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- update to 5.7.0:
  * A new NVECTOR 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 the SYCL NVECTOR section in the user guide for
    more details. This module is considered experimental and is subject to major
    changes even in minor releases.
  * A new SUNMatrix and SUNLinearSolver implementation 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).
  * 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.
  * A new NVECTOR implementation based on the AMD ROCm HIP platform has been added.
    This vector can target NVIDIA or AMD GPUs. See HIP NVECTOR section in the user
    guide for more details. This module is considered experimental and is subject
    to change from version to version.
  * The RAJA NVECTOR 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.

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* Update to version 5.5.0.
* Add sundials-link-pthread.patch: Link against pthread explicitly to fix linking errors when `-Wl,--no-undefined` is added to the linker flags; patch sent upstream.
* Add BuildRequires: suitesparse-devel and enable KLU solver; pass appropriate options to cmake to make sure the klu library and header is correctly found.
* Use cmake macros instead of manual cmake commands.
* Split out new libsundials_generic package with the libsundials_generic shared library.
* Enable openmpi4 flavour.
* Run tests except for tests that fail due to floating point errors in the tests themselves.
* Drop Group tags.

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* Update to version 5.3.0.
* Pass SUNDIALS_BUILD_WITH_MONITORING=ON to cmake to enable monitoring the solve phase in different iterative solver modules.

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- Update to version 5.2.0 (See
  https://computing.llnl.gov/projects/sundials/release-history for
  details):
  - Fixed a bug in how ARKode interfaces with a user-supplied,
    iterative, unscaled linear solver.
  - Fixed a bug in how ARKode interfaces with a user-supplied,
    iterative, unscaled linear solver.
  - Fixed a similar bug in how ARKode interfaces with scaled
    linear solvers when solving problems with non-identity mass
    matrices.
  - Fixed a memory leak in CVODES and IDAS from not deallocating
    the atolSmin0 and atolQSmin0 arrays.
  - Fixed a bug where a non-default value for the maximum allowed
    growth factor after the first step would be ignored.
  - Functions were added to each of the time integration packages
    to enable or disable the scaling applied to linear system
    solutions with matrix-based linear solvers to account for
    lagged matrix information.
  - Added two new functions, ARKStepSetMinReduction() and
    ERKStepSetMinReduction() to change the minimum allowed step
    size reduction factor after an error test failure.
  - Added a new SUNMatrix implementation, SUNMATRIX_CUSPARSE, that
    interfaces to the sparse matrix implementation from the NVIDIA
    cuSPARSE library.
  - Added a new "stiff" interpolation module to ARKode, based on
    Lagrange polynomial interpolation, that is accessible to each
    of the ARKStep, ERKStep and MRIStep time-stepping modules.

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- Remove duplicated definitions.
- Remove bogus undefines of suffix and mpi_flavor for "serial"
  flavour. The former causes builds to fail for openSUSE >= 1550
  using rpm >= 4.15.

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initialized devel package after accepting 746535

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- Run spec-cleaner for minor cleanups.
- Update to version 5.0.0:
- Merge all nvec solver libraries into a single shared lib package: %{shlib_nvec}.

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- Enable multibuild with serial, openmpi1, openmpi2, openmpi3,
  and mvapich2 flavours.

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- Follow shared library packaging policy and split out multiple
  versioned shlib packages. The main shared lib %{shlib_main}
  contains the common shared objects, while each individual solver
  gets its own shared lib package.
- Add blas-devel and lapack-devel BuildRequires; enable blas and
  lapack (does not work with 64 bits) during cmake.
- Enable pthread.

- Update to version 4.1.0:
  * An additional N_Vector implementation was added for Tpetra
    vector from 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 EXAMPLES_ENABLE_RAJA CMake option has been removed. The
    option EXAMPLES_ENABLE_CUDA enables all examples that use CUDA
    including the RAJA examples with a CUDA back end (if the RAJA
    NVECTOR is enabled).
  * The implementation header files (e.g. arkode_impl.h) are no
    longer installed. This means users who are directly
    manipulating package memory structures will need to update
    their code to use the package’s public API.
  * Python is no longer required to run make test and make
    test_install.
  * Fixed a bug in ARKodeButcherTable_Write when printing a
    Butcher table without an embedding. 
- Changes between previously packaged version (2.5.0) through
  version 4.0.2:

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