commit:     26026cc4488be016748d6fead1ffaa47204f0984
Author:     David Seifert <soap <AT> gentoo <DOT> org>
AuthorDate: Sat Sep  2 11:38:48 2017 +0000
Commit:     David Seifert <soap <AT> gentoo <DOT> org>
CommitDate: Sat Sep  2 11:38:48 2017 +0000
URL:        https://gitweb.gentoo.org/proj/sci.git/commit/?id=26026cc4

profiles: Remove last mentions of sci-libs/acml

 docs/proj/blas-lapack.xml |  16 --
 docs/proj/linalg.xml      |  19 --
 licenses/ACML-EULA        | 428 ----------------------------------------------
 profiles/license_groups   |   2 +-
 profiles/use.local.desc   |   6 -
 5 files changed, 1 insertion(+), 470 deletions(-)

diff --git a/docs/proj/blas-lapack.xml b/docs/proj/blas-lapack.xml
index 8c94990ab..f4ef31cee 100644
--- a/docs/proj/blas-lapack.xml
+++ b/docs/proj/blas-lapack.xml
@@ -138,12 +138,6 @@ tree:
    routines. Claims to be the fastest BLAS.
   </li>
   <li>
-    <uri link="http://developer.amd.com/acml.jsp";>ACML</uri>: AMD Core Math
-    Library is a closed-source but free package containing BLAS (FORTRAN 77
-    only) and LAPACK for x86 and amd64 architectures, but also other math tools
-    such as statistical libraries and FFTs.
-  </li>
-  <li>
     <uri link="http://developer.intel.com/software/products/mkl/";>MKL</uri>:
     Intel® Math Kernel Library is a closed-source but free package for
     non-commercial use containing BLAS (FORTRAN 77 and C), LAPACK optimized for
@@ -238,8 +232,6 @@ profile combinations that have been used successfully in 
the past:
   </li>
   <li> AMD based CPUs:
     <ul>
-      <li>blas,lapack: acml-gfortran (or acml-gfortran-openmp with
-       multi-processors) </li>
       <li>cblas: reference</li>
     </ul>
   </li>
@@ -292,8 +284,6 @@ compatible. For example:
 </p>
 
 <pre caption="Incompatible combinations">
-# <i>F77=ifort FFLAGS="-O2 -mp" USE="openmp" emerge =acml-3.6.0-r1</i>
-# <i>eselect blas set acml-ifort-openmp</i>
 # <i>F77=gfortran FFLAGS="-O2" emerge lapack-reference</i>
 </pre>
 
@@ -410,12 +400,6 @@ virtuals:
   <th>virtual/lapack</th>
 </tr>
 <tr>
-  <ti><c>sci-libs/acml</c></ti>
-  <ti>*</ti>
-  <ti></ti>
-  <ti>*</ti>
-</tr>
-<tr>
   <ti><c>sci-libs/blas-atlas</c></ti>
   <ti>*</ti>
   <ti>*</ti>

diff --git a/docs/proj/linalg.xml b/docs/proj/linalg.xml
index 0da83057b..02ce98bf4 100644
--- a/docs/proj/linalg.xml
+++ b/docs/proj/linalg.xml
@@ -151,12 +151,6 @@ However, if:
    and C BLAS routines. Still claims to be the fastest BLAS.
   </li>
   <li>
-    <uri 
link="http://developer.amd.com/cpu/libraries/acml/Pages/default.aspx";>ACML</uri>:
-    AMD Core Math Library is a closed-source but free package containing BLAS 
(FORTRAN 77
-    only) and LAPACK for x86 and x86_64 architectures, but also other math 
tools
-    such as statistical libraries and FFTs.
-  </li>
-  <li>
     <uri link="http://software.intel.com/en-us/articles/intel-mkl/";>MKL</uri>:
     Intel® Math Kernel Library is a closed-source but free package for
     non-commercial use on Linux systems containing implementations of all the 
linear
@@ -256,8 +250,6 @@ Installed CBLAS for library directory lib64
   </li>
   <li> performant on AMD based CPUs:
     <ul>
-      <li>blas, lapack: acml-gfortran (or acml-gfortran-openmp with
-       multi-processors) </li>
       <li>cblas: reference</li>
     </ul>
   </li>
@@ -310,8 +302,6 @@ Installed CBLAS for library directory lib64
 </p>
 
