Add a few bullets, specify which version supports what

git-svn-id: svn+ssh://scm.gforge.inria.fr/svn/starpu/website@15646 176f6dd6-97d6-42f4-bd05-d3db9ad07c7a

index.html

@@ -133,9 +133,10 @@ is possible to specify one function for each architectures</b> (e.g. one functio
 for CUDA and one function for CPUs). StarPU takes care of scheduling and
 executing those codelets as efficiently as possible over the entire machine, include
 multiple GPUs.
-One can even specify <b>several functions for each architecture</b> as well as
-<b>parallel imeplementations</b> (e.g. in OpenMP), and StarPU will
-automatically determine which version is best for each input size.
+One can even specify <b>several functions for each architecture</b> (new in
+v1.0) as well as
+<b>parallel implementations</b> (e.g. in OpenMP), and StarPU will
+automatically determine which version is best for each input size (new in v0.9).
   </p>
 
 <h4>Data transfers</h4>
@@ -162,7 +163,10 @@ programmer with best flexibility:
   </ul>
   </p>
   <p>
-StarPU also supports an OpenMP-like <a href="doc/html/AdvancedExamples.html#DataReduction">reduction</a> access mode.
+StarPU also supports an OpenMP-like <a href="doc/html/DataManagement.html#DataReduction">reduction</a> access mode (new in v0.9).
+  </p>
+  <p>
+It also supports a <a href="doc/html/DataManagement.html#DataCommute">commute</a> access mode to allow data access commutativity (new in v1.2).
   </p>
 
 <h4>Heterogeneous Scheduling</h4>
@@ -183,7 +187,23 @@ explicit network communications, which will then be <b>automatically combined an
 overlapped</b> with the intra-node data transfers and computation. The application
 can also just provide the whole task graph, a data distribution over MPI nodes, and StarPU
 will automatically determine which MPI node should execute which task, and
-<b>generate all required MPI communications</b> accordingly.
+<b>generate all required MPI communications</b> accordingly (new in v0.9).
+  </p>
+
+<h4>Out of core</h4>
+  <p>
+When memory is not big enough for the working set, one may have to resort to
+using disks. StarPU makes this seamless thanks to its <a href="doc/html/OutOfCore.html">out of core support</a> (new in 1.2).
+StarPU will automatically evict data from the main memory in advance, and
+prefetch back required data before it is needed for tasks.
+  <p>
+
+To deal with clusters, StarPU can nicely integrate with <a href="doc/html/MPISupport.html">MPI</a> through
+explicit network communications, which will then be <b>automatically combined and
+overlapped</b> with the intra-node data transfers and computation. The application
+can also just provide the whole task graph, a data distribution over MPI nodes, and StarPU
+will automatically determine which MPI node should execute which task, and
+<b>generate all required MPI communications</b> accordingly (new in v0.9).
   </p>
 
 <h4>Extensions to the C Language</h4>
@@ -192,14 +212,20 @@ will automatically determine which MPI node should execute which task, and
   that <a href="doc/html/cExtensions.html">extends the C programming
   language</a> with pragmas and attributes that make it easy
   to <b>annotate a sequential C program to turn it into a parallel
-  StarPU program</b>.
+  StarPU program</b> (new in v1.0).
+</p>
+
+<h4>OpenCL-compatible interface</h4>
+<p>
+  StarPU provides an <a href="doc/html/SOCLOpenclExtensions.html">OpenCL-compatible interface, SOCL</a>
+  which allows to simply run OpenCL applications on top of StarPU (new in v1.0).
 </p>
 
 <h4>Simulation support</h4>
 <p>
   StarPU can very accurately simulate an application execution
   and measure the resulting performance thanks to using the
-  <a href="http://simgrid.gforge.inria.fr">SimGrid simulator</a>.  This allows
+  <a href="http://simgrid.gforge.inria.fr">SimGrid simulator</a> (new in v1.1).  This allows
   to quickly experiment with various scheduling heuristics, various application
   algorithms, and even various platforms (available GPUs and CPUs, available
   bandwidth)!
@@ -230,11 +256,11 @@ for (k = 0; k < tiles; k++) {
 <h4>Supported Architectures</h4>
 <ul>
 <li>SMP/Multicore Processors (x86, PPC, ...) </li>
-<li>NVIDIA GPUs (e.g. heterogeneous multi-GPU)</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 1.1)</li>
 <li>OpenCL devices</li>
 <li>Cell Processors (experimental)</li>
 </ul>
-and soon
+and soon (in v1.2)
 <ul>
 <li>Intel SCC</li>
 <li>Intel MIC / Xeon Phi</li>
@@ -279,7 +305,7 @@ GFlop/s</b>
 
 <p>
 <a href="http://www.hlrs.de/temanejo">Temanejo</a> can be used to debug the task
-graph, as shown below.
+graph, as shown below (new in v1.1).
 </p>
 
 <center>