[Swift-commit] r3891 - text/parco10submission

[noreply at svn.ci.uchicago.edu]

Author: dsk
Date: 2011-01-07 10:48:49 -0600 (Fri, 07 Jan 2011)
New Revision: 3891

Modified:
   text/parco10submission/paper.tex
Log:
merging in Ian's changes


Modified: text/parco10submission/paper.tex
===================================================================
--- text/parco10submission/paper.tex	2011-01-07 16:41:11 UTC (rev 3890)
+++ text/parco10submission/paper.tex	2011-01-07 16:48:49 UTC (rev 3891)
@@ -80,13 +80,20 @@
 
 \begin{abstract}
 
-The work of scientists, engineers and statisticians often requires executing domain-specific application programs a
-massive number of times on large collections of file-based data.  This  process requires complex data management to pass data to, from, and between application invocations. Distributed and
-parallel computing resources can greatly speed up
-such processing, but their use increases the complexity of the programming effort and presents new barriers. The Swift parallel scripting language reduces these complexities with a
-scripting language for composing ordinary application programs into powerful parallel scripts that can efficiently utilize parallel and distributed resources.
-In this paper we present Swift's implicitly parallel and deterministic programming model, which applies external applications to file collections using a functional, ``in-memory'' style of scripting that abstracts and simplifies distributed parallel execution.
+Scientists, engineers and statisticians must often execute domain-specific application programs 
+many times on large collections of file-based data.  This  activity requires complex orchestration and data management 
+as data is passed to, from, and among application invocations. Distributed and
+parallel computing resources can accelerate
+such processing, but their use increases programming complexity yet further. 
+The Swift parallel scripting language reduces these complexities by (a) making file system structures accessible via language constructs,
+and (b)
+allowing
+ordinary application programs to be composed into powerful parallel scripts that can efficiently utilize parallel and distributed resources.
+We present Swift's implicitly parallel and deterministic programming model, 
+which applies external applications to file collections using a functional style of scripting that abstracts and simplifies distributed parallel execution.
 
+%IAN: Re above--it seems important to me to make point (a).
+
 \end{abstract}
 
 \begin{keyword}
@@ -107,8 +114,8 @@
 % mw: not sure why idempotency matters.  This gets into issues of single-assignment; restartability; and whether or not we treat application invocations as both idempotent and/or referentially transparent.  Since we treat execution of apps as "isolated", and "side-effect-free", neither parallel interleavings nor re-runs should have much effect on them.
 
 Swift is a scripting language designed for composing
-application programs into distributed,
-parallelized applications for execution on clusters, grids, clouds, and supercomputers
+application programs into parallel
+applications that can be executed on multicore processors, clusters, grids, clouds, and supercomputers
 with tens to hundreds of thousands of processors.
 %It is intended to serve as a higher level framework for composing the interaction of
 %concurrently executing programs (even parallel ones) and scripts
@@ -128,14 +135,19 @@
 %inherent complexity of programming on these systems, necessitates a
 %new approach.
 
-While many application needs involve the execution of a single large
-message-passing parallel program, many others require the coupling or
+Many parallel applications involve a single
+message-passing parallel program: a model supported well by the Message Passing Interface (MPI). 
+However, many others require the coupling or
 orchestration of large numbers of application invocations: either many
 invocations of the same program, or many invocations of sequences and
-patterns of several programs. In this model, existing applications are similar to
-functions in programming, and users typically need to execute many of
-them. Scaling up requires the distribution of such workloads among
-many computers or clusters and hence a ``grid'' approach. Even if
+patterns of several programs. The execution of these 
+%In this model, existing applications are similar to
+%functions in programming, and users typically need to execute many of
+%them. 
+Scaling up requires the distribution of such workloads among
+many computers or clusters.
+%and hence a ``grid'' approach.
+Even if
 a single large parallel cluster suffices, users will not always have
 access to the same system (i.e., big machines may be congested, or temporarily unavailable to a user due to maintenance or allocation depletion). This leads to the need to be able to utilize
 whatever resource happens to be available or economical at the moment