​

upcoming

• • [CiCP22b] H. Sheng, C. Yang, PFNN-2: A Domain Decomposed Penalty-Free Neural Network Method for Solving Partial Differential Equations, Commun. Comput. Phys., to appear. 
• • [JCST22] L. Duan, C. Xiao, M. Li, M. Ding, C. Yang, a-Tucker: Fast Input-Adaptive and Matricization-Free Tucker Decomposition of Higher-Order Tensors on GPUs, CCF T. High Perf. Comput., to appear. 
• • [ICPP22] L. Jiang, P. Xu, Q. Zhu, X. Li, S. Yan, X. Zhang, D. Lin, W. Ma, Z. Li, J. Liu, J. Ma, M, Jin, C. Yang, EasyView: Enabling and Scheduling Tensor Views in Deep Learning Compilers, in: Proc. ICPP-2022, to appear. 

2022

• • [JCP22a] L. Yin, C. Yang, S.-Z. Ma. Y. Cai, K. Zhang, Parallel finite volume simulation of the spherical shell dynamo with pseudo-vacuum magnetic boundary conditions, J. Comput. Phys., 451 (2022), pp. 110866. 
• • [JCP22b] T. Cheng, H. Yang, C. Yang, S. Sun, Scalable semismooth Newton methods with multilevel domain decomposition for subsurface flow and reactive transport in porous media, J. Comput. Phys., 467 (2022), pp. 111440. 
• • [CiCP22a] Y. Liu, C. Yang, VPVnet: a velocity-pressure-vorticity neural network method for the Stokes’ equations under reduced regularity, Commun. Comput. Phys., 31:3 (2022), pp. 739-770. 

2021

• • [SC21a] J. Xiao, J. Chen, J. Zheng, H. An, S. Huang, C. Yang, et al., Symplectic Structure-Preserving Particle-in-Cell Whole-Volume Simulation of Tokamak Plasmas to 111.3 Trillion Particles and 25.7 Billion Grids, in: Proc. ACM/IEEE SC-2021 (ACM Gordon Bell Prize Finalist), pp. 2:1-13.
• • [SC21b] Q. Zhu, H. Luo, C. Yang, M. Ding, W. Yin, X. Yuan, Enabling and Scaling the HPCG Benchmark on the Newest Generation Sunway Supercomputer with 42 Million Heterogeneous Cores, in: Proc. ACM/IEEE SC-2021 (SC21 Best Paper Finalist, SC21 Best Student Paper Finalist), pp. 57:1-13.
• • [JCP21] H. Sheng, C. Yang, PFNN: A Penalty-Free Neural Network Method for Solving a Class of Second-Order Boundary-Value Problems on Complex Geometries, J. Comput. Phys., 428 (2021), pp. 110085. 
• • [CiCP21] R. Li, H. Yang, C. Yang, Adaptive Fully Implicit Simulator with Multilevel Schwarz Methods for Gas Reservoir Flows in Fractured Porous Media, Commun. Comput. Phys., 30:5 (2021), pp. 1499-1528. 
• • [TPDS21] M. Li, Y. Ao, C. Yang, Adaptive SpMV/SpMSpV on GPUs for Input Vectors of Varied Sparsity, IEEE Trans. Par. Dist. Sys., 32:7 (2021), pp. 1842-1853. 
• • [CPC21] H. Yang, C. Yang, J. Huang, Variational inequality transport model on the sphere by the active-set reduced-space algorithm, Comput. Phys. Comm., 260 (2021), pp. 107739. 
• • [JSC21] C. Xiao, C. Yang, M. Li, Efficient Alternating Least Squares Algorithms for Low Multilinear Rank Approximation of Tensors, J. Sci. Comput., 87 (2021), pp. 67:1-25. 
• • [CC21] P. Zhang, C. Yang, Y. Ao, AutoWM: A novel domain-specific toolkit for universal multi-/many-core accelerations of the WRF cloud microphysics, Cluster Computing, 24:2 (2021), pp. 935-951. 

2020

• • [SISC20] J. Huang, C. Yang, Y. Wei, Parallel Energy-Stable Solver for a Coupled Allen-Cahn and Cahn-Hilliard System, SIAM J. Sci. Comput., 42:5 (2020), pp. C294-C312.
• • [JCP20] R. Li, H. Yang, C. Yang, Parallel multilevel restricted Schwarz preconditioners for implicit simulation of subsurface flows with Peng-Robinson equation of state, J. Comput. Phys., 422 (2020), pp. 109745. 
• • [TACO20] L. Jiang, C. Yang, W. Ma, Enabling Highly Efficient Batched Matrix Multiplications on SW26010 Many-core Processor, ACM Trans. Arch. Code Opt., 17:1 (2020), pp. 3:1-23. 
• • [CC20] W. Ma, Y. Ao, C. Yang, S. Williams, AutoWM: A novel domain-specific toolkit for universal multi-/many-core accelerations of the WRF cloud microphysics, Cluster Computing, 23:2 (2020), pp. 493-507. 

