4.1. Introduction

CVODE is part of a software family called SUNDIALS: SUite of Nonlinear and DIfferential/ALgebraic equation Solvers [64]. This suite consists of CVODE, ARKODE, KINSOL, and IDA, and variants of these with sensitivity analysis capabilities.

4.1.1. Historical Background

Fortran solvers for ODE initial value problems are widespread and heavily used. Two solvers that have been written at LLNL in the past are VODE [21] and VODPK [27]. VODE is a general purpose solver that includes methods for both stiff and nonstiff systems, and in the stiff case uses direct methods (full or banded) for the solution of the linear systems that arise at each implicit step. Externally, VODE is very similar to the well known solver LSODE [87]. VODPK is a variant of VODE that uses a preconditioned Krylov (iterative) method, namely GMRES, for the solution of the linear systems. VODPK is a powerful tool for large stiff systems because it combines established methods for stiff integration, nonlinear iteration, and Krylov (linear) iteration with a problem-specific treatment of the dominant source of stiffness, in the form of the user-supplied preconditioner matrix [22]. The capabilities of both VODE and VODPK have been combined in the C-language package CVODE [37].

At present, CVODE may utilize a variety of Krylov methods provided in SUNDIALS that can be used in conjuction with Newton iteration: these include the GMRES (Generalized Minimal RESidual) [90], FGMRES (Flexible Generalized Minimum RESidual) [89], Bi-CGStab (Bi-Conjugate Gradient Stabilized) [107], TFQMR (Transpose-Free Quasi-Minimal Residual) [52], and PCG (Preconditioned Conjugate Gradient) [59] linear iterative methods. As Krylov methods, these require almost no matrix storage for solving the Newton equations as compared to direct methods. However, the algorithms allow for a user-supplied preconditioner matrix, and for most problems preconditioning is essential for an efficient solution. For very large stiff ODE systems, the Krylov methods are preferable over direct linear solver methods, and are often the only feasible choice. Among the Krylov methods in SUNDIALS, we recommend GMRES as the best overall choice. However, users are encouraged to compare all options, especially if encountering convergence failures with GMRES. Bi-CGStab and TFQMR have an advantage in storage requirements, in that the number of workspace vectors they require is fixed, while that number for GMRES depends on the desired Krylov subspace size. FGMRES has an advantage in that it is designed to support preconditioners that vary between iterations (e.g. iterative methods). PCG exhibits rapid convergence and minimal workspace vectors, but only works for symmetric linear systems.

In the process of translating the VODE and VODPK algorithms into C, the overall CVODE organization has been changed considerably. One key feature of the CVODE organization is that the linear system solvers comprise a layer of code modules that is separated from the integration algorithm, allowing for easy modification and expansion of the linear solver array. A second key feature is a separate module devoted to vector operations; this facilitated the extension to multiprosessor environments with minimal impacts on the rest of the solver, resulting in PVODE [30], the parallel variant of CVODE.

Around 2002, the functionality of CVODE and PVODE were combined into one single code, simply called CVODE. Development of this version of CVODE was concurrent with a redesign of the vector operations module across the SUNDIALS suite. The key feature of the N_Vector module is that it is written in terms of abstract vector operations with the actual vector kernels attached by a particular implementation (such as serial or parallel) of N_Vector. This allows writing the SUNDIALS solvers in a manner independent of the actual N_Vector implementation (which can be user-supplied), as well as allowing more than one N_Vector module linked into an executable file. SUNDIALS (and thus CVODE) is supplied with a wide range of different N_Vector implementations, including: serial, MPI-parallel, both OpenMP and Pthreads thread-parallel N_Vector implementations, a Hypre parallel implementation, a PETSc implementation, and various GPU-enabled implementations.

4.1.2. Changes from previous versions

4.1.2.1. Changes in v6.5.0

Added the functions CVodeGetJac(), CVodeGetJacTime(), CVodeGetJacNumSteps() to assist in debugging simulations utilizing a matrix-based linear solver.

Added support for the SYCL backend with RAJA 2022.x.y.

Fixed an underflow bug during root finding.

A new capability to keep track of memory allocations made through the SUNMemoryHelper classes has been added. Memory allocation stats can be accessed through the SUNMemoryHelper_GetAllocStats() function. See the documentation for the SUNMemoryHelper classes for more details.

Added support for CUDA v12. Fixed an issue with finding oneMKL when using the icpx compiler with the -fsycl flag as the C++ compiler instead of dpcpp.

Fixed the shape of the arrays returned by FN_VGetArrayPointer functions as well as the FSUNDenseMatrix_Data, FSUNBandMatrix_Data, FSUNSparseMatrix_Data, FSUNSparseMatrix_IndexValues, and FSUNSparseMatrix_IndexPointers functions. Compiling and running code that uses the SUNDIALS Fortran interfaces with bounds checking will now work.

4.1.2.2. Changes in v6.4.1

Fixed a bug with the Kokkos interfaces that would arise when using clang.

Fixed a compilation error with the Intel oneAPI 2022.2 Fortran compiler in the Fortran 2003 interface test for the serial N_Vector.

Fixed a bug in the SUNLINSOL_LAPACKBAND and SUNLINSOL_LAPACKDENSE modules which would cause the tests to fail on some platforms.

4.1.2.3. Changes in v6.4.0

CMake 3.18.0 or newer is now required for CUDA support.

A C++14 compliant compiler is now required for C++ based features and examples e.g., CUDA, HIP, RAJA, Trilinos, SuperLU_DIST, MAGMA, GINKGO, and KOKKOS.

Added support for GPU enabled SuperLU_DIST and SuperLU_DIST v8.x.x. Removed support for SuperLU_DIST v6.x.x or older. Fix mismatched definition and declaration bug in SuperLU_DIST matrix constructor.

Added support for the Ginkgo linear algebra library. This support includes new SUNMatrix and SUNLinearSolver implementations, see the sections §10.16 and §11.23.

Added new NVector, dense SUNMatrix, and dense SUNLinearSolver implementations utilizing the Kokkos Ecosystem for performance portability, see sections §9.19, §10.17, and §11.24 for more information.

Fixed a bug in the CUDA and HIP vectors where N_VMaxNorm() would return the minimum positive floating-point value for the zero vector.

Fixed a memory leak where the projection memory would not be deallocated when calling CVodeFree().

4.1.2.4. Changes in v6.3.0

Added the function CVodeGetUserData() to retrieve the user data pointer provided to CVodeSetUserData().

Added a new example, examples/cvode/serial/cvRocket_dns.c, which demonstrates using CVODE with a discontinuous right-hand-side function and rootfinding.

Fixed the unituitive behavior of the USE_GENERIC_MATH CMake option which caused the double precision math functions to be used regardless of the value of SUNDIALS_PRECISION. Now, SUNDIALS will use precision appropriate math functions when they are available and the user may provide the math library to link to via the advanced CMake option SUNDIALS_MATH_LIBRARY.

Changed SUNDIALS_LOGGING_ENABLE_MPI CMake option default to be ‘OFF’.

4.1.2.5. Changes in v6.2.0

Added the SUNLogger API which provides a SUNDIALS-wide mechanism for logging of errors, warnings, informational output, and debugging output.

Deprecated SUNNonlinSolSetPrintLevel_Newton(), SUNNonlinSolSetInfoFile_Newton(), SUNNonlinSolSetPrintLevel_FixedPoint(), SUNNonlinSolSetInfoFile_FixedPoint(), SUNLinSolSetInfoFile_PCG(), SUNLinSolSetPrintLevel_PCG(), SUNLinSolSetInfoFile_SPGMR(), SUNLinSolSetPrintLevel_SPGMR(), SUNLinSolSetInfoFile_SPFGMR(), SUNLinSolSetPrintLevel_SPFGMR(), SUNLinSolSetInfoFile_SPTFQM(), SUNLinSolSetPrintLevel_SPTFQMR(), SUNLinSolSetInfoFile_SPBCGS(), SUNLinSolSetPrintLevel_SPBCGS() it is recommended to use the SUNLogger API instead. The SUNLinSolSetInfoFile_** and SUNNonlinSolSetInfoFile_* family of functions are now enabled by setting the CMake option SUNDIALS_LOGGING_LEVEL to a value >= 3.

Added the function SUNProfiler_Reset() to reset the region timings and counters to zero.

Added the function CVodePrintAllStats() to output all of the integrator, nonlinear solver, linear solver, and other statistics in one call. The file scripts/sundials_csv.py contains functions for parsing the comma-separated value output files.

Added the functions CVodeSetEtaFixedStepBounds(), CVodeSetEtaMaxFirstStep(), CVodeSetEtaMaxEarlyStep(), CVodeSetNumStepsEtaMaxEarlyStep(), CVodeSetEtaMax(), CVodeSetEtaMin(), CVodeSetEtaMinErrFail(), CVodeSetEtaMaxErrFail(), CVodeSetNumFailsEtaMaxErrFail(), and CVodeSetEtaConvFail() to adjust various parameters controlling changes in step size.

