Bug 1198: abstract

doc/papers/2010/SPM/spm.tex

@@ -65,6 +65,29 @@ Oude Hoogeveensedijk 4, 7991 PD\ \ Dwingeloo, The Netherlands \\
 \maketitle
 
 \begin{abstract}
+A recent development in radio astronomy is to replace traditional dishes
+with many small antennas. The signals are combined to form one large,
+virtual telescope.  The enormous data streams are cross-correlated to
+filter out noise.  A recent trend is to correlate in software instead of dedicated hardware. Examples
+include e-VLBI and LOFAR.
+In this paper, we explain how to implement and optimize a correlator 
+ on multi-core CPUs
+and many-core architectures, such as NVIDIA and ATI GPUs,
+and the \mbox{Cell/B.E.}  The correlator is a streaming, real-time
+application, and is much more I/O intensive than applications that are
+typically implemented on many-core hardware today.  We compare with
+the LOFAR production correlator on an IBM Blue Gene/P supercomputer.
+We identify several important architectural problems which cause
+architectures to perform suboptimally, and also deal with programmability. 
+Our findings are applicable to signal processing applications in general.
+
+The results show that the processing power and memory bandwidth of
+current GPUs are highly imbalanced.  While
+the production correlator on the Blue Gene/P achieves a superb 96\% of the
+theoretical peak performance, this is only 14\% on ATI GPUs, and 26\%
+on NVIDIA GPUs. The \mbox{Cell/B.E.} processor, in contrast, achieves an
+excellent 92\%. The research presented is an
+important pathfinder for next-generation telescopes.
 \end{abstract}
 
 \section{Introduction}
@@ -206,7 +229,7 @@ FPGAs for on-the-field processing and a Blue Gene/P
 supercomputer to perform real-time, central processing.
 We describe LOFAR in more detail below.
 
-% @@@ dit past hier niet
+%  dit past hier niet
 %% Recent many-core architectures seem to be a viable complement to the aforementioned processing platforms.
 %% GPUs provide more processing power and are more power-efficient than CPUs,
 %% while GPUs are more flexible and easier to program than FPGAs.
@@ -214,7 +237,7 @@ We describe LOFAR in more detail below.
 %% extensive performance comparison between the architectures of popular GPUs 
 %% for signal-processing purposes, particularly, for correlation
 %% purposes~\cite{Nieuwpoort:09}.
-%@@@ Cell
+
 
 \subsection{The LOFAR telescope}