2019

• • [JCP19] R. Li, H. Yang, C. Yang, A fully implicit constraint-preserving simulator for the black oil model of petroleum reservoirs, J. Comput. Phys., 396 (2019), pp. 347–363. 
• • [CPC19b] H. Yang, S. Sun, Y. Li, C. Yang, Parallel reservoir simulators for fully implicit complementarity formulation of multicomponent compressible flows, Comput. Phys. Comm., 244 (2019), pp. 2–12. 
• • [CPC19a] Y. Wei, C. Yang, J. Huang, Parallel energy-stable phase field crystal simulations based on domain decomposition methods, Comput. Phys. Comm., 234 (2019), pp. 26-39. 
• • [CAF19] L. Yin, C. Yang, S.-Z. Ma, K.-K. Zhang, Parallel and fully implicit simulations of the thermal convection in the Earth’s outer core, Comput. & Fluids, 193 (2019), pp. 104278.
• • [TPDS19] J. Xu, H. Fu, W. Luk, L. Gan, W. Shi, W. Xue, C. Yang, et al., Optimizing Finite Volume Method Solvers on Nvidia GPUs, IEEE Trans. Par. Dist. Sys., 30:12 (2019), pp. 2790-2805. 
• • [JCST19] M. Li, C. Yang, Q. Sun, et al., Enabling highly efficient k-means computations on the SW26010 many-core processor of Sunway TaihuLight, J. Comput. Sci. Tech., 34:1 (2019), pp. 77-93. 

2018

• • [TPDS18] L. He, H. An, C. Yang, F. Wang, et al., PEPS++: Towards extreme-scale simulations of strongly correlated quantum many-particle models on Sunway TaihuLight, IEEE Trans. Par. Dist. Sys., 29:2 (2018), pp. 2838-2848. 
• • [TACO18b] Y. Cai, Y. Ao, C. Yang, W. Ma, H. Zhao, Extreme-scale high-order WENO simulations of 3-D detonation wave with ten million cores, ACM Trans. Arch. Code Opt., 15:2 (2018), pp. 26:1-21. 
• • [CMAME18] H. Yang, S. Sun, Y. Li, C. Yang, A scalable fully implicit framework for reservoir simulation on parallel computers, Comput. Methods Appl. Mech. Eng., 330 (2018), pp. 334-350. 
• • [TACO18a] Y. Ao, C. Yang, F. Liu, et al., Performance optimization of the HPCG benchmark on the Sunway TaihuLight supercomputer, ACM Trans. Arch. Code Opt., 15:1 (2018), pp. 11:1-20. 
• • [ICPP18] X. Wang, P. Xu, W. Xue, Y. Ao, C. Yang, et al., A Fast Sparse Triangular Solver for Structured-grid Problems on Sunway Many-core Processor SW26010, in: Proc. ICPP-2018, pp. 53:1-11. 
• • [CCGRID18] Y. Cai, C. Yang, W. Ma, Y. Ao, Extreme-scale realistic stencil computations on Sunway TaihuLight with ten million cores, in: Proc. CCGRID-2018, pp. 566-571. 

2017

• • [GJI17] L. Yin, C. Yang, S.-Z. Ma, et al., Parallel numerical simulation of the thermal convection in the Earth’s outer core on the cubed-sphere, Geophys. J. Int’l., 209:3 (2017), pp. 1934-1954. 
• • [JCP17] H. Yang, S. Sun, C. Yang, Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media, J. Comput. Phys., 332 (2017), pp. 1-20. 
• • [SUPE17] P. Zhang, C. Yang, C. Chen, et al., Development of a hybrid parallel MCV-based high-order global shallow-water model, J. Supercomput., 73:6 (2017), pp. 2823-2842. 
• • [Micro17] L. Gan, H. Fu, W. Luk, C. Yang, et al., Solving mesoscale atmospheric dynamics using reconfigurable dataflow architecture, IEEE Micro, 37:4 (2017), pp. 40-50. 
• • [PONE17] H. Fu, L. Gan, C. Yang, W. Xue, et al., Solving global shallow water equations on heterogeneous supercomputers, PLoS ONE, 12:3 (2017), pp. e0172583.
• • [IPDPS17] Y. Ao, C. Yang, X. Wang, et al., 26 PFLOPS stencil computations for atmospheric modeling on Sunway TaihuLight, in: Proc. IEEE IPDPS-2017, pp. 535-544. 
• • [ICPP17] L. Jiang, C. Yang, Y. Ao, et al., Towards highly efficient DGEMM on the emerging SW26010 many-core processor, in: Proc. ICPP-2017, pp. 422-431. 