Added the functions CVodeSetDeltaGammaMaxLSetup() and CVodeSetDeltaGammaMaxBadJac() to adjust the \(\gamma\) change thresholds to require a linear solver setup or Jacobian/precondition update, respectively.

The behavior of N_VSetKernelExecPolicy_Sycl() has been updated to be consistent with the CUDA and HIP vectors. The input execution policies are now cloned and may be freed after calling N_VSetKernelExecPolicy_Sycl(). Additionally, NULL inputs are now allowed and, if provided, will reset the vector execution policies to the defaults.

Fixed the SUNContext convenience class for C++ users to disallow copy construction and allow move construction.

A memory leak in the SYCL vector was fixed where the execution policies were not freed when the vector was destroyed.

The include guard in nvector_mpimanyvector.h has been corrected to enable using both the ManyVector and MPIManyVector NVector implementations in the same simulation.

Changed exported SUNDIALS PETSc CMake targets to be INTERFACE IMPORTED instead of UNKNOWN IMPORTED.

A bug was fixed in the functions CVodeGetNumNonlinSolvConvFails() and CVodeGetNonlinSolvStats() where the number of nonlinear solver failures returned was the number of failed steps due to a nonlinear solver failure i.e., if a nonlinear solve failed with a stale Jacobian or preconditioner but succeeded after updating the Jacobian or preconditioner, the initial failure was not included in the nonlinear solver failure count. These functions have been updated to return the total number of nonlinear solver failures. As such users may see an increase in the number of failures reported.

The function CVodeGetNumStepSolveFails() has been added to retrieve the number of failed steps due to a nonlinear solver failure. The count returned by this function will match those previously returned by CVodeGetNumNonlinSolvConvFails() and CVodeGetNonlinSolvStats().

4.1.2.6. Changes in v6.1.1

Fixed exported SUNDIALSConfig.cmake.

4.1.2.7. Changes in v6.1.0

Added new reduction implementations for the CUDA and HIP NVECTORs that use shared memory (local data storage) instead of atomics. These new implementations are recommended when the target hardware does not provide atomic support for the floating point precision that SUNDIALS is being built with. The HIP vector uses these by default, but the N_VSetKernelExecPolicy_Cuda() and N_VSetKernelExecPolicy_Hip() functions can be used to choose between different reduction implementations.

SUNDIALS::<lib> targets with no static/shared suffix have been added for use within the build directory (this mirrors the targets exported on installation).

CMAKE_C_STANDARD is now set to 99 by default.

Fixed exported SUNDIALSConfig.cmake when profiling is enabled without Caliper.

Fixed sundials_export.h include in sundials_config.h.

Fixed memory leaks in the SUNLINSOL_SUPERLUMT linear solver.

4.1.2.8. Changes in v6.0.0

SUNContext

SUNDIALS v6.0.0 introduces a new SUNContext object on which all other SUNDIALS objects depend. As such, the constructors for all SUNDIALS packages, vectors, matrices, linear solvers, nonlinear solvers, and memory helpers have been updated to accept a context as the last input. Users upgrading to SUNDIALS v6.0.0 will need to call SUNContext_Create() to create a context object with before calling any other SUNDIALS library function, and then provide this object to other SUNDIALS constructors. The context object has been introduced to allow SUNDIALS to provide new features, such as the profiling/instrumentation also introduced in this release, while maintaining thread-safety. See the documentation section on the SUNContext for more details.

A script upgrade-to-sundials-6-from-5.sh has been provided with the release (obtainable from the GitHub release page) to help ease the transition to SUNDIALS v6.0.0. The script will add a SUNCTX_PLACEHOLDER argument to all of the calls to SUNDIALS constructors that now require a SUNContext object. It can also update deprecated SUNDIALS constants/types to the new names. It can be run like this:

> ./upgrade-to-sundials-6-from-5.sh <files to update>

SUNProfiler

A capability to profile/instrument SUNDIALS library code has been added. This can be enabled with the CMake option SUNDIALS_BUILD_WITH_PROFILING. A built-in profiler will be used by default, but the Caliper library can also be used instead with the CMake option ENABLE_CALIPER. See the documentation section on profiling for more details. WARNING: Profiling will impact performance, and should be enabled judiciously.

SUNMemoryHelper

The SUNMemoryHelper functions SUNMemoryHelper_Alloc(), SUNMemoryHelper_Dealloc(), and SUNMemoryHelper_Copy() have been updated to accept an opaque handle as the last input. At a minimum, user-defined SUNMemoryHelper implementations will need to update these functions to accept the additional argument. Typically, this handle is the execution stream (e.g., a CUDA/HIP stream or SYCL queue) for the operation. The CUDA, HIP, and SYCL implementations have been updated accordingly. Additionally, the constructor SUNMemoryHelper_Sycl() has been updated to remove the SYCL queue as an input.

NVector

Two new optional vector operations, N_VDotProdMultiLocal() and N_VDotProdMultiAllReduce(), have been added to support low-synchronization methods for Anderson acceleration.

The CUDA, HIP, and SYCL execution policies have been moved from the sundials namespace to the sundials::cuda, sundials::hip, and sundials::sycl namespaces respectively. Accordingly, the prefixes “Cuda”, “Hip”, and “Sycl” have been removed from the execution policy classes and methods.

The Sundials namespace used by the Trilinos Tpetra NVector has been replaced with the sundials::trilinos::nvector_tpetra namespace.

The serial, PThreads, PETSc, hypre, Parallel, OpenMP_DEV, and OpenMP vector functions N_VCloneVectorArray_* and N_VDestroyVectorArray_* have been deprecated. The generic N_VCloneVectorArray() and N_VDestroyVectorArray() functions should be used instead.

The previously deprecated constructor N_VMakeWithManagedAllocator_Cuda and the function N_VSetCudaStream_Cuda have been removed and replaced with N_VNewWithMemHelp_Cuda() and N_VSetKerrnelExecPolicy_Cuda() respectively.

The previously deprecated macros PVEC_REAL_MPI_TYPE and PVEC_INTEGER_MPI_TYPE have been removed and replaced with MPI_SUNREALTYPE and MPI_SUNINDEXTYPE respectively.

SUNLinearSolver

The following previously deprecated functions have been removed:

Removed	Replacement
`SUNBandLinearSolver`	`SUNLinSol_Band()`
`SUNDenseLinearSolver`	`SUNLinSol_Dense()`
`SUNKLU`	`SUNLinSol_KLU()`
`SUNKLUReInit`	`SUNLinSol_KLUReInit()`
`SUNKLUSetOrdering`	`SUNLinSol_KLUSetOrdering()`
`SUNLapackBand`	`SUNLinSol_LapackBand()`
`SUNLapackDense`	`SUNLinSol_LapackDense()`
`SUNPCG`	`SUNLinSol_PCG()`
`SUNPCGSetPrecType`	`SUNLinSol_PCGSetPrecType()`
`SUNPCGSetMaxl`	`SUNLinSol_PCGSetMaxl()`
`SUNSPBCGS`	`SUNLinSol_SPBCGS()`
`SUNSPBCGSSetPrecType`	`SUNLinSol_SPBCGSSetPrecType()`
`SUNSPBCGSSetMaxl`	`SUNLinSol_SPBCGSSetMaxl()`
`SUNSPFGMR`	`SUNLinSol_SPFGMR()`
`SUNSPFGMRSetPrecType`	`SUNLinSol_SPFGMRSetPrecType()`
`SUNSPFGMRSetGSType`	`SUNLinSol_SPFGMRSetGSType()`
`SUNSPFGMRSetMaxRestarts`	`SUNLinSol_SPFGMRSetMaxRestarts()`
`SUNSPGMR`	`SUNLinSol_SPGMR()`
`SUNSPGMRSetPrecType`	`SUNLinSol_SPGMRSetPrecType()`
`SUNSPGMRSetGSType`	`SUNLinSol_SPGMRSetGSType()`
`SUNSPGMRSetMaxRestarts`	`SUNLinSol_SPGMRSetMaxRestarts()`
`SUNSPTFQMR`	`SUNLinSol_SPTFQMR()`
`SUNSPTFQMRSetPrecType`	`SUNLinSol_SPTFQMRSetPrecType()`
`SUNSPTFQMRSetMaxl`	`SUNLinSol_SPTFQMRSetMaxl()`
`SUNSuperLUMT`	`SUNLinSol_SuperLUMT()`
`SUNSuperLUMTSetOrdering`	`SUNLinSol_SuperLUMTSetOrdering()`

CVODE

The previously deprecated function CVodeSetMaxStepsBetweenJac has been removed and replaced with CVodeSetJacEvalFrequency().

The CVODE Fortran 77 interface has been removed. See §2.5 and the F2003 example programs for more details using the SUNDIALS Fortran 2003 module interfaces.

Deprecations

In addition to the deprecations noted elsewhere, many constants, types, and functions have been renamed so that they are properly namespaced. The old names have been deprecated and will be removed in SUNDIALS v7.0.0.

