Copyright (C) 2024 Advanced Micro Devices, Inc. All rights reserved.

Copyright (C) 2014, The University of Texas at Austin

AOCL-LAPACK library - Release Notes - version 5.0.0
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AOCL-LAPACK is a high performant implementation of Linear Algebra PACKage
(LAPACK). LAPACK provides routines for solving systems of linear equations,
least-squares problems, eigenvalue problems, singular value problems, and the
associated matrix factorizations. It is extensible, easy to use, and available
under an open-source license. AOCL-LAPACK is a C-only implementation.
Applications relying on standard Netlib LAPACK interfaces can utilize
AOCL-LAPACK with virtually no changes to their source code.
In combination with the AOCL-BLAS library, which includes optimizations for the
AMD “Zen”-based processors, AOCL-LAPACK enables running high performing LAPACK
functionalities on AMD platforms. AOCL-LAPACK supports C, FORTRAN, and C++
template interfaces (for a subset of APIs) for the LAPACK APIs.

Highlights of AMD optimized AOCL-LAPACK 5.0.0
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• Improved performance of following APIs through AVX2 & AVX512 SIMD instructions
  - Double Precision SVD (DGESVD)
  - LU Factorization / Solver routines for general matrices (DGETRF, ZGETRF,
    DGETRS & DGESV)
  - Matrix inverse routine DGETRI for small sizes
  - Least Square solver DGELS for small sizes
  - Double Precision Auxiliary routine, DLARFG
• Improved performance of following APIs using local AOCL-BLAS optimized kernels
  - LU Factorization / Solver routines for band storage matrices (DGBTRF, DGBTRS)
• Option to set specific ISA code path through AOCL_ENABLE_INSTRUCTIONS
  environment variable
• Sphinx-based AOCL-LAPACK API documentation
• LAPACK API modifications
  - Updated AOCL-LAPACK APIs return type to match with corresponding netlib
    subroutine prototypes
  - Removed xerbla and lsame definition from AOCL-LAPACK. Applications have to
    invoke lsame from BLAS library
• Test suite framework enhancements
  - Improvements to accuracy tests using better input generation mechanisms
  - Addition of extreme values, negative and corner test cases
  - Addition of cases to test numerical stability
  - Support for LAPACKE interface test
• Minor Bug fixes and code quality improvement changes

Please refer AOCL User Guide for supported Operating Systems and Compilers.

The package contains AOCL-LAPACK Library binaries which includes optimizations
for the AMD EPYC and AMD Ryzen processor families, header files and examples.

Note: 
1. AOCL-LAPACK 4.1.0 has dependency on libstdc++ library. On Linux, user must
   link libstdc++(-lstdc++) when AOCL-LAPACK library is used.
2. From 4.1.0 release onwards, AOCL-LAPACK depends on Python 3.x as a
   prerequisite. Python 2.x is no longer supported.
3. The pre-built AOCL-LAPACK binaries are compiled with ENABLE_AOCL_BLAS
   option. Hence applications must link with AOCL-BLAS when using prebuilt
   AOCL-LAPACK library.

Known Issues
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1. Numerical failures in few Netlib LAPACK tests for complex datatype routines.
