\documentstyle[11pt]{article}

\hyphenation{time-stamp time-stamps}

\begin{document}

\title{ParaGraph: A Tool for Visualizing Performance \\
of Parallel Programs
\thanks{
This user guide is adapted from a technical report \protect\cite{hea91a},
which also appears in a modified form in \protect\cite{hea91b}.
The principal modifications to produce this manual were the omission
of illustrations and most bibliographic citations, and the addition of
a considerable amount of detail to aid in using and understanding
ParaGraph.  This edition also reflects many new features recently
added to ParaGraph, and is up to date as of June 8, 1994.}
}

\author{Michael T. Heath, University of Illinois \and
Jennifer Etheridge Finger, Oak Ridge National Laboratory}
\maketitle

{\abstract
ParaGraph is a graphical display system for visualizing the behavior
and performance of parallel programs on message-passing multicomputer
architectures.  The visual animation is based on execution trace
information monitored during an actual run of a parallel program on
a message-passing parallel computer.  The resulting trace data are
replayed pictorially to provide a dynamic depiction of the behavior of
the parallel program, as well as graphical summaries of its overall
performance.  Many different visual perspectives are provided from
which to view the same performance data, in an attempt to gain insights
that might be missed by any single view.  We describe this
visualization tool, outline the motivation and philosophy behind its
design, and provide details on how to use it.
\endabstract
}

\clearpage

\tableofcontents

\clearpage

\section{Motivation and Design Philosophy}

Graphical visualization is a standard technique for facilitating
human comprehension of complex phenomena and large volumes of data.
The behavior of parallel programs on advanced computer architectures
is often extremely complex, and hardware or software performance
monitoring of such programs can generate vast quantities of data.
Thus, it seems natural to use visualization techniques to gain insight
into the behavior of parallel programs so that their performance can
be understood and improved.  We have developed such a software tool,
called ParaGraph, that provides a detailed, dynamic, graphical
animation of the behavior of message-passing parallel programs, as well
as graphical summaries of their performance.  The purpose of this
document is to explain how to use the visualization tool to analyze
parallel programs.

\subsection{Graphical Simulation}

For lack of a better term, we will often use the word ``simulation''
to refer to the graphical animation of a parallel program.  The use
of this term should not be taken to suggest that there is anything
artificial about the programs or their behavior as we portray them.
ParaGraph displays the behavior and performance of real parallel
programs running on real parallel computers to solve real problems.
In effect, ParaGraph simply provides a visual replay of the events
that actually occurred when a parallel program was run on a parallel
machine.

To date, ParaGraph has been used only in such a ``post processing''
manner, using a tracefile created during the execution of the parallel
program and saved for later study.  But the design of the package does
not rule out the possibility that the data for the visualization could
be arriving at the graphical workstation as the parallel program
executes on the parallel machine.  In practice, however, there are
major impediments to such real-time performance visualization.  With
the current generation of distributed-memory parallel architectures, it
is difficult to extract performance data from the processors and send
it to the outside world during execution without significantly
perturbing the application program being monitored.  Moreover, the
network bandwidth between the parallel processor and the graphical
workstation, as well as the drawing speed of the workstation, are
usually inadequate to handle the extremely high data transmission rates
that would be required for real-time display.  Finally, even if these
other limitations were not a factor, human visual perception would be
hard pressed to digest a detailed graphical depiction as it flies by in
real time.  One of the strengths of ParaGraph is the insight that can
be gained from repeated replays of the same execution trace data, much
the way ``instant'' replays are used in televised sports events.

Program visualization can be thought of in either static or dynamic
terms.  After a parallel program has completed execution, the tracefile
of events saved on disk can be considered as a static, immutable object
to be studied by various analytical or statistical means.  Some
performance visualization packages reflect this philosophy in that they
provide graphical tools designed for visual browsing of the performance
data from various perspectives using scrollbars and the like.  In
designing ParaGraph, we have adopted a more dynamic approach whose
conceptual basis is algorithm animation.  We see the tracefile as a
script to be played out, visually re-enacting the original live action
of parallel program execution in order to provide insight into the
program's dynamic behavior.  There are advantages and disadvantages in
both static and dynamic approaches.  Algorithm animation is good at
capturing a sense of motion and change, but it is difficult to control
the apparent speed of the simulation.  The static ``browser with
scrollbars'' approach, on the other hand, gives the user control over
the speed with which the data are viewed (indeed, ``time'' can even
move backward), but does not provide such an intuitive feeling for the
dynamic behavior of parallel programs.  In designing ParaGraph, we have
opted for the dynamic animation approach, sacrificing some control over
simulation speed (as will be discussed in greater detail below).

\subsection{Design Goals}

In designing ParaGraph, our principal goals were:

\begin{itemize}
\item ease of understanding,
\item ease of use, and
\item portability.
\end{itemize}

We now briefly discuss each of these goals in turn.

