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LICENSEH A D05-Oct-20211.5 KiB3023

NOTICEH A D05-Oct-20211.1 KiB2118

README.mdH A D05-Oct-20212.5 KiB6245

cvodea.cH A D05-Oct-202182.7 KiB3,1171,834

cvodea_io.cH A D05-Oct-202119.1 KiB748454

cvodes.cH A D05-Oct-2021263.2 KiB8,9925,156

cvodes_bandpre.cH A D05-Oct-202119.7 KiB626388

cvodes_bandpre_impl.hH A D05-Oct-20212.4 KiB7833

cvodes_bbdpre.cH A D05-Oct-202128.5 KiB915603

cvodes_bbdpre_impl.hH A D05-Oct-20213.1 KiB10447

cvodes_diag.cH A D05-Oct-202113.5 KiB510289

cvodes_diag_impl.hH A D05-Oct-20212.2 KiB7025

cvodes_direct.cH A D05-Oct-20212.4 KiB6631

cvodes_impl.hH A D05-Oct-202150.7 KiB1,192536

cvodes_io.cH A D05-Oct-202145.4 KiB2,0651,226

cvodes_ls.cH A D05-Oct-202190.2 KiB2,8061,794

cvodes_ls_impl.hH A D05-Oct-202110.1 KiB248121

cvodes_nls.cH A D05-Oct-202111 KiB356223

cvodes_nls_sim.cH A D05-Oct-202118.1 KiB554352

cvodes_nls_stg.cH A D05-Oct-202114.6 KiB450293

cvodes_nls_stg1.cH A D05-Oct-202111.9 KiB372233

cvodes_spils.cH A D05-Oct-20214.2 KiB10860

README.md

1# CVODES
2### Version 5.7.0 (Jan 2021)
3
4**Alan C. Hindmarsh, Radu Serban, Cody J. Balos, David J. Gardner,
5  and Carol S. Woodward, Center for Applied Scientific Computing, LLNL**
6
7**Daniel R. Reynolds, Department of Mathematics, Southern Methodist University**
8
9
10CVODES is a package for the solution of stiff and nonstiff ordinary differential
11equation (ODE) systems (initial value problem) given in explicit form
12```
13dy/dt = f(t,y,p), y(t0) = y0(p)
14```
15with sensitivity analysis capabilities (both forward and adjoint modes). CVODES
16provides a choice of two variable-order, variable-coefficient multistep methods,
17Adams-Moulton methods for non-stiff problems or BDF (Backward Differentiation
18Formula) methods in fixed-leading-coefficient form for stiff problems.
19
20CVODES is part of the SUNDIALS Suite of Nonlinear and Differential/Algebraic
21equation Solvers which consists of ARKode, CVODE, CVODES, IDA, IDAS and KINSOL.
22It is written in ANSI standard C and can be used in a variety of computing
23environments including serial, shared memory, distributed memory, and
24accelerator-based (e.g., GPU) systems. This flexibility is obtained from a
25modular design that leverages the shared vector, matrix, linear solver, and
26nonlinear solver APIs used across SUNDIALS packages.
27
28## Documentation
29
30See the [CVODES User Guide](/doc/cvodes/cvs_guide.pdf) and
31[CVODES Examples](/doc/cvodes/cvs_examples.pdf) document for more information
32about CVODES usage and the provided example programs respectively.
33
34## Installation
35
36For installation instructions see the [INSTALL_GUIDE](/INSTALL_GUIDE.pdf)
37or the "Installation Procedure" chapter in the CVODES User Guide.
38
39## Release History
40
41Information on recent changes to CVODES can be found in the "Introduction"
42chapter of the CVODES User Guide and a complete release history is available in
43the "SUNDIALS Release History" appendix of the CVODES User Guide.
44
45## References
46
47* A. C. Hindmarsh, R. Serban, C. J. Balos, D. J. Gardner, D. R. Reynolds
48  and C. S. Woodward, "User Documentation for CVODES v5.7.0,"
49  LLNL technical report UCRL-SM-208111, Jan 2021.
50
51* A. C. Hindmarsh and R. Serban, "Example Programs for CVODES v5.7.0,"
52  LLNL technical report UCRL-SM-208115, Jan 2021.
53
54* R. Serban and A. C. Hindmarsh, "CVODES: the Sensitivity-Enabled ODE
55  solver in SUNDIALS," Proceedings of IDETC/CIE 2005, Sept. 2005,
56  Long Beach, CA.
57
58* A. C. Hindmarsh, P. N. Brown, K. E. Grant, S. L. Lee, R. Serban,
59  D. E. Shumaker, and C. S. Woodward, "SUNDIALS, Suite of Nonlinear and
60  Differential/Algebraic Equation Solvers," ACM Trans. Math. Softw.,
61  31(3), pp. 363-396, 2005.
62