The following constants, macros, and typedefs are now deprecated:

Deprecated Name	New Name
`realtype`	`sunrealtype`
`booleantype`	`sunbooleantype`
`RCONST`	`SUN_RCONST`
`BIG_REAL`	`SUN_BIG_REAL`
`SMALL_REAL`	`SUN_SMALL_REAL`
`UNIT_ROUNDOFF`	`SUN_UNIT_ROUNDOFF`
`PREC_NONE`	`SUN_PREC_NONE`
`PREC_LEFT`	`SUN_PREC_LEFT`
`PREC_RIGHT`	`SUN_PREC_RIGHT`
`PREC_BOTH`	`SUN_PREC_BOTH`
`MODIFIED_GS`	`SUN_MODIFIED_GS`
`CLASSICAL_GS`	`SUN_CLASSICAL_GS`
`ATimesFn`	`SUNATimesFn`
`PSetupFn`	`SUNPSetupFn`
`PSolveFn`	`SUNPSolveFn`
`DlsMat`	`SUNDlsMat`
`DENSE_COL`	`SUNDLS_DENSE_COL`
`DENSE_ELEM`	`SUNDLS_DENSE_ELEM`
`BAND_COL`	`SUNDLS_BAND_COL`
`BAND_COL_ELEM`	`SUNDLS_BAND_COL_ELEM`
`BAND_ELEM`	`SUNDLS_BAND_ELEM`

In addition, the following functions are now deprecated (compile-time warnings will be thrown if supported by the compiler):

Deprecated Name	New Name
`CVSpilsSetLinearSolver`	`CVodeSetLinearSolver`
`CVSpilsSetEpsLin`	`CVodeSetEpsLin`
`CVSpilsSetPreconditioner`	`CVodeSetPreconditioner`
`CVSpilsSetJacTimes`	`CVodeSetJacTimes`
`CVSpilsGetWorkSpace`	`CVodeGetLinWorkSpace`
`CVSpilsGetNumPrecEvals`	`CVodeGetNumPrecEvals`
`CVSpilsGetNumPrecSolves`	`CVodeGetNumPrecSolves`
`CVSpilsGetNumLinIters`	`CVodeGetNumLinIters`
`CVSpilsGetNumConvFails`	`CVodeGetNumConvFails`
`CVSpilsGetNumJTSetupEvals`	`CVodeGetNumJTSetupEvals`
`CVSpilsGetNumJtimesEvals`	`CVodeGetNumJtimesEvals`
`CVSpilsGetNumRhsEvals`	`CVodeGetNumLinRhsEvals`
`CVSpilsGetLastFlag`	`CVodeGetLastLinFlag`
`CVSpilsGetReturnFlagName`	`CVodeGetLinReturnFlagName`
`CVDlsSetLinearSolver`	`CVodeSetLinearSolver`
`CVDlsSetJacFn`	`CVodeSetJacFn`
`CVDlsGetWorkSpace`	`CVodeGetLinWorkSpace`
`CVDlsGetNumJacEvals`	`CVodeGetNumJacEvals`
`CVDlsGetNumRhsEvals`	`CVodeGetNumLinRhsEvals`
`CVDlsGetLastFlag`	`CVodeGetLastLinFlag`
`CVDlsGetReturnFlagName`	`CVodeGetLinReturnFlagName`
`DenseGETRF`	`SUNDlsMat_DenseGETRF`
`DenseGETRS`	`SUNDlsMat_DenseGETRS`
`denseGETRF`	`SUNDlsMat_denseGETRF`
`denseGETRS`	`SUNDlsMat_denseGETRS`
`DensePOTRF`	`SUNDlsMat_DensePOTRF`
`DensePOTRS`	`SUNDlsMat_DensePOTRS`
`densePOTRF`	`SUNDlsMat_densePOTRF`
`densePOTRS`	`SUNDlsMat_densePOTRS`
`DenseGEQRF`	`SUNDlsMat_DenseGEQRF`
`DenseORMQR`	`SUNDlsMat_DenseORMQR`
`denseGEQRF`	`SUNDlsMat_denseGEQRF`
`denseORMQR`	`SUNDlsMat_denseORMQR`
`DenseCopy`	`SUNDlsMat_DenseCopy`
`denseCopy`	`SUNDlsMat_denseCopy`
`DenseScale`	`SUNDlsMat_DenseScale`
`denseScale`	`SUNDlsMat_denseScale`
`denseAddIdentity`	`SUNDlsMat_denseAddIdentity`
`DenseMatvec`	`SUNDlsMat_DenseMatvec`
`denseMatvec`	`SUNDlsMat_denseMatvec`
`BandGBTRF`	`SUNDlsMat_BandGBTRF`
`bandGBTRF`	`SUNDlsMat_bandGBTRF`
`BandGBTRS`	`SUNDlsMat_BandGBTRS`
`bandGBTRS`	`SUNDlsMat_bandGBTRS`
`BandCopy`	`SUNDlsMat_BandCopy`
`bandCopy`	`SUNDlsMat_bandCopy`
`BandScale`	`SUNDlsMat_BandScale`
`bandScale`	`SUNDlsMat_bandScale`
`bandAddIdentity`	`SUNDlsMat_bandAddIdentity`
`BandMatvec`	`SUNDlsMat_BandMatvec`
`bandMatvec`	`SUNDlsMat_bandMatvec`
`ModifiedGS`	`SUNModifiedGS`
`ClassicalGS`	`SUNClassicalGS`
`QRfact`	`SUNQRFact`
`QRsol`	`SUNQRsol`
`DlsMat_NewDenseMat`	`SUNDlsMat_NewDenseMat`
`DlsMat_NewBandMat`	`SUNDlsMat_NewBandMat`
`DestroyMat`	`SUNDlsMat_DestroyMat`
`NewIntArray`	`SUNDlsMat_NewIntArray`
`NewIndexArray`	`SUNDlsMat_NewIndexArray`
`NewRealArray`	`SUNDlsMat_NewRealArray`
`DestroyArray`	`SUNDlsMat_DestroyArray`
`AddIdentity`	`SUNDlsMat_AddIdentity`
`SetToZero`	`SUNDlsMat_SetToZero`
`PrintMat`	`SUNDlsMat_PrintMat`
`newDenseMat`	`SUNDlsMat_newDenseMat`
`newBandMat`	`SUNDlsMat_newBandMat`
`destroyMat`	`SUNDlsMat_destroyMat`
`newIntArray`	`SUNDlsMat_newIntArray`
`newIndexArray`	`SUNDlsMat_newIndexArray`
`newRealArray`	`SUNDlsMat_newRealArray`
`destroyArray`	`SUNDlsMat_destroyArray`

In addition, the entire sundials_lapack.h header file is now deprecated for removal in SUNDIALS v7.0.0. Note, this header file is not needed to use the SUNDIALS LAPACK linear solvers.

4.1.2.9. Changes in v5.8.0

The RAJA N_Vector implementation has been updated to support the SYCL backend in addition to the CUDA and HIP backend. Users can choose the backend when configuring SUNDIALS by using the SUNDIALS_RAJA_BACKENDS CMake variable. This module remains experimental and is subject to change from version to version.

New SUNMatrix and SUNLinearSolver implementations were added to interface with the Intel oneAPI Math Kernel Library (oneMKL). Both the matrix and the linear solver support general dense linear systems as well as block diagonal linear systems. See §11.14 for more details. This module is experimental and is subject to change from version to version.

Added a new optional function to the SUNLinearSolver API, SUNLinSolSetZeroGuess(), to indicate that the next call to SUNlinSolSolve() will be made with a zero initial guess. SUNLinearSolver implementations that do not use the SUNLinSolNewEmpty() constructor will, at a minimum, need set the setzeroguess function pointer in the linear solver ops structure to NULL. The SUNDIALS iterative linear solver implementations have been updated to leverage this new set function to remove one dot product per solve.

CVODE now supports a new “matrix-embedded” SUNLinearSolver type. This type supports user-supplied SUNLinearSolver implementations that set up and solve the specified linear system at each linear solve call. Any matrix-related data structures are held internally to the linear solver itself, and are not provided by the SUNDIALS package.

Added specialized fused HIP kernels to CVODE which may offer better performance on smaller problems when using CVODE with the N_Vector HIP module. See the optional input function CVodeSetUseIntegratorFusedKernels() for more information. As with other SUNDIALS HIP features, this capability is considered experimental and may change from version to version.

Added the function CVodeSetNlsRhsFn() to supply an alternative right-hand side function for use within nonlinear system function evaluations.

The installed SUNDIALSConfig.cmake file now supports the COMPONENTS option to find_package. The exported targets no longer have IMPORTED_GLOBAL set.

A bug was fixed in SUNMatCopyOps() where the matrix-vector product setup function pointer was not copied.

A bug was fixed in the SPBCGS and SPTFQMR solvers for the case where a non-zero initial guess and a solution scaling vector are provided. This fix only impacts codes using SPBCGS or SPTFQMR as standalone solvers as all SUNDIALS packages utilize a zero initial guess.

