0.8.1

• Implemented LGMRES solver ("Loose" GMRES, [BaJM05]).
• Implemented FGMRES solver (Flexible GMRES, [Saad03]).
• GMRES uses real residual instead of preconditioned one in termination condition.
• Performance improvements in components using QR decomposition (spai1,
  aggregation with null-space provided).
• Provided python examples.
• Minor bug fixes and improvements.

0.8.0

• Updated two-stage preconditioners
  • Replaced SIMPLE preconditioner with Schur complement pressure correction.
  • Implemented MPI version of Schur complement pressure correction preconditioner.
  • Made CPR preconditioner actually work.
• Breaking changes
  • Renamed amgcl/amgcl.hpp -> amgcl/amg.hpp
• Added support for complex and non-scalar values for coefficients/unknowns.
• Implemented ILU(k) smoother/preconditioner.
• Added MPI block-preconditioner wrapper.
• Introduced mpi::make_solver.
• Allow using make_solver as preconditioner.
• Improve Matrix-Matrix product performance for many-cored CPUs.
• Provide MatrixMarket format I/O functions.
• Generalize profiler class, provide a couple of custom performance counters.
• Improve coarse solution performance on GPGPU backends.
• Allow checking for consistency of runtime parameters.
• Move documentation to http://amgcl.readthedocs.org.
• Various bugfixes and improvements.

0.7.0

This is rather big and an API breaking release!

• All runtime parameters (namely, coarsening type, relaxation type, and solver
  type) were moved to the generic parameter structure (stored in
  boost::property_tree). So the following code:

boost::property_tree::ptree prm;
typedef amgcl::runtime::make_solver< amgcl::backend::builtin<double> > Solver;
Solver S(amgcl::runtime::coarsening::smoothed_aggregation,
     amgcl::runtime::relaxation::spai0,
     amgcl::runtime::solver::bicgstab,
     A, prm);

would have to be changed to

boost::property_tree::ptree prm;
typedef amgcl::runtime::make_solver< amgcl::backend::builtin<double> > Solver;
prm.put("precond.coarsening.type", amgcl::runtime::coarsening::smoothed_aggregation);
prm.put("precond.relaxation.type", amgcl::runtime::relaxation::spai0);
prm.put("solver.type",     amgcl::runtime::solver::bicgstab);
Solver S(A, prm);

This is done as part of the effort to generalize use of preconditioners
in the library, so that any preconditioner supported by AMGCL could be
uniformly constructed with the system matrix and the parameters.

• amg::top_matrix() method was renamed to amg::system_matrix() for the same reason.

• The use of preconditioners in AMGCL was generalized. A class that may be used
  as a preconditioner should have the following properties:

  • Provide public type backend_type for its backend.
  • Provide public type params containing its parameters.
  • Have constructor that takes three arguments:
  • System matrix
  • Parameters
  • Backend parameters
  • Export the system matrix in the backend format through system_matrix()
    method.

  A preconditioner may be used in the following contexts:

  • As a parameter to an iterative solver.
  • As a template parameter to make_solver class.
  • As a template parameter to a two-step preconditioner (CPR and SIMPLE).
  • As a template parameter to subdomain deflation class (as a local preconditioner).

• Added amgcl::as_preconditioner<Backend, Relaxation> and amgcl::runtime::as_preconditioner<Backend>
  wrapper classes that allow to use smoothers as preconditioners.

• Added ILUT(p,tau) smoother/preconditioner.

• Implemented Chow and Patel version of parallel ILU. This allowed to enable
  ILU-type smoothers on all backends, but may not work as well as serial version
  for some problems.

• Provided a wrapper for cuSPARSE implementation of ILU0 on CUDA backend.

• Added adapter for complex-valued matrices. This uses an equivalent real
  formulation (ERF) for the matrix so that it may be solved with AMGCL.

• Added zero copy matrix adapter for CRS matrices. The adapter allows to skip
  copy and thus save some memory for matrices that are binary compatible with
  internal AMGCL storage. Basically, that means that row pointer and column
  number arrays should be either signed or unsigned ptrdiff_t.

• Provided wrapper interface for Fortran.

0.6.4

This is the last release before API-breaking 0.7.0

• Implemented two-step preconditioners for Navier-Stokes type
  problems (CPR and SIMPLE).
• Implemented multicolor Gauss-Seidel smoother
• Get rid of mandatory dependence on std::chrono
• Bug fixes and minor improvements

0.6.3

• Use norm of right-hand side instead of initial error for scaling residuals in
  iterative solvers. This yields consistent results when starting with a decent
  initial approximation.
• Provide an HPX backend.
• Accept near null-space vectors for aggregation-based coarsening.
• Added SPAI(1) smoother (may work better than SPAI(0), but is extremely slow
  to setup for larger problems).
• Iterative solvers now provide apply() methods, so that they may be used as
  preconditioners themselves.
• Various fixes and improvements.

0.6.2

• Added adapter for ublas types.
  Provides amgcl::backend::map() for ublas::compressed_matrix and allows
  to use ublas vectors with builtin backend.
• Moved make_solver parameters into single params struct
  This is an API breaking change!
  This unifies treatment of amg and solver params in amgcl::make_solver,
  amgcl::runtime::make_solver, and amgcl::mpi::subdmain_deflation classes.
  Now, whenever a class contains both an amg hierarchy and an iterative
  solver, the amg parameters may be accessed through the class
  params::amg, and the solver parameters -- through params::solver.
• Fixed pyamgcl for use with python3 and arch linux.

0.6.1

Minor bug fixes

0.6.0

This is a rather big release with lots of new features.

• Added crs_builder backend. The backend is similar to crs_tuple in the sense
  that it is only used for initialization of AMG hierarchy. The difference is
  that crs_builder does not need fully constructed matrix in CRS format (which
  would be copied into AMG anyway), but builds matrix rows as needed. This
  results in reduced memory requirements.
• Implemented MPI solver with subdomain deflation in collaboration with
  @RiccardoRossi. The method allows solution on parallel machines with
  distributed memory and has very good scalability.
• Implemented BiCGStab(L) iterative solver.
• Added an adapter for Epetra_CrsMatrix from Trilinos project.
• Added SkylineLU sparse direct solver. This allows for larger coarse levels in
  builtin backend, which improves convergence and solve time. Again, thanks to
  @RiccardoRossi for help.
• Added classes in amgcl::runtime namespace that allow for runtime
  configuration of multigrid template parameters. This makes AMGCL easy to use
  in 3rd party libraries/applications.
• Provided Delphi wrapper for AMGCL.
• Provided python wrapper for AMGCL. May be installed by
  pip install pyamgcl
• New tests and examples
• Various improvements and bug fixes.

0.5.0 aka v2

This is a major change in the library interface and implementation.
The code base has been rewritten from scratch to decouple various components of
the AMG method, such as backends, coarseners, smoothers, and iterative solvers.

This makes extending the library much easier. See the README for more information.

0.3.2 aka v1

The main purpose of this release is to make a snapshot of the current library API before switching to v2 branch.

Some changes that were made since the last release:

• Added Blaze library backend (https://code.google.com/p/blaze-lib)
• Use Kahan summation in implementation of inner_product for the VexCL backend
• Bug fixes and minor changes