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ChangeLog.md

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pastix-6.0.2

  • Integrate the clusting strategies developped for low-rank (See https://hal.inria.fr/hal-01961675)
  • Restructure the ordering/symbolic factorization code to make sure with exit the ordering step with permutation, partition, and elimination tree.
  • Relook the splitting/proportional mapping strategy
  • Add new compression kernels: PQRCP, RQRCP, and TQRCP
  • Fix inplace compilation (Issue #36)
  • Fix issue when StarPU threads where fighting for ressources with PaStiX threads (Add pause/resume calls)
  • Handle multi-dof static and/or variable in the analysis steps

pastix-6.0.1

  • Support for HWLOC 2.0.0
  • Move the SPM library as a submodule
  • Parallel (multithreaded) version of the reordering step
  • Parallel (multithreaded) version of the refinement steps
  • StarPU version of the solve step
  • Fix Python/Fortran interface
  • Fix Schur functions
  • Fix multi-RHS solve
  • Fix for METIS
  • Update morse_cmake FindPACKAGE
  • Update PaRSEC for release 6.0.1
  • Improve PKG-CONFIG
  • Improve documentation
  • Better handle of disconnected graphs
  • Add optimal reordering for grids
  • Add more detailed statistics during analysis step
  • Add detailed statistics about memory gain for the low-rank solver
  • Add a function to compress the solver matrix outside the factorization step
  • Add an example to dump the symbol matrix including the ranks of the block
  • Add an refinement driver and testings
  • Add a subtask_refine which does not perform the vector ordering
  • Add a more complex testing based on example proposed by @andrea3.14
  • Add an iparm IPARM_APPLYPERM_WS to enable/disable the use of an extra workspace to make the functions bvec_xlapmr thread-safe (by default, it is enabled, if disabled, the functions have no memory overhead but loose the thread-safe property)
  • Remove the sparse-kit package to avoid conflict (the driver is replaced by HB)

pastix-6.0.0

  • low-rank compression (See https://hal.inria.fr/hal-01824275)
  • static scheduler, PaRSEC and StarPU runtime support
  • GPUs (Kepler) and KNL support through runtime systems