4.1.2.10. Changes in v5.7.0

A new N_Vector implementation based on the SYCL abstraction layer has been added targeting Intel GPUs. At present the only SYCL compiler supported is the DPC++ (Intel oneAPI) compiler. See §9.17 for more details. This module is considered experimental and is subject to major changes even in minor releases.

New SUNMatrix and SUNLinearSolver implementations were added to interface with the MAGMA linear algebra library. Both the matrix and the linear solver support general dense linear systems as well as block diagonal linear systems, and both are targeted at GPUs (AMD or NVIDIA). See §11.13 for more details.

4.1.2.11. Changes in v5.6.1

Fixed a bug in the SUNDIALS CMake which caused an error if the CMAKE_CXX_STANDARD and SUNDIALS_RAJA_BACKENDS options were not provided.

Fixed some compiler warnings when using the IBM XL compilers.

4.1.2.12. Changes in v5.6.0

A new N_Vector implementation based on the AMD ROCm HIP platform has been added. This vector can target NVIDIA or AMD GPUs. See §9.16 for more details. This module is considered experimental and is subject to change from version to version.

The RAJA N_Vector implementation has been updated to support the HIP backend in addition to the CUDA backend. Users can choose the backend when configuring SUNDIALS by using the SUNDIALS_RAJA_BACKENDS CMake variable. This module remains experimental and is subject to change from version to version.

A new optional operation, N_VGetDeviceArrayPointer(), was added to the N_Vector API. This operation is useful for N_Vectors that utilize dual memory spaces, e.g. the native SUNDIALS CUDA N_Vector.

The SUNMATRIX_CUSPARSE and SUNLINEARSOLVER_CUSOLVERSP_BATCHQR implementations no longer require the SUNDIALS CUDA N_Vector. Instead, they require that the vector utilized provides the N_VGetDeviceArrayPointer() operation, and that the pointer returned by N_VGetDeviceArrayPointer() is a valid CUDA device pointer.

4.1.2.13. Changes in v5.5.0

Refactored the SUNDIALS build system. CMake 3.12.0 or newer is now required. Users will likely see deprecation warnings, but otherwise the changes should be fully backwards compatible for almost all users. SUNDIALS now exports CMake targets and installs a SUNDIALSConfig.cmake file.

Added support for SuperLU DIST 6.3.0 or newer.

4.1.2.14. Changes in v5.4.0

Added new functions CVodeComputeState(), and CVodeGetNonlinearSystemData() which advanced users might find useful if providing a custom SUNNonlinSolSysFn.

Added the function CVodeSetLSNormFactor() to specify the factor for converting between integrator tolerances (WRMS norm) and linear solver tolerances (L2 norm) i.e., tol_L2 = nrmfac * tol_WRMS.

The expected behavior of SUNNonlinSolGetNumIters() and SUNNonlinSolGetNumConvFails() in the SUNNonlinearSolver API have been updated to specify that they should return the number of nonlinear solver iterations and convergence failures in the most recent solve respectively rather than the cumulative number of iterations and failures across all solves respectively. The API documentation and SUNDIALS provided SUNNonlinearSolver implementations have been updated accordingly. As before, the cumulative number of nonlinear iterations may be retreived by calling CVodeGetNumNonlinSolvIters(), the cumulative number of failures with CVodeGetNumNonlinSolvConvFails(), or both with CVodeGetNonlinSolvStats().

A minor inconsistency in checking the Jacobian evaluation frequency has been fixed. As a result codes using using a non-default Jacobian update frequency through a call to CVodeSetMaxStepsBetweenJac() will need to increase the provided value by 1 to achieve the same behavior as before. For greater clarity the function has been deprecated and replaced with CVodeSetJacEvalFrequency(). Additionally, the function CVodeSetLSetupFrequency() has been added to set the frequency of calls to the linear solver setup function.

A new class, SUNMemoryHelper, was added to support GPU users who have complex memory management needs such as using memory pools. This is paired with new constructors for the NVECTOR_CUDA and NVECTOR_RAJA modules that accept a SUNMemoryHelper object. Refer to §2.6, §13, §9.15 and §9.18 for more information.

The NVECTOR_RAJA vector implementation has been updated to mirror the NVECTOR_CUDA implementation. Notably, the update adds managed memory support. Users of the vector will need to update any calls to the function because that signature was changed. This vector remains experimental and is subject to change from version to version.

The NVECTOR_TRILINOS vector implementation has been updated to work with Trilinos 12.18+. This update changes the local ordinal type to always be an int.

4.1.2.15. Changes in v5.3.0

Fixed a bug in the iterative linear solver modules where an error is not returned if the Atimes function is NULL or, if preconditioning is enabled, the PSolve function is NULL.

Added specialized fused CUDA kernels to CVODE which may offer better performance on smaller problems when using CVODE with the NVECTOR_CUDA module. See the optional input function for more information. As with other SUNDIALS CUDA features, this capability is considered experimental and may change from version to version.

Added the ability to control the CUDA kernel launch parameters for the NVECTOR_CUDA and SUNMATRIX_CUSPARSE modules. These modules remain experimental and are subject to change from version to version. In addition, the kernels were rewritten to be more flexible. Most users should see equivalent performance or some improvement, but a select few may observe minor performance degradation with the default settings. Users are encouraged to contact the SUNDIALS team about any perfomance changes that they notice.

Added new capabilities for monitoring the solve phase in the SUNNONLINSOL_NEWTON and SUNNONLINSOL_FIXEDPOINT modules, and the SUNDIALS iterative linear solver modules. SUNDIALS must be built with the SUNDIALS_BUILD_WITH_MONITORING CMake option set to TRUE to use these capabilties.

Added a new function, CVodeSetMonitorFn(), that takes a user-function to be called by CVODE after every \(nst\) succesfully completed time-steps. This is intended to provide a way of monitoring the CVODE statistics throughout the simulation.

Added a new function CVodeGetLinSolveStats() to get the CVODE linear solver statistics as a group.

Added the optional function CVodeSetJacTimsRhsFn() to specify an alternative right-hand side function for computing Jacobian-vector products with the internal difference quotient approximation.

Added support for integrating IVPs with constraints using BDF methods and projecting the solution onto the constraint manifold with a user defined projection function. This implementation is accompanied by additions to user documentation and CVODE examples. See CVodeSetProjFn() for more information.

Added support for CUDA v11.

4.1.2.16. Changes in v5.2.0

Fixed a build system bug related to the Fortran 2003 interfaces when using the IBM XL compiler. When building the Fortran 2003 interfaces with an XL compiler it is recommended to set CMAKE_Fortran_COMPILER to f2003, xlf2003, or xlf2003_r.

Fixed a linkage bug affecting Windows users that stemmed from dllimport/dllexport attributes missing on some SUNDIALS API functions.

Added a new SUNMatrix implementation, SUNMATRIX_CUSPARSE, that interfaces to the sparse matrix implementation from the NVIDIA cuSPARSE library. In addition, the linear solver has been updated to use this matrix, therefore, users of this module will need to update their code. These modules are still considered to be experimental, thus they are subject to breaking changes even in minor releases.

The function CVodeSetLinearSolutionScaling() was added to enable or disable the scaling applied to linear system solutions with matrix-based linear solvers to account for a lagged value of \(\gamma\) in the linear system matrix \(I - \gamma J\). Scaling is enabled by default when using a matrix-based linear solver with BDF methods.

4.1.2.17. Changes in v5.1.0

Fixed a build system bug related to finding LAPACK/BLAS.

Fixed a build system bug related to checking if the KLU library works.

Fixed a build system bug related to finding PETSc when using the CMake variables PETSC_INCLUDES and PETSC_LIBRARIES instead of PETSC_DIR.

Added a new build system option, CUDA_ARCH, that can be used to specify the CUDA architecture to compile for.

Added two utility functions, SUNDIALSFileOpen() and SUNDIALSFileClose() for creating/destroying file pointers that are useful when using the Fortran 2003 interfaces.

Added support for constant damping to the SUNNonlinearSolver_FixedPoint module when using Anderson acceleration.

4.1.2.18. Changes in v5.0.0

Build system changes

Increased the minimum required CMake version to 3.5 for most SUNDIALS configurations, and 3.10 when CUDA or OpenMP with device offloading are enabled.
The CMake option BLAS_ENABLE and the variable BLAS_LIBRARIES have been removed to simplify builds as SUNDIALS packages do not use BLAS directly. For third party libraries that require linking to BLAS, the path to the BLAS library should be included in the variable for the third party library e.g., SUPERLUDIST_LIBRARIES when enabling SuperLU_DIST.
Fixed a bug in the build system that prevented the NVECTOR_PTHREADS module from being built.