\subsubsection{Ease of understanding}
Since the whole point of visualization is to facilitate human
understanding, it is imperative that the visual displays provided be as
intuitively meaningful as possible.  The charts and diagrams should be
aesthetically appealing, and the information they convey should be as
self-evident as possible.  A diagram is not likely to be useful if it
requires an extensive explanation.  The type of information conveyed by
a diagram should be immediately obvious, or at least easily remembered
once learned.  The choice of colors used should take advantage of
existing conventions to reinforce the meaning of graphical objects, and
should also be consistent across views.  Above all, it is essential to
provide many different visual perspectives, since no single view is
likely to provide full insight into the complex behavior and large
volume of data associated with the execution of parallel programs.
ParaGraph in fact provides some twenty-five different displays or
views, all based on the same underlying execution trace data.

\subsubsection{Ease of use}
One of the main purposes of software tools is to relieve tedium,
not promote it.  Through the use of color and animation, we have
tried to make ParaGraph painless, perhaps even entertaining, to use.
It certainly seems reasonable that any graphics package should have a
graphical user interface.  ParaGraph has an interactive, mouse- and
menu-oriented user interface so that the various features of the
package are easily invoked and customized.  Another important factor
in ease of use is that the user's parallel program (the object under
study) need not be modified extensively to obtain the data on which the
visualization is based.  ParaGraph currently takes its input data from
execution tracefiles produced by PICL (Portable Instrumented
Communication Library \cite{gei90a,gei90b}), which enables the user to
produce such trace data automatically.  We have also tried to keep the
user's learning curve for ParaGraph very short, even at the expense of
limiting the flexibility of its data processing and graphical display
capabilities.  Our intent is to require minimal data manipulation
and to provide a variety of views that are customized to the task at
hand, rather than providing more general data processing and graphics
capabilities in a toolkit for constructing views of program behavior.

\subsubsection{Portability}
There are two senses in which portability is important in the present
context.  One is that the graphics package itself be portable.
ParaGraph is based on the X Window System, and thus runs on a wide
variety of scientific workstations from many different vendors.
ParaGraph does not require any X toolkit or widget set, as it is based
directly on the standard Xlib library, which is available in any
distribution of the X Window System.  ParaGraph has been tested with
all MIT distributions of X11 through X11R5, as well as several
vendor-supplied versions of X Windows.  Although ParaGraph is most
effective in color, it also works on monochrome and grayscale
monitors.  It automatically detects which type of monitor is in use,
but this automatic choice can be overridden by the user, if desired.
A second sense in which portability is important is that the package
be capable of displaying execution behavior from different parallel
architectures and parallel programming paradigms.  ParaGraph inherits
a high degree of such portability from PICL, which runs on parallel
architectures from a number of different vendors (e.g., Cogent, Intel,
Meiko, Ncube, Symult, Thinking Machines).  On the other hand, many of
the displays in ParaGraph are based on a message-passing paradigm, and
thus the package does not currently offer support for displaying the
behavior of programs based explicitly on shared-memory constructs.
Further comments on the programming model supported by ParaGraph are
given below.

\subsection{Relationship to Previous Work}

ParaGraph is certainly not the first software tool to be developed for
visualizing parallel programs.  Graphical animation techniques for
visualizing serial algorithms have received considerable study.
Visualization of parallel computations has been the subject of a number
of Ph.D. theses, technical articles, and books.  Graphical
visualization has also been an important component of several
environments that have been developed for parallel programming,
debugging, and monitoring, as well as integrated environments that
combine several of these components.  Algorithm visualization tools
have also been developed for specific applications, such as matrix
computations.  See \cite{hea91a} for an extensive list of references on
much of this prior work.  ParaGraph is a general-purpose performance
visualization tool that is distinguished from most previous efforts in
the following ways:

\begin{itemize}

\item The multiplicity of displays provided by ParaGraph is
unique.  Other packages have emphasized the importance of multiple
views, but ParaGraph provides a substantially greater variety of
perspectives than any other package of which we are aware.  Some of the
displays we have incorporated into ParaGraph appear to be original,
while others have been motivated by similar displays found in previous
packages.

\item Many previous packages for visualizing parallel programs have
targeted a particular parallel architecture and/or been based on a
proprietary graphical display system.  ParaGraph is applicable to any
parallel architecture having message passing as its programming
paradigm, and ParaGraph itself is based on the X Window System, which
is widely available on workstations from many vendors.

\item We have tried to attain high standards in the intuitive appeal
and aesthetic quality of the displays provided by ParaGraph, including
both the new displays we have devised and the display concepts that we
have borrowed from previous packages.  Of course, the perceived success
of this attempt is in the eye of the beholder and can be judged only by
users.

\item We have also tried to make ParaGraph exceptionally easy to use,
both through its interactive, graphical user interface and by relying
on an instrumented communication library (PICL) to provide the
requisite trace data without requiring the user to instrument
explicitly the parallel program under study.  We have also emphasized
a short learning curve, minimal data manipulation, and views that are
already tuned to the specific task at hand.