2016

• • [SISC16b] H. Yang, C. Yang, S. Sun, Active-set reduced-space methods with nonlinear elimination for two-phase flow problems in porous media, SIAM J. Sci. Comput., 38:4 (2016), pp. B593-B618.
• • [SISC16a] J. Huang, C. Yang, X.-C. Cai, A nonlinearly preconditioned inexact Newton algorithm for steady state lattice Boltzmann equations, SIAM J. Sci. Comput., 38:3 (2016), pp. S1701-S1724.
• • [NSR16] J. Sun, C. Yang, X.-C. Cai, Algorithm development for extreme-scale computing, Nat’l Sci. Rev., 3:1 (2016), pp. 26-27.
• • [IJHPC16] Y. Liu, C. Yang, 623 Tflop/s HPCG run on Tianhe-2: leveraging millions of hybrid cores, Int’l J. High Perf. Comput. Appl., 30:1 (2016), pp. 39-54.
• • [CAS16] Y. Liu, H. Yang, C. Jiang, C. Yang, A scalable fully implicit method with adaptive time stepping for unsteady compressible inviscid flows, Comput. & Struct., 176 (2016), pp. 1-12.
• • [SC16] C. Yang, W. Xue, H. Fu, et al., 10M-core scalable fully-implicit solver for nonhydrostatic atmospheric dynamics, in: Proc. ACM/IEEE SC-2016 (ACM Gordon Bell Prize), pp. 6:1-12.

2015

• • [SISC15] J. Huang, C. Yang, X.-C. Cai, Fully implicit method for lattice Boltzmann equations, SIAM J. Sci. Comput., 37:5 (2015), pp. S291-S313.
• • [JCP15] X. Zheng, C. Yang, X.-C. Cai, D. Keyes, A parallel domain decomposition-based implicit method for the Cahn–Hilliard–Cook phase-field equation in 3D, J. Comput. Phys., 285 (2015), pp. 55-70.
• • [TC15] W. Xue, C. Yang, H. Fu, et al., Ultra-scalable CPU-MIC acceleration of mesoscale atmospheric modeling on Tianhe-2, IEEE Trans. Computers, 64:8 (2015), pp. 2382-2393.
• • [TRETS15] L. Gan, H. Fu, W. Luk, C. Yang, et al., Solving the global atmospheric equations through heterogeneous reconfigurable platforms, ACM Trans. Recon. Tech. Sys., 8:2 (2015), pp. 11:1-16.
• • [CAF15] H. Yang, C. Yang, X.-C. Cai, Mixed order discretization based two-level Schwarz precondtioners for a tracer transport problem on the cubed-sphere, Comput. & Fluids, 110 (2015), pp. 88-95.
• • [AMC15] J. Huang, L. Cao, C. Yang, A multiscale algorithm for radiative heat transfer equation with rapidly oscillating coefficients, Appl. Math. Comput., 266 (2015), pp 149–168.
• • [ICPP15] P. Zhang, Y. Ao, C. Yang, et al., Pattern-driven hybrid multi- and many-core acceleration in the MPAS shallow water model, in: Proc. ICPP-2015, pp. 71-80.

Before 2015

• • [SISC14] C. Yang, X.-C. Cai, A scalable fully implicit compressible Euler solver for mesoscale nonhydrostatic simulation of atmospheric flows, SIAM J. Sci. Comput., 36:5 (2014), pp. S23-S47.
• • [JSC14] H. Yang, C. Yang, X.-C. Cai, Parallel domain decomposition methods with mixed order discretization for fully implicit solution of tracer transport problems on the cubed-sphere, J. Sci. Comput., 61:2 (2014), pp. 258-280.
• • [IPDPS14] W. Xue, C. Yang, H. Fu, et al., Enabling and scaling a global shallow-water atmospheric model on Tianhe-2, in: Proc. IEEE IPDPS-2014, pp. 745-754.
• • [PPoPP13] C. Yang, W. Xue, H. Fu, et al., A Peta-scalable CPU-GPU algorithm for global atmospheric simulations, in: Proc. ACM PPoPP-2013, pp. 1-12.
• • [AMC12] C. Yang, J. Sun, New six-node and seven-node hexagonal finite elements, Appl. Math. Comput., 218:24 (2012), pp. 11763-11774.
• • [JCP11] C. Yang, X.-C. Cai, Parallel multilevel methods for implicit solution of shallow water equations with nonsmooth topography on the cubed-sphere, J. Comput. Phys., 230:7 (2011), pp. 2523-2539.
• • [JCAM11] C. Yang, X.-C. Cai, A parallel well-balanced finite volume method for shallow water equations with topography on the cubed-sphere, J. Comput. Appl. Math., 235:18 (2011), pp. 5357-5366.
• • [SISC10] C. Yang, J. Cao, X.-C. Cai, A fully implicit domain decomposition algorithm for shallow water equations on the cubed-sphere, SIAM J. Sci. Comput., 32:1 (2010), pp. 418–438.