NVECTOR module changes

Two new functions were added to aid in creating custom N_Vector objects. The constructor N_VNewEmpty() allocates an “empty” generic N_Vector with the object’s content pointer and the function pointers in the operations structure initialized to NULL. When used in the constructor for custom objects this function will ease the introduction of any new optional operations to the N_Vector API by ensuring only required operations need to be set. Additionally, the function N_VCopyOps() has been added to copy the operation function pointers between vector objects. When used in clone routines for custom vector objects these functions also will ease the introduction of any new optional operations to the N_Vector API by ensuring all operations are copied when cloning objects. See §9.1.2 for more details.
Two new N_Vector implementations, NVECTOR_MANYVECTOR and NVECTOR_MPIMANYVECTOR, have been created to support flexible partitioning of solution data among different processing elements (e.g., CPU + GPU) or for multi-physics problems that couple distinct MPI-based simulations together. This implementation is accompanied by additions to user documentation and SUNDIALS examples. See §9.22 and §9.23 for more details.
One new required vector operation and ten new optional vector operations have been added to the N_Vector API. The new required operation, , returns the global length of an . The optional operations have been added to support the new NVECTOR_MPIMANYVECTOR implementation. The operation must be implemented by subvectors that are combined to create an NVECTOR_MPIMANYVECTOR, but is not used outside of this context. The remaining nine operations are optional local reduction operations intended to eliminate unnecessary latency when performing vector reduction operations (norms, etc.) on distributed memory systems. The optional local reduction vector operations are N_VDotProdLocal(), N_VMaxNormLocal(), N_VL1NormLocal(), N_VWSqrSumLocal(), N_VWSqrSumMaskLocal(), N_VInvTestLocal(), N_VConstrMaskLocal(), N_VMinLocal(), and N_VMinQuotientLocal(). If an N_Vector implementation defines any of the local operations as , then the NVECTOR_MPIMANYVECTOR will call standard N_Vector operations to complete the computation.
An additional N_Vector implementation, NVECTOR_MPIPLUSX, has been created to support the MPI+X paradigm where X is a type of on-node parallelism (e.g., OpenMP, CUDA). The implementation is accompanied by additions to user documentation and SUNDIALS examples. See §9.24 for more details.
The and functions have been removed from the NVECTOR_CUDA and NVECTOR_RAJA implementations respectively. Accordingly, the nvector_mpicuda.h, libsundials_nvecmpicuda.lib, libsundials_nvecmpicudaraja.lib, and files have been removed. Users should use the NVECTOR_MPIPLUSX module coupled in conjunction with the NVECTOR_CUDA or NVECTOR_RAJA modules to replace the functionality. The necessary changes are minimal and should require few code modifications. See the programs in and for examples of how to use the NVECTOR_MPIPLUSX module with the NVECTOR_CUDA and NVECTOR_RAJA modules respectively.
Fixed a memory leak in the NVECTOR_PETSC module clone function.
Made performance improvements to the NVECTOR_CUDA module. Users who utilize a non-default stream should no longer see default stream synchronizations after memory transfers.
Added a new constructor to the NVECTOR_CUDA module that allows a user to provide custom allocate and free functions for the vector data array and internal reduction buffer. See §9.15 for more details.
Added new Fortran 2003 interfaces for most N_Vector modules. See §9 for more details on how to use the interfaces.
Added three new N_Vector utility functions N_VGetVecAtIndexVectorArray(), N_VSetVecAtIndexVectorArray(), and N_VNewVectorArray() for working with arrays when using the Fortran 2003 interfaces.

SUNMatrix module changes

Two new functions were added to aid in creating custom SUNMatrix objects. The constructor SUNMatNewEmpty() allocates an “empty” generic SUNMatrix with the object’s content pointer and the function pointers in the operations structure initialized to . When used in the constructor for custom objects this function will ease the introduction of any new optional operations to the SUNMatrix API by ensuring only required operations need to be set. Additionally, the function SUNMatCopyOps() has been added to copy the operation function pointers between matrix objects. When used in clone routines for custom matrix objects these functions also will ease the introduction of any new optional operations to the SUNMatrix API by ensuring all operations are copied when cloning objects. See §10 for more details.
A new operation, SUNMatMatvecSetup(), was added to the SUNMatrix API to perform any setup necessary for computing a matrix-vector product. This operation is useful for SUNMatrix implementations which need to prepare the matrix itself, or communication structures before performing the matrix-vector product. Users who have implemented custom SUNMatrix modules will need to at least update their code to set the corresponding structure member to NULL. See §10.2 for more details.
The generic SUNMatrix API now defines error codes to be returned by SUNMatrix operations. Operations which return an integer flag indiciating success/failure may return different values than previously. See §10.2.1 for more details.
A new SUNMatrix (and SUNLinearSolver) implementation was added to facilitate the use of the SuperLU_DIST library with SUNDIALS. See §10.15 for more details.
Added new Fortran 2003 interfaces for most SUNMatrix modules. See §10 for more details on how to use the interfaces.

SUNLinearSolver module changes

A new function was added to aid in creating custom SUNLinearSolver objects. The constructor allocates an “empty” generic SUNLinearSolver with the object’s content pointer and the function pointers in the operations structure initialized to . When used in the constructor for custom objects this function will ease the introduction of any new optional operations to the SUNLinearSolver API by ensuring only required operations need to be set. See §11.1.8 for more details.
The return type of the SUNLinearSolver API function has changed from to to be consistent with the type used to store row indices in dense and banded linear solver modules.
Added a new optional operation to the SUNLinearSolver API, SUNLinSolLastFlag(), that returns a for identifying the linear solver module.
The SUNLinearSolver API has been updated to make the initialize and setup functions optional.
A new SUNLinearSolver (and SUNMatrix) implementation was added to facilitate the use of the SuperLU_DIST library with SUNDIALS. See §11.20 for more details.
Added a new SUNLinearSolver implementation, SUNLINEARSOLVER_CUSOLVERSP, which leverages the NVIDIA cuSOLVER sparse batched QR method for efficiently solving block diagonal linear systems on NVIDIA GPUs.
Added three new accessor functions to the SUNLINSOL_KLU module, SUNLinSol_KLUGetSymbolic(), , SUNLinSol_KLUGetNumeric() and SUNLinSol_KLUGetCommon(), to provide user access to the underlying KLU solver structures. See §11.10 for more details.
Added new Fortran 2003 interfaces for most SUNLinearSolver modules. See §11 for more details on how to use the interfaces.

SUNNonlinearSolver module changes

A new function was added to aid in creating custom SUNNonlinearSolver objects. The constructor SUNNonlinSolSetConvTestFN() allocates an “empty” generic SUNNonlinearSolver with the object’s content pointer and the function pointers in the operations structure initialized to . When used in the constructor for custom objects this function will ease the introduction of any new optional operations to the SUNNonlinearSolver API by ensuring only required operations need to be set. See §12.1.7 for more details.
To facilitate the use of user supplied nonlinear solver convergence test functions the function in the SUNNonlinearSolver API has been updated to take a data pointer as input. The supplied data pointer will be passed to the nonlinear solver convergence test function on each call.
The inputs values passed to the first two inputs of the function SUNNonlinSolSolve() in the SUNNonlinearSolver have been changed to be the predicted state and the initial guess for the correction to that state. Additionally, the definitions of SUNNonlinSolLSetupFn() and SUNNonlinSolLSolveFn() in the SUNNonlinearSolver API have been updated to remove unused input parameters. For more information on the nonlinear system formulation see §12.3 and for more details on the API functions see §12.
Added a new SUNNonlinearSolver implementation, SUNNONLINSOL_PETSC, which interfaces to the PETSc SNES nonlinear solver API. See §12.9 for more details.
Added new Fortran 2003 interfaces for most SUNNonlinearSolver modules. See §2.5 for more details on how to use the interfaces.

CVODE changes

Fixed a bug in the CVODE constraint handling where the step size could be set below the minimum step size.
Fixed a bug in the CVODE nonlinear solver interface where the norm of the accumulated correction was not updated when using a non-default convergence test function.
Fixed a memeory leak in FCVODE when not using the default nonlinear solver.
Removed extraneous calls to for simulations where the scalar valued absolute tolerance, or all entries of the vector-valued absolute tolerance array, are strictly positive. In this scenario, CVODE will remove at least one global reduction per time step.
The CVLS interface has been updated to only zero the Jacobian matrix before calling a user-supplied Jacobian evaluation function when the attached linear solver has type SUNLINEARSOLVER_DIRECT.
A new linear solver interface function CVLsLinSysFn() was added as an alternative method for evaluating the linear system \(M = I - \gamma J\).
Added two new functions, CVodeGetCurrentGamma() and CVodeGetCurrentState(), which may be useful to users who choose to provide their own nonlinear solver implementations.
The CVODE Fortran 2003 interface was completely redone to be more sustainable and to allow users to write more idiomatic Fortran. See §2.5 for more details.

4.1.2.19. Changes in v4.1.0

An additional N_Vector implementation was added for the Tpetra vector from the Trilinos library to facilitate interoperability between SUNDIALS and Trilinos. This implementation is accompanied by additions to user documentation and SUNDIALS examples.

A bug was fixed where a nonlinear solver object could be freed twice in some use cases.

The CMake option EXAMPLES_ENABLE_RAJA has been removed. The option enables all examples that use CUDA including the RAJA examples with a CUDA back end (if the RAJA N_Vector is enabled).

