Tags: YangWang92/ginkgo

Minor release v1.1.1.

This version of Ginkgo provides a few fixes in Ginkgo's core routines. The
supported systems and requirements are unchanged from version 1.1.0.

+ Improve Ginkgo's installation and fix the `test_install` step ([ginkgo-project#406](ginkgo-project#406)),
+ Fix some documentation issues ([ginkgo-project#406](ginkgo-project#406)),
+ Fix multiple code issues reported by sonarqube ([ginkgo-project#406](ginkgo-project#406)),
+ Update the git-cmake-format repository ([ginkgo-project#399](ginkgo-project#399)),
+ Improve the global update header script ([ginkgo-project#390](ginkgo-project#390)),
+ Fix broken bounds checks ([ginkgo-project#388](ginkgo-project#388)),
+ Fix CSR strategies and improve performance ([ginkgo-project#379](ginkgo-project#379)),
+ Fix a small typo in the stencil examples ([ginkgo-project#381](ginkgo-project#381)),
+ Fix ELL error on small matrices ([ginkgo-project#375](ginkgo-project#375)),
+ Fix SellP read function ([ginkgo-project#374](ginkgo-project#374)),
+ Add factorization support in `create_new_algorithm.sh`  ([ginkgo-project#371](ginkgo-project#371))

Ginkgo version 1.1.0.

The Ginkgo team is proud to announce the new minor release of Ginkgo version
1.1.0. This release brings several performance improvements, adds Windows support,
adds support for factorizations inside Ginkgo and a new ILU preconditioner
based on ParILU algorithm, among other things. For detailed information, check the respective issue.

Supported systems and requirements:
+ For all platforms, cmake 3.9+
+ Linux and MacOS
  + gcc: 5.3+, 6.3+, 7.3+, 8.1+
  + clang: 3.9+
  + Intel compiler: 2017+
  + Apple LLVM: 8.0+
  + CUDA module: CUDA 9.0+
+ Windows
  + MinGW and CygWin: gcc 5.3+, 6.3+, 7.3+, 8.1+
  + Microsoft Visual Studio: VS 2017 15.7+
  + CUDA module: CUDA 9.0+, Microsoft Visual Studio
  + OpenMP module: MinGW or Cygwin.

The current known issues can be found in the [known issues
page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues).

Additions:
+ Upper and lower triangular solvers ([ginkgo-project#327](ginkgo-project#327), [ginkgo-project#336](ginkgo-project#336), [ginkgo-project#341](ginkgo-project#341), [ginkgo-project#342](ginkgo-project#342))
+ New factorization support in Ginkgo, and addition of the ParILU
  algorithm ([ginkgo-project#305](ginkgo-project#305), [ginkgo-project#315](ginkgo-project#315), [ginkgo-project#319](ginkgo-project#319), [ginkgo-project#324](ginkgo-project#324))
+ New ILU preconditioner ([ginkgo-project#348](ginkgo-project#348), [ginkgo-project#353](ginkgo-project#353))
+ Windows MinGW and Cygwin support ([ginkgo-project#347](ginkgo-project#347))
+ Windows Visual Studio support ([ginkgo-project#351](ginkgo-project#351))
+ New example showing how to use ParILU as a preconditioner ([ginkgo-project#358](ginkgo-project#358))
+ New example on using loggers for debugging ([ginkgo-project#360](ginkgo-project#360))
+ Add two new 9pt and 27pt stencil examples ([ginkgo-project#300](ginkgo-project#300), [ginkgo-project#306](ginkgo-project#306))
+ Allow benchmarking CuSPARSE spmv formats through Ginkgo's benchmarks ([ginkgo-project#303](ginkgo-project#303))
+ New benchmark for sparse matrix format conversions ([ginkgo-project#312](https://github.com/ginkgo-project/ginkgo/issues/312)[#317](https://github.com/ginkgo-project/ginkgo/issues/317))
+ Add conversions between CSR and Hybrid formats ([ginkgo-project#302](ginkgo-project#302), [ginkgo-project#310](ginkgo-project#310))
+ Support for sorting rows in the CSR format by column idices ([ginkgo-project#322](ginkgo-project#322))
+ Addition of a CUDA COO SpMM kernel for improved performance ([ginkgo-project#345](ginkgo-project#345))
+ Addition of a LinOp to handle perturbations of the form (identity + scalar *
  basis * projector) ([ginkgo-project#334](ginkgo-project#334))
+ New sparsity matrix representation format with Reference and OpenMP
  kernels ([ginkgo-project#349](ginkgo-project#349), [ginkgo-project#350](ginkgo-project#350))

