SFOPDES: A stepwise tutorial for teaching Partial Differential Equations using a CAS

Partial Differential Equations (PDE) are one of the most difficult topics that Engineering and Sciences students have to study in the different Math subjects in their degree. In this talk we introduce SFOPDES (Stepwise First Order Partial Differential Equations Solver) aimed to be used as a tutorial for helping both the teacher and the students in the teaching and learning process of PDE. The type of problems that SFOPDES solves can be grouped in the following three blocks: 1. Pfaff Differential Equations, which consists on finding the general solution for: P(x; y; z) dx + Q(x; y; z) dy + R(x; y; z) dz = 0 (a) General method. (b) Particular cases: i. Separable equations. ii. Exact Pfaff equations. iii. One-separated variable equations. 2. Quasi-linear Partial Differential Equations, which consists on finding the general solution for: P(x; y; x) p + Q(x; y; z) q = R(x; y; z) (a) General method. (b) Particular solution which contents a given curve. 3. Using Lagrange-Charpit Method for finding a complete integral for a given general first order partial differential equation: F(x; y; z; p; q) = 0. (a) General method. (b) Particular cases: i. F(p; q) = 0 ii. g1(x; p) = g2(y; q) iii. z = px + qy + g(p; q)Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Fine-grained bit-flip protection for relaxation methods

[EN] Resilience is considered a challenging under-addressed issue that the high performance computing community (HPC) will have to face in order to produce reliable Exascale systems by the beginning of the next decade. As part of a push toward a resilient HPC ecosystem, in this paper we propose an error-resilient iterative solver for sparse linear systems based on stationary component-wise relaxation methods. Starting from a plain implementation of the Jacobi iteration, our approach introduces a low-cost component-wise technique that detects bit-flips, rejecting some component updates, and turning the initial synchronized solver into an asynchronous iteration. Our experimental study with sparse incomplete factorizations from a collection of real-world applications, and a practical GPU implementation, exposes the convergence delay incurred by the fault-tolerant implementation and its practical performance.This material is based upon work supported in part by the U.S. Department of Energy (Award Number DE-SC-0010042) and NVIDIA. E. S. Quintana-Orti was supported by project CICYT TIN2014-53495-R of MINECO and FEDER.Anzt, H.; Dongarra, J.; Quintana Ortí, ES. (2019). Fine-grained bit-flip protection for relaxation methods. Journal of Computational Science. 36:1-11. https://doi.org/10.1016/j.jocs.2016.11.013S11136Chow, E., & Patel, A. (2015). Fine-Grained Parallel Incomplete LU Factorization. SIAM Journal on Scientific Computing, 37(2), C169-C193. doi:10.1137/140968896Karpuzcu, U. R., Kim, N. S., & Torrellas, J. (2013). Coping with Parametric Variation at Near-Threshold Voltages. IEEE Micro, 33(4), 6-14. doi:10.1109/mm.2013.71Bronevetsky, G., & de Supinski, B. (2008). Soft error vulnerability of iterative linear algebra methods. Proceedings of the 22nd annual international conference on Supercomputing - ICS ’08. doi:10.1145/1375527.1375552Sao, P., & Vuduc, R. (2013). Self-stabilizing iterative solvers. Proceedings of the Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems - ScalA ’13. doi:10.1145/2530268.2530272Calhoun, J., Snir, M., Olson, L., & Garzaran, M. (2015). Understanding the Propagation of Error Due to a Silent Data Corruption in a Sparse Matrix Vector Multiply. 2015 IEEE International Conference on Cluster Computing. doi:10.1109/cluster.2015.101Chazan, D., & Miranker, W. (1969). Chaotic relaxation. Linear Algebra and its Applications, 2(2), 199-222. doi:10.1016/0024-3795(69)90028-7Frommer, A., & Szyld, D. B. (2000). On asynchronous iterations. Journal of Computational and Applied Mathematics, 123(1-2), 201-216. doi:10.1016/s0377-0427(00)00409-xDuff, I. S., & Meurant, G. A. (1989). The effect of ordering on preconditioned conjugate gradients. BIT, 29(4), 635-657. doi:10.1007/bf01932738Aliaga, J. I., Barreda, M., Dolz, M. F., Martín, A. F., Mayo, R., & Quintana-Ortí, E. S. (2014). Assessing the impact of the CPU power-saving modes on the task-parallel solution of sparse linear systems. Cluster Computing, 17(4), 1335-1348. doi:10.1007/s10586-014-0402-

A Second Order Godunov Method for Multidimensional Relativistic Magnetohydrodynamics

We describe a new Godunov algorithm for relativistic magnetohydrodynamics (RMHD) that combines a simple, unsplit second order accurate integrator with the constrained transport (CT) method for enforcing the solenoidal constraint on the magnetic field. A variety of approximate Riemann solvers are implemented to compute the fluxes of the conserved variables. The methods are tested with a comprehensive suite of multidimensional problems. These tests have helped us develop a hierarchy of correction steps that are applied when the integration algorithm predicts unphysical states due to errors in the fluxes, or errors in the inversion between conserved and primitive variables. Although used exceedingly rarely, these corrections dramatically improve the stability of the algorithm. We present preliminary results from the application of these algorithms to two problems in RMHD: the propagation of supersonic magnetized jets, and the amplification of magnetic field by turbulence driven by the relativistic Kelvin-Helmholtz instability (KHI). Both of these applications reveal important differences between the results computed with Riemann solvers that adopt different approximations for the fluxes. For example, we show that use of Riemann solvers which include both contact and rotational discontinuities can increase the strength of the magnetic field within the cocoon by a factor of ten in simulations of RMHD jets, and can increase the spectral resolution of three-dimensional RMHD turbulence driven by the KHI by a factor of 2. This increase in accuracy far outweighs the associated increase in computational cost. Our RMHD scheme is publicly available as part of the Athena code.Comment: 75 pages, 28 figures, accepted for publication in ApJS. Version with high resolution figures available from http://jila.colorado.edu/~krb3u/Athena_SR/rmhd_method_paper.pd

Bridging the computational gap between mesoscopic and continuum modeling of red blood cells for fully resolved blood flow

We present a computational framework for the simulation of blood flow with fully resolved red blood cells (RBCs) using a modular approach that consists of a lattice Boltzmann solver for the blood plasma, a novel finite element based solver for the deformable bodies and an immersed boundary method for the fluid-solid interaction. For the RBCs, we propose a nodal projective FEM (npFEM) solver which has theoretical advantages over the more commonly used mass-spring systems (mesoscopic modeling), such as an unconditional stability, versatile material expressivity, and one set of parameters to fully describe the behavior of the body at any mesh resolution. At the same time, the method is substantially faster than other FEM solvers proposed in this field, and has an efficiency that is comparable to the one of mesoscopic models. At its core, the solver uses specially defined potential energies, and builds upon them a fast iterative procedure based on quasi-Newton techniques. For a known material, our solver has only one free parameter that demands tuning, related to the body viscoelasticity. In contrast, state-of-the-art solvers for deformable bodies have more free parameters, and the calibration of the models demands special assumptions regarding the mesh topology, which restrict their generality and mesh independence. We propose as well a modification to the potential energy proposed by Skalak et al. 1973 for the red blood cell membrane, which enhances the strain hardening behavior at higher deformations. Our viscoelastic model for the red blood cell, while simple enough and applicable to any kind of solver as a post-convergence step, can capture accurately the characteristic recovery time and tank-treading frequencies. The framework is validated using experimental data, and it proves to be scalable for multiple deformable bodies