The implementation header file is no longer installed. This means users who are directly manipulating the structure will need to update their code to use CVODE’s public API.

Python is no longer required to run make test and make test_install.

4.1.2.20. Changes in v4.0.2

Added information on how to contribute to SUNDIALS and a contributing agreement.

Moved definitions of DLS and SPILS backwards compatibility functions to a source file. The symbols are now included in the CVODE library, libsundials_cvode.

4.1.2.21. Changes in v4.0.1

No changes were made in this release.

4.1.2.22. Changes in v4.0.0

CVODE’s previous direct and iterative linear solver interfaces, CVDLS and CVSPILS, have been merged into a single unified linear solver interface, CVLS, to support any valid SUNLinearSolver module. This includes the “DIRECT” and “ITERATIVE” types as well as the new “MATRIX_ITERATIVE” type. Details regarding how CVLS utilizes linear solvers of each type as well as discussion regarding intended use cases for user-supplied SUNLinearSolver implementations are included in §11. All CVODE example programs and the standalone linear solver examples have been updated to use the unified linear solver interface.

The unified interface for the new CVLS module is very similar to the previous CVDLS and CVSPILS interfaces. To minimize challenges in user migration to the new names, the previous C and Fortran routine names may still be used; these will be deprecated in future releases, so we recommend that users migrate to the new names soon. Additionally, we note that Fortran users, however, may need to enlarge their array of optional integer outputs, and update the indices that they query for certain linear-solver-related statistics.

The names of all constructor routines for SUNDIALS-provided SUNLinearSolver implementations have been updated to follow the naming convention SUNLinSol_* where is the name of the linear solver. Solver-specific “set” routine names have been similarly standardized. To minimize challenges in user migration to the new names, the previous routine names may still be used; these will be deprecated in future releases, so we recommend that users migrate to the new names soon. All CVODE example programs and the standalone linear solver examples have been updated to use the new naming convention.

The SUNMATRIX_BAND constructor has been simplified to remove the storage upper bandwidth argument.

SUNDIALS integrators have been updated to utilize generic nonlinear solver modules defined through the SUNNonlinearSolver API. This API will ease the addition of new nonlinear solver options and allow for external or user-supplied nonlinear solvers. The SUNNonlinearSolver API and SUNDIALS provided modules are described in §12 and follow the same object oriented design and implementation used by the N_Vector, SUNMatrix, and SUNLinearSolver modules. Currently two SUNNonlinearSolver implementations are provided, SUNNONLINSOL_NEWTON and SUNNONLINSOL_FIXEDPOINT. These replicate the previous integrator specific implementations of a Newton iteration and a fixed-point iteration (previously referred to as a functional iteration), respectively. Note the SUNNONLINSOL_FIXEDPOINT module can optionally utilize Anderson’s method to accelerate convergence. Example programs using each of these nonlinear solver modules in a standalone manner have been added and all CVODE example programs have been updated to use generic SUNNonlinearSolver modules.

With the introduction of SUNNonlinearSolver modules, the iter input parameter to CVodeCreate() has been removed along with the function CVodeSetIterType() and the constants CV_NEWTON and CV_FUNCTIONAL. Similarly, the parameter has been removed from the Fortran interface function FCVMALLOC. Instead of specifying the nonlinear iteration type when creating the CVODE memory structure, CVODE uses the SUNNONLINSOL_NEWTON module implementation of a Newton iteration by default. For details on using a non-default or user-supplied nonlinear solver see :numref:CVODE.Usage.CC. CVODE functions for setting the nonlinear solver options (e.g., CVodeSetMaxNonlinIters()) or getting nonlinear solver statistics (e.g., CVodeGetNumNonlinSolvIters()) remain unchanged and internally call generic SUNNonlinearSolver functions as needed.

Three fused vector operations and seven vector array operations have been added to the N_Vector API. These optional operations are disabled by default and may be activated by calling vector specific routines after creating an N_Vector (see §9 for more details). The new operations are intended to increase data reuse in vector operations, reduce parallel communication on distributed memory systems, and lower the number of kernel launches on systems with accelerators. The fused operations are N_VLinearCombination(), N_VScaleAddMulti(), and N_VDotProdMulti() and the vector array operations are N_VLinearCombinationVectorArray(), N_VScaleVectorArray(), N_VConstVectorArray(), N_VWrmsNormVectorArray(), N_VWrmsNormMaskVectorArray(), and N_VScaleAddMultiVectorArray(). If an N_Vector implementation defines any of these operations as, then standard N_Vector operations will automatically be called as necessary to complete the computation.

Multiple updates to NVECTOR_CUDA were made:

Changed to return the global vector length instead of the local vector length.
Added to return the local vector length.
Added to return the MPI communicator used.
Removed the accessor functions in the namespace suncudavec.
Changed the function to take a host data pointer and a device data pointer instead of an object.
Added the ability to set the used for execution of the NVECTOR_CUDA kernels. See the function N_VSetCudaStream_Cuda().
Added N_VNewManaged_Cuda(), N_VMakeManaged_Cuda(), and N_VIsManagedMemory_Cuda() functions to accommodate using managed memory with NVECTOR_CUDA.

Multiple changes to NVECTOR_RAJA were made:

Changed to return the global vector length instead of the local vector length.

Added to return the local vector length.

Added to return the MPI communicator used.

Removed the accessor functions in the namespace suncudavec.

A new N_Vector implementation for leveraging OpenMP 4.5+ device offloading has been added, NVECTOR_OPENMPDEV.

Two changes were made in the CVODE/CVODES/ARKODE initial step size algorithm:

Fixed an efficiency bug where an extra call to the right hand side function was made.

Changed the behavior of the algorithm if the max-iterations case is hit. Before the algorithm would exit with the step size calculated on the penultimate iteration. Now it will exit with the step size calculated on the final iteration.

A Fortran 2003 interface to CVODE has been added along with Fortran 2003 interfaces to the following shared SUNDIALS modules:

SUNNONLINSOL_FIXEDPOINT and SUNNONLINSOL_NEWTON nonlinear solver modules

SUNLINSOL_BAND, SUNLINSOL_DENSE, SUNLINSOL_KLU, SUNLINSOL_PCG, SUNLINSOL_SPBCGS, SUNLINSOL_SPFGMR, SUNLINSOL_SPGMR, and SUNLINSOL_SPTFQMR linear solver modules

NVECTOR_SERIAL, NVECTOR_PTHREADS, and NVECTOR_OPENMP vector modules

4.1.2.23. Changes in v3.2.1

The changes in this minor release include the following:

Fixed a bug in the CUDA N_Vector where the operation could write beyond the allocated vector data.
Fixed library installation path for multiarch systems. This fix changes the default library installation path to CMAKE_INSTALL_PREFIX/CMAKE_INSTALL_LIBDIR from CMAKE_INSTALL_PREFIX/lib. CMAKE_INSTALL_LIBDIR is automatically set, but is available as a CMake option that can modified.

4.1.2.24. Changes in v3.2.0

Support for optional inequality constraints on individual components of the solution vector has been added to CVODE and CVODES. See §4.2 and the description of in §4.4.5.10 for more details. Use of CVodeSetConstraints() requires the N_Vector operations N_VMinQuotient(), N_VConstMask(), and N_VCompare() that were not previously required by CVODE and CVODES.

Fixed a problem with setting which would occur with some compilers (e.g. armclang) that did not define __STDC_VERSION__.

Added hybrid MPI/CUDA and MPI/RAJA vectors to allow use of more than one MPI rank when using a GPU system. The vectors assume one GPU device per MPI rank.

Changed the name of the RAJA N_Vector library to from to better reflect that we only support CUDA as a backend for RAJA currently.

Several changes were made to the build system:

CMake 3.1.3 is now the minimum required CMake version.

Deprecate the behavior of the CMake option and added the CMake option to select the integer size.

The native CMake FindMPI module is now used to locate an MPI installation.

If MPI is enabled and MPI compiler wrappers are not set, the build system will check if can compile MPI programs before trying to locate and use an MPI installation.

The previous options for setting MPI compiler wrappers and the executable for running MPI programs have been have been depreated. The new options that align with those used in native CMake FindMPI module are MPI_C_COMPILER, MPO_CXX_COMPILER, MPI_Fortran_COMPILER, and MPIEXEC_EXECUTABLE.

When a Fortran name-mangling scheme is needed (e.g., is ) the build system will infer the scheme from the Fortran compiler. If a Fortran compiler is not available or the inferred or default scheme needs to be overridden, the advanced options and can be used to manually set the name-mangling scheme and bypass trying to infer the scheme.

Parts of the main CMakeLists.txt file were moved to new files in the and directories to make the CMake configuration file structure more modular.