Fixes:
+ Accelerate GMRES solver for CUDA executor ([ginkgo-project#363](ginkgo-project#363))
+ Fix BiCGSTAB solver convergence ([ginkgo-project#359](ginkgo-project#359))
+ Fix CGS logging by reporting the residual for every sub iteration ([ginkgo-project#328](ginkgo-project#328))
+ Fix CSR,Dense->Sellp conversion's memory access violation ([ginkgo-project#295](ginkgo-project#295))
+ Accelerate CSR->Ell,Hybrid conversions on CUDA ([ginkgo-project#313](ginkgo-project#313), [ginkgo-project#318](ginkgo-project#318))
+ Fixed slowdown of COO SpMV on OpenMP ([ginkgo-project#340](ginkgo-project#340))
+ Fix gcc 6.4.0 internal compiler error ([ginkgo-project#316](ginkgo-project#316))
+ Fix compilation issue on Apple clang++ 10 ([ginkgo-project#322](ginkgo-project#322))
+ Make Ginkgo able to compile on Intel 2017 and above ([ginkgo-project#337](ginkgo-project#337))
+ Make the benchmarks spmv/solver use the same matrix formats ([ginkgo-project#366](ginkgo-project#366))
+ Fix self-written isfinite function ([ginkgo-project#348](ginkgo-project#348))
+ Fix Jacobi issues shown by cuda-memcheck

Tools and ecosystem:
+ Multiple improvements to the CI system and tools ([ginkgo-project#296](ginkgo-project#296), [ginkgo-project#311](ginkgo-project#311), [ginkgo-project#365](ginkgo-project#365))
+ Multiple improvements to the Ginkgo containers ([ginkgo-project#328](ginkgo-project#328), [ginkgo-project#361](ginkgo-project#361))
+ Add sonarqube analysis to Ginkgo ([ginkgo-project#304](ginkgo-project#304), [ginkgo-project#308](ginkgo-project#308), [ginkgo-project#309](ginkgo-project#309))
+ Add clang-tidy and iwyu support to Ginkgo ([ginkgo-project#298](ginkgo-project#298))
+ Improve Ginkgo's support of xSDK M12 policy by adding the `TPL_` arguments
  to CMake ([ginkgo-project#300](ginkgo-project#300))
+ Add support for the xSDK R7 policy ([ginkgo-project#325](ginkgo-project#325))
+ Fix examples in html documentation ([ginkgo-project#367](ginkgo-project#367))

First release of Ginkgo, version 1.0.0.

The Ginkgo team is proud to announce the first release of Ginkgo, the
next-generation high-performance on-node sparse linear algebra library. Ginkgo
leverages the features of modern C++ to give you a tool for the iterative
solution of linear systems that is:

* Easy to use. Interfaces with cryptic naming schemes and dozens of parameters
  are a thing of the past. Ginkgo was built with good software design in mind,
  making simple things simple to express.
* High performance. Our optimized CUDA kernels ensure you are reaching the
  potential of today's GPU-accelerated high-end systems, while Ginkgo's open
  design allows extension to future hardware architectures.
* Controllable.  While Ginkgo can automatically move your data when needed, you
  remain in control by optionally specifying when the data is moved and what is
  its ownership scheme.
* Composable. Iterative solution of linear systems is an extremely versatile
  field, where effective methods are built by mixing and matching various
  components. Need a GMRES solver preconditioned with a block-Jacobi enhanced
  BiCGSTAB? Thanks to its novel linear operator abstraction, Ginkgo can do it!
* Extensible. Did not find a component you were looking for? Ginkgo is designed
  to be easily extended in various ways. You can provide your own loggers,
  stopping criteria, matrix formats, preconditioners and solvers to Ginkgo and
  have them integrate as well as the natively supported ones, without the need
  to modify or recompile the library.

For more details, access the release notes on Github:
https://github.com/ginkgo-project/ginkgo/releases