contents: clean up news, and remove references to gcc-plugin and cell architecture

contents/index.html

@@ -43,7 +43,7 @@
 <li><b>The application provides algorithms and constraints</b>
     <ul>
     <li>CPU/GPU implementations of tasks</li>
-    <li>A graph of tasks, using either the StarPU's high level <b>GCC plugin</b> pragmas, StarPU's rich <b>C/C++ API</b>, or <b>OpenMP pragmas</b>.</li>
+    <li>A graph of tasks, using either StarPU's rich <b>C/C++ API</b>, or <b>OpenMP pragmas</b>.</li>
     </ul>
 <br>
 </li>
@@ -103,56 +103,12 @@ October
       and accelerator devices with other parallel runtime systems, ...
 </p>
 <p>
-June
-2019 <b>&raquo;&nbsp;</b><a href="http://gforge.inria.fr/frs/?group_id=1570"><b>The
-      release 1.3.2 of StarPU is now
-      available!</b></a> The 1.3 release brings among other
-      functionalities a MPI master-slave support, a tool to replay
-      execution through SimGrid, a HDF5 implementation of the
-      Out-of-core, a new implementation of StarPU-MPI on top of
-      NewMadeleine, implicit support for asynchronous partition
-      planning, a resource management module to share processor cores
-      and accelerator devices with other parallel runtime systems, ...
-</p>
-<p>
 May 2019 <b>&raquo;&nbsp;</b><a href="http://gforge.inria.fr/frs/?group_id=1570"><b>The
       v1.1.8 release of StarPU is now available!</b></a>. This release notably brings the concept of
       scheduling contexts which allows to separate computation
       resources. This is really intented to be the last release for the
       branch 1.1.
 </p>
-<p>
-April
-2019 <b>&raquo;&nbsp;</b><a href="http://gforge.inria.fr/frs/?group_id=1570"><b>The
-      release 1.3.1 of StarPU is now
-      available!</b></a> The 1.3 release brings among other
-      functionalities a MPI master-slave support, a tool to replay
-      execution through SimGrid, a HDF5 implementation of the
-      Out-of-core, a new implementation of StarPU-MPI on top of
-      NewMadeleine, implicit support for asynchronous partition
-      planning, a resource management module to share processor cores
-      and accelerator devices with other parallel runtime systems, ...
-</p>
-<p>
-March
-2019 <b>&raquo;&nbsp;</b><a href="http://gforge.inria.fr/frs/?group_id=1570"><b>The
-      release 1.3.0 of StarPU is now
-      available!</b></a> The 1.3 release brings among other
-      functionalities a MPI master-slave support, a tool to replay
-      execution through SimGrid, a HDF5 implementation of the
-      Out-of-core, a new implementation of StarPU-MPI on top of
-      NewMadeleine, implicit support for asynchronous partition
-      planning, a resource management module to share processor cores
-      and accelerator devices with other parallel runtime systems, ...
-</p>
-<p>
-February 2019 <b>&raquo;&nbsp;</b><a href="http://gforge.inria.fr/frs/?group_id=1570"><b>The
-      1.2.8 release of StarPU is now available!</b></a>.
-	The 1.2 release serie notably brings an out-of-core support, a MIC Xeon
-	Phi support, an OpenMP runtime support, and a new internal
-	communication system for MPI.
-	(The release 1.2.7 is broken and should not be used)
-</p>
 </div>
 
 <div class="section emphasizebot" style="text-align: right; font-style: italic;">
@@ -372,11 +328,9 @@ StarPU will <b>automatically evict</b> data from the main memory in advance, and
 
 <h4>All in all</h4>
   <p>
-All that means that, with the help
-of <a href="doc/html/cExtensions.html">StarPU's extensions to the C
-language</a>, the following sequential source code of a tiled version of
-the classical Cholesky factorization algorithm using BLAS is also valid
-StarPU code, possibly running on all the CPUs and GPUs, and given a data
+All that means that the following sequential source code of a tiled version of
+the classical Cholesky factorization algorithm using BLAS is also (a
+almost) valid StarPU code, possibly running on all the CPUs and GPUs, and given a data
 distribution over MPI nodes, it is even a distributed version!
   </p>
 
@@ -397,7 +351,6 @@ for (k = 0; k < tiles; k++) {
 <li>SMP/Multicore Processors (x86, PPC, ARM, ... all Debian architecture have been tested) </li>
 <li>NVIDIA GPUs (e.g. heterogeneous multi-GPU), with pipelined and concurrent kernel execution support (new in v1.2) and GPU-GPU direct transfers (new in v1.1)</li>
 <li>OpenCL devices</li>
-<li>Cell Processors (experimental)</li>
 <li>Intel SCC (experimental, new in v1.2)</li>
 <li>Intel MIC / Xeon Phi (new in v1.2)</li>
 </ul>