 <pre caption="Looking for trouble combinations">
-# <i>USE=ifort emerge acml</i>
-# <i>eselect blas set acml-ifort-openmp</i>
 # <i>FC=gfortran FFLAGS="-O2" emerge lapack-reference</i>
 </pre>
 
@@ -453,15 +443,6 @@ Installed CBLAS for library directory lib64
   <th>virtual/scalapack</th>
 </tr>
 <tr>
-  <ti><c>sci-libs/acml</c></ti>
-  <ti>*</ti>
-  <ti></ti>
-  <ti>*</ti>
-  <ti></ti>
-  <ti></ti>
-  <ti></ti>
-</tr>
-<tr>
   <ti><c>sci-libs/atlas</c></ti>
   <ti>*</ti>
   <ti>*</ti>

diff --git a/licenses/ACML-EULA b/licenses/ACML-EULA
deleted file mode 100644
index 870f574b6..000000000
--- a/licenses/ACML-EULA
+++ /dev/null
@@ -1,428 +0,0 @@
-LICENSE AGREEMENT
-(AMD CORE MATH LIBRARY)
-
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(“Licensee”) and 
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LIBRARY, (“ACML”) 
-including (a) Documentation; (b) Sample Code; (c) header files, tools and 
utilities; (d) Libraries; and (e) 
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“Licensed Materials”), are subject to the 
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as Licensee, have carefully read 
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AMD Confidential Information and 
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diff --git a/profiles/license_groups b/profiles/license_groups
index d41f4584e..c23a2a105 100644
--- a/profiles/license_groups
+++ b/profiles/license_groups
@@ -1,2 +1,2 @@
-EULA ACML-EULA AMD-APPSDK NVIDIA-gdk NVIDIA-CUDA OpenSIFT
+EULA AMD-APPSDK NVIDIA-gdk NVIDIA-CUDA OpenSIFT
 MISC-FREE CeCILL-B

diff --git a/profiles/use.local.desc b/profiles/use.local.desc
index 6d7dd0143..565f542eb 100644
--- a/profiles/use.local.desc
+++ b/profiles/use.local.desc
@@ -29,7 +29,6 @@ dev-lang/path64:assembler - Build PathAS assembler
 dev-lang/path64:debugger - Build PathDB debugger
 dev-lang/path64:native - Use EKOPath/Path64 for bootstraping
 dev-lang/path64:valgrind - Support compiler debugging with dev-util/valgrind
-dev-lang/pgi:acml - Install AMD's core math library.
 dev-lang/pgi:cuda - Install PGI's CUDA components (e.g. for OpenACC)
 dev-lang/pgi:java - Install a PGI-tuned JRE.
 dev-libs/intel-common:compiler - Install the libraries needed for the icc and 
ifort compilers
@@ -121,11 +120,6 @@ sci-electronics/player:festival - Automatically generated 
description for festiv
 sci-electronics/player:openssl - Automatically generated description for 
openssl
 sci-electronics/player:sphinx2 - Automatically generated description for 
sphinx2
 sci-geosciences/qgis:grass - Add support for sci-geosciences/grass
-sci-libs/acml:gfortran - Fetch and install acml compiled with GNU FORTRAN 
compiler
-sci-libs/acml:ifort - Fetch and install acml compiled with the Intel FORTRAN 
compiler
-sci-libs/acml:int64 - Install the 64 bits integer library
-sci-libs/acml:open64 - Fetch and install acml compiled with the Open64 FORTRAN 
Compiler
-sci-libs/acml:pgi - Fetch and install acml compiled with the Portland Group 
FORTRAN compiler
 sci-libs/armadillo:arpack - Link with sci-libs/arpack libraries for eigen 
decomposition
 sci-libs/armadillo:atlas - Link with sci-libs/atlas libraries for cblas and 
clapack
 sci-libs/armadillo:mkl - Use matrix allocation from the Intel MKL sci-libs/mkl

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