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Release 0.7.0 (#553)
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* up-ed the version number

* release notes in CHANGELOG.md

* user manual pdf
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cnpetra committed Sep 30, 2022
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11 changes: 9 additions & 2 deletions CHANGELOG.md
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# Change Log
All notable changes to HiOp are documented in this file.

## Version 0.7.0: Fortran interface and misc fixes and improvements:
- Fortran interface and examples
- Bug fixing for sparse device linear solvers
- Implementation of CUDA CSR matrices
- Iterative refinement within CUSOLVER linear solver class
- Improved robustness and performance of mixed dense-sparse solver for AMD/HIP

## Version 0.6.2: Initial ginkgo solver integration and misc fixes
This tag provides an initial integration with ginko, fixes a couple of issues, and add options for (outer) iterative refinement.

## Version 0.6.1: HIP linear algebra workaround and update for RAJA > v0.14 (March 31, 2022)
This version/tag provides a workaround for an issue in the HIP BLAS and updates the RAJA code to better operate with the newer versions of RAJA.

## Version 0.6.0: Release of the PriDec optimization and improved GPU computations (March 31, 2022)
The salient features of v0.6.0 are
The salient features of v0.6.0 are

- the release of the primal decomposition (PriDec) solver for structured two-stage problems
- the release of the primal decomposition (PriDec) solver for structured two-stage problems
- improved support for (NVIDIA) GPUs for solving sparse optimization problems via NVIDIA's cuSOLVER API and newly developed condensed optimization kernels.

Other notable capabilities include
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2 changes: 1 addition & 1 deletion CMakeLists.txt
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cmake_policy(SET CMP0074 NEW)
endif ()

project (hiop VERSION "0.6.2")
project (hiop VERSION "0.7.0")

string(TIMESTAMP HIOP_RELEASE_DATE "%Y-%m-%d")

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11 changes: 8 additions & 3 deletions doc/src/techrep_main.tex
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\vspace{3cm}

{\huge\bfseries \Hi\ -- User Guide} \\[14pt]
{\large\bfseries version 0.6}
{\large\bfseries version 0.7}

\vspace{3cm}

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\vspace{4.75cm}

\textcolor{violet}{{\large\bfseries Oct 15, 2017} \\
{\large\bfseries Updated Sep 01, 2022}}
{\large\bfseries Updated Sep 30, 2022}}

\vspace{0.75cm}

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Starting version 0.6, \Hi offers support for offloading computations to AMD GPU accelerators when solving NLPs in the mixed dense-sparse (MDS) form. Support for HIP should be enabled during the build by using \texttt{cmake} options \texttt{-DHIOP\_USE\_GPU} and \texttt{-DHIOP\_USE\_HIP}, which will result in using the HIP accelerators for the internal linear solves.

\Hi's \texttt{cmake} build system is quite versatile to find the dependencies required to offload computations to the device GPUs since was developed and tested on a few GPU-enabled HPC platforms at Oak Ridge, Lawrence Livermore, and Pacific Northwest National Laboratories. These dependencies consist of CUDA library version 10.1 or later, rocm library version 4.5.0 or later and a recent Magma linear solver library (as well as a physical NVIDIA/AMD GPU device). \Hi offers an extensive build support for using customized NVIDIA libraries, AMD libraries and/or Magma solver as well as for advanced troubleshooting. The user is referred to \texttt{cmake/FindHiopCudaLibraries.cmake}, \texttt{cmake/FindHiopHipLibraries.cmake} and \texttt{cmake/FindHiOpMagma.cmake} scripts.
\Hi's \texttt{cmake} build system is quite versatile to find the dependencies required to offload computations to the device GPUs since was developed and tested on a few GPU-enabled HPC platforms at Oak Ridge, Lawrence Livermore, and Pacific Northwest National Laboratories. These dependencies consist of CUDA library version 10.1 or later, rocm library version 4.5.0 or later and a recent Magma linear solver library (as well as a physical NVIDIA/AMD GPU device). \Hi offers an extensive build support for using customized NVIDIA libraries, AMD libraries, and/or Magma solver as well as for advanced troubleshooting. The user is referred to the following CMake scripts for more details:
\begin{itemize}
\item \texttt{cmake/FindHiopCudaLibraries.cmake}
\item \texttt{cmake/FindHiopHipLibraries.cmake}
\item \texttt{cmake/FindHiOpMagma.cmake} scripts.
\end{itemize}

\warningcp{Note: } Installing NVIDIA CUDA, AMD HIP, and/or building Magma can be quite challenging. The user is encouraged to rely on preinstalled versions of these, as they are available via \texttt{module} utility on virtually all high-performance computing machines. An example of how to satisfy all the GPU dependencies on Summit supercomputer at Oak Ridge National Lab with a one commands are available at \url{https://github.com/LLNL/hiop/blob/master/README_summit.md}.

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