4.1.2.25. Changes in v3.1.2

The changes in this minor release include the following:

Updated the minimum required version of CMake to 2.8.12 and enabled using rpath by default to locate shared libraries on OSX.
Fixed Windows specific problem where was not correctly defined when using 64-bit integers for the SUNDIALS index type. On Windows sunindextype is now defined as the MSVC basic type __int64.
Added sparse SUNMatrix “Reallocate” routine to allow specification of the nonzero storage.
Updated the KLU SUNLinearSolver module to set constants for the two reinitialization types, and fixed a bug in the full reinitialization approach where the sparse SUNMatrix pointer would go out of scope on some architectures.
Updated the “ScaleAdd” and “ScaleAddI” implementations in the sparse SUNMatrix module to more optimally handle the case where the target matrix contained sufficient storage for the sum, but had the wrong sparsity pattern. The sum now occurs in-place, by performing the sum backwards in the existing storage. However, it is still more efficient if the user-supplied Jacobian routine allocates storage for the sum \(I+\gamma J\) manually (with zero entries if needed).
Added the following examples from the usage notes page of the SUNDIALS website, and updated them to work with SUNDIALS 3.x:
- cvDisc_dns.c, which demonstrates using CVODE with discontinuous solutions or RHS.
- cvRoberts_dns_negsol.c, which illustrates the use of the RHS function return value to control unphysical negative concentrations.
Changed the LICENSE install path to instdir/icnlude/sundials.

4.1.2.26. Changes in v3.1.1

The changes in this minor release include the following:

Fixed a minor bug in the cvSLdet routine, where a return was missing in the error check for three inconsistent roots.
Fixed a potential memory leak in the SPGMR and SPFGMR linear solvers: if “Initialize” was called multiple times then the solver memory was reallocated (without being freed).
Updated KLU SUNLinearSolver module to use a for the precision-specific solve function to be used (to avoid compiler warnings).
Added missing typecasts for some pointers (again, to avoid compiler warnings).
Bugfix in sunmatric_sparse.c where we had used instead of in one location.
Added missing #include <stio.h> in N_Vector and SUNMatrix header files.
Fixed an indexing bug in the CUDA N_Vector implementation of and revised the RAJA N_Vector implementation of N_VWrmsNormMask() to work with mask arrays using values other than zero or one. Replaced double with realtype in the RAJA vector test functions.
Fixed compilation issue with GCC 7.3.0 and Fortran programs that do not require a SUNMatrix or SUNLinearSolver module (e.g., iterative linear solvers or fixed-point iteration).

In addition to the changes above, minor corrections were also made to the example programs, build system, and user documentation.

4.1.2.27. Changes in v3.1.0

Added N_Vector print functions that write vector data to a specified file (e.g., N_VPrintFile_Serial()).

Added make test and make test_install options to the build system for testing SUNDIALS after building with and installing with respectively.

4.1.2.28. Changes in v3.0.0

All interfaces to matrix structures and linear solvers have been reworked, and all example programs have been updated. The goal of the redesign of these interfaces was to provide more encapsulation and ease in interfacing custom linear solvers and interoperability with linear solver libraries. Specific changes include:

Added generic SUNMATRIX module with three provided implementations: dense, banded and sparse. These replicate previous SUNDIALS Dls and Sls matrix structures in a single object-oriented API.
Added example problems demonstrating use of generic SUNMATRIX modules.
Added generic SUNLINEARSOLVER module with eleven provided implementations: dense, banded, LAPACK dense, LAPACK band, KLU, SuperLU_MT, SPGMR, SPBCGS, SPTFQMR, SPFGMR, PCG. These replicate previous SUNDIALS generic linear solvers in a single object-oriented API.
Added example problems demonstrating use of generic SUNLINEARSOLVER modules.
Expanded package-provided direct linear solver (Dls) interfaces and scaled, preconditioned, iterative linear solver (Spils) interfaces to utilize generic SUNMATRIX and SUNLINEARSOLVER objects.
Removed package-specific, linear solver-specific, solver modules (e.g. CVDENSE, KINBAND, IDAKLU, ARKSPGMR) since their functionality is entirely replicated by the generic Dls/Spils interfaces and SUNLINEARSOLVER/SUNMATRIX modules. The exception is CVDIAG, a diagonal approximate Jacobian solver available to CVODE and CVODES.
Converted all SUNDIALS example problems to utilize new generic SUNMATRIX and SUNLINEARSOLVER objects, along with updated Dls and Spils linear solver interfaces.
Added Spils interface routines to ARKode, CVODE, CVODES, IDA and IDAS to allow specification of a user-provided “JTSetup” routine. This change supports users who wish to set up data structures for the user-provided Jacobian-times-vector (“JTimes”) routine, and where the cost of one JTSetup setup per Newton iteration can be amortized between multiple JTimes calls.

Two additional N_Vector implementations were added – one for CUDA and one for RAJA vectors. These vectors are supplied to provide very basic support for running on GPU architectures. Users are advised that these vectors both move all data to the GPU device upon construction, and speedup will only be realized if the user also conducts the right-hand-side function evaluation on the device. In addition, these vectors assume the problem fits on one GPU. Further information about RAJA, users are referred to th web site, https://software.llnl.gov/RAJA/. These additions are accompanied by additions to various interface functions and to user documentation.

All indices for data structures were updated to a new sunindextype that can be configured to be a 32- or 64-bit integer data index type. sunindextype is defined to be int32_t or int64_t when portable types are supported, otherwise it is defined as int or long int. The Fortran interfaces continue to use for indices, except for their sparse matrix interface that now uses the new . This new flexible capability for index types includes interfaces to PETSc, hypre, SuperLU_MT, and KLU with either 32-bit or 64-bit capabilities depending how the user configures SUNDIALS.

To avoid potential namespace conflicts, the macros defining booleantype values TRUE and FALSE have been changed to SUNTRUE and SUNFALSE respectively.

Temporary vectors were removed from preconditioner setup and solve routines for all packages. It is assumed that all necessary data for user-provided preconditioner operations will be allocated and stored in user-provided data structures.

The file include/sundials_fconfig.h was added. This file contains SUNDIALS type information for use in Fortran programs.

Added functions SUNDIALSGetVersion() and SUNDIALSGetVersionNumber() to get SUNDIALS release version information at runtime.

The build system was expanded to support many of the xSDK-compliant keys. The xSDK is a movement in scientific software to provide a foundation for the rapid and efficient production of high-quality, sustainable extreme-scale scientific applications. More information can be found at, https://xsdk.info.

In addition, numerous changes were made to the build system. These include the addition of separate BLAS_ENABLE and BLAS_LIBRARIES CMake variables, additional error checking during CMake configuration, minor bug fixes, and renaming CMake options to enable/disable examples for greater clarity and an added option to enable/disable Fortran 77 examples. These changes included changing EXAMPLES_ENABLE to EXAMPLES_ENABLE_C, changing CXX_ENABLE to EXAMPLES_ENABLE_CXX, changing F90_ENABLE to EXAMPLES_ENABLE_F90, and adding an EXAMPLES_ENABLE_F77 option.

A bug fix was made in CVodeFree() to call lfree unconditionally (if non-NULL).

Corrections and additions were made to the examples, to installation-related files, and to the user documentation.

4.1.2.29. Changes in v2.9.0

Two additional N_Vector implementations were added – one for Hypre (parallel) ParVector vectors, and one for PETSc vectors. These additions are accompanied by additions to various interface functions and to user documentation.

Each N_Vector module now includes a function, N_VGetVectorID(), that returns the N_Vector module name.

For each linear solver, the various solver performance counters are now initialized to 0 in both the solver specification function and in solver linit function. This ensures that these solver counters are initialized upon linear solver instantiation as well as at the beginning of the problem solution.

In FCVODE, corrections were made to three Fortran interface functions. Missing Fortran interface routines were added so that users can supply the sparse Jacobian routine when using sparse direct solvers.

A memory leak was fixed in the banded preconditioner interface. In addition, updates were done to return integers from linear solver and preconditioner ’free’ functions.

The Krylov linear solver Bi-CGstab was enhanced by removing a redundant dot product. Various additions and corrections were made to the interfaces to the sparse solvers KLU and SuperLU_MT, including support for CSR format when using KLU.

New examples were added for use of the OpenMP vector and for use of sparse direct solvers from Fortran.

Minor corrections and additions were made to the CVODE solver, to the Fortran interfaces, to the examples, to installation-related files, and to the user documentation.

4.1.2.30. Changes in v2.8.0

Two major additions were made to the linear system solvers that are available for use with the CVODE solver. First, in the serial case, an interface to the sparse direct solver KLU was added. Second, an interface to SuperLU_MT, the multi-threaded version of SuperLU, was added as a thread-parallel sparse direct solver option, to be used with the serial version of the N_Vector module. As part of these additions, a sparse matrix (CSC format) structure was added to CVODE.

Otherwise, only relatively minor modifications were made to the CVODE solver:

In cvRootFind, a minor bug was corrected, where the input array was ignored, and a line was added to break out of root-search loop if the initial interval size is below the tolerance ttol.

In CVLapackBand, the line smu = MIN(N-1,mu+ml) was changed to to correct an illegal input error for DGBTRF/DGBTRS.

