Self-review updates on data-ownership chapter

Signed-off-by: Paul E. McKenney <paulmck@linux.vnet.ibm.com>

1 files changed, 6 insertions, 3 deletions

diff --git a/owned/owned.tex b/owned/owned.tex
index c6585da9..d576b639 100644
--- a/owned/owned.tex
+++ b/owned/owned.tex
@@ -289,7 +289,7 @@ a considerable reduction in the spread of certain types of disease.
 In other cases, privatization imposes costs.
 For example, consider the simple limit counter shown in
 Figure~\ref{fig:count:Simple Limit Counter Add, Subtract, and Read} on
-page~\ref{fig:count:Simple Limit Counter Add, Subtract, and Read}.
+page~\pageref{fig:count:Simple Limit Counter Add, Subtract, and Read}.
 This is an example of an algorithm where threads can read each others'
 data, but are only permitted to update their own data.
 A quick review of the algorithm shows that the only cross-thread
@@ -334,7 +334,9 @@ of parallel-programming environments.
 Examples of data ownership include:
 
 \begin{enumerate}
-\item	All message-passing environments, such as MPI, PVM, and BOINC.
+\item	All message-passing environments, such as MPI~\cite{MPIForum2008}
+	and BOINC~\cite{BOINC2008}.
+\item	Map-reduce~\cite{MapReduce2008MIT}.
 \item	Client-server systems, including RPC, web services, and
 	pretty much any system with a back-end database server.
 \item	Shared-nothing database systems.
@@ -348,7 +350,8 @@ When used properly, it delivers unrivaled simplicity, performance,
 and scalability.
 Perhaps its simplicity costs it the respect that it deserves.
 Hopefully a greater appreciation for the subtlety and power of data ownership
-will lead to greater level of respect.
+will lead to greater level of respect, to say nothing of leading to
+greater performance and scalability coupled with reduced complexity.
 
 % populate with problems showing benefits of coupling data ownership with
 % other approaches. For example, work-stealing schedulers. Perhaps also