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Chih-Jen Sung
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2020 – today
- 2022
- [j4]Nicholas J. Curtis
, Kyle E. Niemeyer
Accelerating reactive-flow simulations using vectorized chemistry integration. Comput. Phys. Commun. 278: 108409 (2022)
2010 – 2019
- 2018
- [i4]Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung:
Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms. CoRR abs/1809.01029 (2018) - 2017
- [j3]Kyle E. Niemeyer
pyJac: Analytical Jacobian generator for chemical kinetics. Comput. Phys. Commun. 215: 188-203 (2017) - 2016
- [c1]Bryan W. Weber, Chih-Jen Sung:
UConnRCMPy: Python-based data analysis for Rapid Compression Machines. SciPy 2016: 36-44 - [i3]Kyle E. Niemeyer, Chih-Jen Sung:
On the importance of graph search algorithms for DRGEP-based mechanism reduction methods. CoRR abs/1606.07802 (2016) - [i2]Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung:
An investigation of GPU-based stiff chemical kinetics integration methods. CoRR abs/1607.03884 (2016) - [i1]Kyle E. Niemeyer, Chih-Jen Sung:
GPU-Based Parallel Integration of Large Numbers of Independent ODE Systems. CoRR abs/1611.02274 (2016) - 2014
- [j2]Kyle E. Niemeyer
Accelerating moderately stiff chemical kinetics in reactive-flow simulations using GPUs. J. Comput. Phys. 256: 854-871 (2014) - [j1]Kyle E. Niemeyer
Recent progress and challenges in exploiting graphics processors in computational fluid dynamics. J. Supercomput. 67(2): 528-564 (2014) - [p1]Kyle E. Niemeyer
GPU-Based Parallel Integration of Large Numbers of Independent ODE Systems. Numerical Computations with GPUs 2014: 159-182
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