Update README, DESCRIPTION, and NEWS

jjallaire · jjallaire · commit 74e6dc56ef4e · 2015-03-04T05:52:42.000-05:00
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,10 +1,19 @@
 Package: RcppParallel
 Type: Package
 Title: Parallel Programming Tools for Rcpp
-Version: 4.3.3
-Date: 2014-10-20
-Author: JJ Allaire; Romain Francois; Intel, Inc.; Marcus Geelnard
-Maintainer: JJ Allaire <jj@rstudio.com>
+Version: 4.3.4
+Date: 2015-04-04
+Authors@R: c(
+    person("JJ", "Allaire", role = c("aut", "cre"), email = "jj@rstudio.com"),
+    person("Romain", "Francios", role = c("aut", "cph")),
+    person("Gregory", "Vandenbrouck", role = "aut"),
+    person("Marcus", "Geelnard", role = c("aut", "cph"),
+       comment = "TinyThread library, http://tinythreadpp.bitsnbites.eu/"),
+    person(family = "RStudio", role = "cph"),
+    person(family = "Intel", role = c("aut", "cph"),
+       comment = "Intel TBB library, https://www.threadingbuildingblocks.org/"),
+    person(family = "Microsoft", role = "cph")
+    )
 Description: High level functions for doing parallel programming with Rcpp.
   For example, the parallelFor function can be used to convert the work of 
   a standard serial "for" loop into a parallel one and the parallelReduce 
diff --git a/NEWS b/NEWS
@@ -1,4 +1,9 @@
-RcppParallel 4.3.1
+RcppParallel 4.3.4
+------------------------------------------------------------------------
+
+* Support for TBB on Windows
+
+RcppParallel 4.3.3
 ------------------------------------------------------------------------
 
 * Update to TBB 4.3 (fixes clang compilation error in platform.h)
diff --git a/README.md b/README.md
@@ -2,7 +2,7 @@
 
 High level functions for doing parallel programming with Rcpp. For example, the `parallelFor` function can be used to convert the work of a standard serial "for" loop into a parallel one and the `parallelReduce` function can be used for accumulating aggregate or other values.
 
-The high level interface enables safe and robust parallel programming without direct manipulation of operating system threads. The underlying implementation differs by platform: on Linux and Mac systems the [Intel TBB](https://www.threadingbuildingblocks.org/) (Threading Building Blocks) are used while on Windows systems the [TinyThread](http://tinythreadpp.bitsnbites.eu/) library is used.
+The high level interface enables safe and robust parallel programming without direct manipulation of operating system threads. On Windows, OS X, and Linux systems the underlying implementation is based on [Intel TBB](https://www.threadingbuildingblocks.org/) (Threading Building Blocks). On other platforms a less-performant fallback implementation based on the [TinyThread](http://tinythreadpp.bitsnbites.eu/) library is used.
 
 ### Examples
 
@@ -16,8 +16,6 @@ Here are links to some examples that illustrate using RcppParallel. Performance
 
 [Parallel Inner Product](http://gallery.rcpp.org/articles/parallel-inner-product/) --- Demonstrates using `parallelReduce` to compute the inner product of two vectors in parallel. In this example the parallel version performs 2.5x faster than the serial version.
 
-Note that the benchmark times above are for the TBB back-end (Posix systems only). Performance on Windows will be about 30-50% slower as a result of less sophisticated thread scheduling.
-
 ### Usage
 
 You can install the RcppParallel package from CRAN as follows:
