [PDF]
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2017
- Sven Karol, Tobias Nett, Pietro Incardona, Nesrine Khouzami, Jeronimo Castrillon, Ivo F. Sbalzarini, "A Language and Development Environment for Parallel Particle Methods", Proceedings of the 5th International Conference on Particle-based Methods. Fundamentals and Applications PARTICLES 2017 (P. Wriggers and M. Bischoff and E. Oñate and D.R.J. Owen and T. Zohdi), Sep 2017. [Bibtex & Downloads]
A Language and Development Environment for Parallel Particle Methods
×Reference
Sven Karol, Tobias Nett, Pietro Incardona, Nesrine Khouzami, Jeronimo Castrillon, Ivo F. Sbalzarini, "A Language and Development Environment for Parallel Particle Methods", Proceedings of the 5th International Conference on Particle-based Methods. Fundamentals and Applications PARTICLES 2017 (P. Wriggers and M. Bischoff and E. Oñate and D.R.J. Owen and T. Zohdi), Sep 2017.
Bibtex
@InProceedings{karol_particles17,
author = {Sven Karol and Tobias Nett and Pietro Incardona and Nesrine Khouzami and Jeronimo Castrillon and Ivo F. Sbalzarini},
title = {A Language and Development Environment for Parallel Particle Methods},
booktitle = {Proceedings of the 5th International Conference on Particle-based Methods. Fundamentals and Applications PARTICLES 2017},
year = {2017},
editor = {P. Wriggers and M. Bischoff and E. O{\~n}ate and D.R.J. Owen and T. Zohdi},
url = {https://www.semanticscholar.org/paper/A-Language-and-Development-Environment-for-Paralle-Karol-Nett/2b79bd3836aeb8e2fb2a2b5d9949f9efb1bdfab7?tab=abstract},
month = sep,
}Downloads
1709_Karol_particles [PDF]
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