In order to eliminate or minimize the differences between the sources for private functions in CVODE and CVODES, the names of 48 private functions were changed from to , and a few other names were also changed.

Two minor bugs were fixed regarding the testing of input on the first call to – one involving and one involving the initialization of *tret.

In order to avoid possible name conflicts, the mathematical macro and function names MIN, MAX, SQR, RAbs, RSqrt, RExp, RPowerI, and were changed to SUNMIN, SUNMAX, SUNSQR, SUNRabs, SUNRsqrt, SUNRexp, SUNRpowerI, and SUNRPowerR respectively. These names occur in both the solver and in various example programs.

The example program cvAdvDiff_diag_p was added to illustrate the use of in parallel.

In the FCVODE optional input routines FCVSETIIN and FCVSETRIN, the optional fourth argument key_length was removed, with hardcoded key string lengths passed to all tests.

In all FCVODE examples, integer declarations were revised so that those which must match a C type long int are declared INTEGER*8, and a comment was added about the type match. All other integer declarations are just INTEGER. Corresponding minor corrections were made to the user guide.

Two new N_Vector modules have been added for thread-parallel computing environments — one for OpenMP, denoted NVECTOR_OPENMP, and one for Pthreads, denoted NVECTOR_PTHREADS.

With this version of SUNDIALS, support and documentation of the Autotools mode of installation is being dropped, in favor of the CMake mode, which is considered more widely portable.

4.1.2.31. Changes in v2.7.0

One significant design change was made with this release: The problem size and its relatives, bandwidth parameters, related internal indices, pivot arrays, and the optional output lsflag have all been changed from type int to type long int, except for the problem size and bandwidths in user calls to routines specifying BLAS/LAPACK routines for the dense/band linear solvers. The function NewIntArray is replaced by a pair NewIntArray / NewLintArray, for int and long int arrays, respectively.

A large number of minor errors have been fixed. Among these are the following: In , the logic was changed to avoid a divide by zero. After the solver memory is created, it is set to zero before being filled. In CVSetTqBDF each linear solver interface function, the linear solver memory is freed on an error return, and the function now includes a line setting to NULL the main memory pointer to the linear solver memory. In the rootfinding functions CVRcheck1/ CVRcheck2, when an exact zero is found, the array glo of \(g\) values at the left endpoint is adjusted, instead of shifting the \(t\) location slightly. In the installation files, we modified the treatment of the macro SUNDIALS_USE_GENERIC_MATH, so that the parameter GENERIC_MATH_LIB is either defined (with no value) or not defined.

4.1.2.32. Changes in v2.6.0

Two new features were added in this release: (a) a new linear solver module, based on BLAS and LAPACK for both dense and banded matrices, and (b) an option to specify which direction of zero-crossing is to be monitored while performing rootfinding.

The user interface has been further refined. Some of the API changes involve: (a) a reorganization of all linear solver modules into two families (besides the existing family of scaled preconditioned iterative linear solvers, the direct solvers, including the new LAPACK-based ones, were also organized into a direct family); (b) maintaining a single pointer to user data, optionally specified through a -type function; and (c) a general streamlining of the preconditioner modules distributed with the solver.

4.1.2.33. Changes in v2.5.0

The main changes in this release involve a rearrangement of the entire SUNDIALS source tree. At the user interface level, the main impact is in the mechanism of including SUNDIALS header files which must now include the relative path (e.g. #include <cvode/cvode.h>). Additional changes were made to the build system: all exported header files are now installed in separate subdirectories of the instaltion include directory.

The functions in the generic dense linear solver (sundials_dense and sundials_smalldense) were modified to work for rectangular \(m \times n\) matrices (\(m \le n\)), while the factorization and solution functions were renamed to DenseGETRF / denGETRF and DenseGETRS / denGETRS, respectively. The factorization and solution functions in the generic band linear solver were renamed BandGBTRF and BandGBTRS, respectively.

4.1.2.34. Changes in v2.4.0

CVSPBCG and CVSPTFQMR modules have been added to interface with the Scaled Preconditioned Bi-CGstab (SPBCG) and Scaled Preconditioned Transpose-Free Quasi-Minimal Residual (SPTFQMR) linear solver modules, respectively (for details see §4.4). Corresponding additions were made to the Fortran interface module FCVODE. At the same time, function type names for Scaled Preconditioned Iterative Linear Solvers were added for the user-supplied Jacobian-times-vector and preconditioner setup and solve functions.

The deallocation functions now take as arguments the address of the respective memory block pointer.

To reduce the possibility of conflicts, the names of all header files have been changed by adding unique prefixes (cvode_ and sundials_). When using the default installation procedure, the header files are exported under various subdirectories of the target directory. For more details see §14.

4.1.2.35. Changes in v2.3.0

The user interface has been further refined. Several functions used for setting optional inputs were combined into a single one. An optional user-supplied routine for setting the error weight vector was added. Additionally, to resolve potential variable scope issues, all SUNDIALS solvers release user data right after its use. The build systems has been further improved to make it more robust.

4.1.2.36. Changes in v2.2.1

The changes in this minor SUNDIALS release affect only the build system.

4.1.2.37. Changes in v2.2.0

The major changes from the previous version involve a redesign of the user interface across the entire SUNDIALS suite. We have eliminated the mechanism of providing optional inputs and extracting optional statistics from the solver through the and arrays. Instead, CVODE now provides a set of routines (with prefix CVodeSet) to change the default values for various quantities controlling the solver and a set of extraction routines (with prefix CVodeGet) to extract statistics after return from the main solver routine. Similarly, each linear solver module provides its own set of - and -type routines. For more details see §4.4.5.10 and §4.4.5.12.

Additionally, the interfaces to several user-supplied routines (such as those providing Jacobians and preconditioner information) were simplified by reducing the number of arguments. The same information that was previously accessible through such arguments can now be obtained through -type functions.

The rootfinding feature was added, whereby the roots of a set of given functions may be computed during the integration of the ODE system.

Installation of CVODE (and all of SUNDIALS) has been completely redesigned and is now based on configure scripts.

4.1.3. Reading this User Guide

This user guide is a combination of general usage instructions. Specific example programs are provided as a separate document. We expect that some readers will want to concentrate on the general instructions, while others will refer mostly to the examples, and the organization is intended to accommodate both styles.

There are different possible levels of usage of CVODE. The most casual user, with a small IVP problem only, can get by with reading §4.2.1, then §4.4 through §4.4.5.9 only, and looking at examples in [66].

In a different direction, a more expert user with an IVP problem may want to (a) use a package preconditioner (§4.4.7), (b) supply his/her own Jacobian or preconditioner routines (§4.4.6.7), (c) do multiple runs of problems of the same size (§4.4.5.13), (d) supply a new N_Vector module (§9), (e) supply new SUNLinearSolver and/or SUNMatrix modules (§10 and §11), or even (f) supply new SUNNonlinearSolver modules (§12).

The structure of this document is as follows:

In §4.2, we give short descriptions of the numerical methods implemented by CVODE for the solution of initial value problems for systems of ODEs, and continue with short descriptions of preconditioning (§4.2.3), stability limit detection (§4.2.4), and rootfinding (§4.2.5).
The following chapter describes the structure of the SUNDIALS suite of solvers (§4.3) and the software organization of the CVODE solver (§4.3.1).
§4.4 is the main usage document for CVODE for C applications. It includes a complete description of the user interface for the integration of ODE initial value problems.
In §2.5, we describe the use of CVODE with Fortran applications.
§9 gives a brief overview of the generic N_Vector module shared among the various components of SUNDIALS, and details on the N_Vector implementations provided with SUNDIALS.
§10 gives a brief overview of the generic SUNMatrix module shared among the various components of SUNDIALS, and details on the SUNMatrix implementations provided with SUNDIALS: a dense implementation (§10.9), a banded implementation (§10.12) and a sparse implementation (§10.14).
§11 gives a brief overview of the generic SUNLinearSolver module shared among the various components of SUNDIALS. This chapter contains details on the SUNLinearSolver implementations provided with SUNDIALS. The chapter also contains details on the SUNLinearSolver implementations provided with SUNDIALS that interface with external linear solver libraries.
§12 describes the SUNNonlinearSolver API and nonlinear solver implementations shared among the various components of SUNDIALS.
Finally, in the appendices, we provide detailed instructions for the installation of CVODE, within the structure of SUNDIALS (§14), as well as a list of all the constants used for input to and output from CVODE functions (§4.5).

Finally, the reader should be aware of the following notational conventions in this user guide: program listings and identifiers (such as CVodeInit()) within textual explanations are hyperlinked to their definitions directly; fields in C structures (such as content) appear in italics; and packages or modules, such as CVLS, are written in all capitals.

4.1.4. SUNDIALS License and Notices

All SUNDIALS packages are released open source, under the BSD 3-Clause license for more details see the LICENSE and NOTICE files provided with all SUNDIALS packages.

4.1.5. Acknowledgments

We wish to acknowledge the contributions to previous versions of the CVODE and PVODE codes and their user guides by Scott D. Cohen [36] and George D. Byrne [29].