\item Another unusual feature of ParaGraph is its extensibility.
ParaGraph provides a mechanism for users to add new displays of their
own design that can be viewed along with the other displays already
provided.  This capability is intended primarily to support
special-purpose displays for particular applications, and is described
in more detail below.

\end{itemize}

An indication of our degree of success in making ParaGraph easy to use
and easy to understand is the fact that many users obtained an early
version from {\tt netlib@ornl.gov} \cite{don87} over the Internet and
were able to build the program at their locations and use it
effectively without the benefit of any documentation beyond a one-page
README file.  For some case studies of performance tuning with
ParaGraph, see \cite{hea90,hea93,tom93}.

\subsection{Relationship to PICL}

PICL is a Portable Instrumented Communication Library
\cite{gei90a,gei90b} that is available from {\tt netlib@ornl.gov} and
runs on a variety of message-passing parallel architectures.  As its
name implies, PICL provides both portability and instrumentation for
programs that use its communication facilities for passing messages
between processors.  On request, PICL provides a tracefile that records
important events in the execution of the user's parallel program (e.g.,
sending and receiving messages).  The tracefile contains one event
record per line, and each event record consists of a set of integers
that specify the event type, timestamp, processor number, message
length, and other similar information.  The current format of the
tracefile is documented in \cite{wor92}.  (Tracefiles in the original
PICL format documented in {\cite{gei90a} can be converted to the newer
format by a conversion utility provided with the ParaGraph
distribution.)  To obtain further information about PICL, including
documentation and source code, send email to {\tt netlib@ornl.gov}
containing the message {\tt send index from picl}.

ParaGraph has a producer-consumer relationship with PICL: ParaGraph
consumes trace data produced by PICL.  By using PICL rather than the
``native'' parallel programming interface for a particular machine,
the user gains portability, instrumentation, and the ability to use
ParaGraph in analyzing the behavior and performance of the parallel
program.  These benefits are essentially ``free'' in that once the
parallel program is implemented using PICL, no further changes are
required to the source code to move it to a new machine (provided PICL
is available on the target machine), and little or no effort is
required to instrument the program for performance analysis.  On the
other hand, since ParaGraph's dependence on PICL is solely for its
input data, ParaGraph could in fact work equally well with any other
source of data having the same format and semantics.  Thus, other
message-passing systems could be instrumented to produce trace data in
the format expected by ParaGraph, or else ParaGraph's input routine
could be adapted to a different input format.  In this manner,
ParaGraph can be, and indeed has been, used in conjunction with
communication systems other than PICL.  Several vendors of parallel
computers have instrumented their native messaging systems to produce
PICL-compatible tracefiles, which can then be viewed with ParaGraph.

For a meaningful simulation, the timestamps of the events should be as
accurate and consistent across processors as possible.  This is not
necessarily easy to accomplish on a machine in which each processor may
have its own clock with its own starting time, running at its own
rate.  Moreover, the resolution of the clock may be inadequate to
resolve events precisely.  Poor resolution and/or poor synchronization
of the processor clocks can lead to ``tachyons'' in the tracefile, that
is, messages that appear to be received before they are sent.  Such an
occurrence will confuse ParaGraph, since much of its logic depends on
correctly pairing sends and receives, and will invalidate the
information in some of the displays.  For this reason, PICL goes to
considerable lengths to synchronize the processor clocks, and also to
adjust for potential clock drift, so that the timestamps will be as
consistent and meaningful as possible \cite{dun91}.  On some machines,
PICL actually provides a higher resolution clock than the one supplied
by the system vendor.  Fortunately, the trend is towards more accurate
clocks and centralized clock pulses in distributed parallel machines,
so clock consistency should be less of a problem in the future.

Another important issue is the amount of additional overhead introduced
by the collection of trace information compared to the execution time
of an equivalent uninstrumented program.  PICL tries to minimize the
perturbation due to tracing by saving the trace data locally in each
processor's memory, then downloading it to disk only after the program
has finished execution.  Nevertheless, such monitoring inevitably
introduces some extra overhead; in PICL the clock calls necessary to
determine the timestamps for the event records, plus other minor
overhead, add a fixed amount (independent of message size) to the cost
of sending each message.  The overall perturbation is thus a function
of the frequency and volume of communication traffic, and it also
varies from machine to machine.  In general, we believe that this
perturbation is small enough that the behavior of parallel programs is
not fundamentally altered.  It is certainly true that in our experience
the lessons we learn from visual study of instrumented runs invariably
lead to improved performance of uninstrumented runs.

\section{Programming Model}

The most fundamental restriction in the parallel programming model
currently supported by ParaGraph (and PICL) is the assumption that
there is only one user process per processor.  Such a programming style
is typical of SPMD (single program multiple data) programs for
multicomputers and is adequate for the vast majority of applications on
these machines.  Nevertheless, this restriction is occasionally limiting,
and it will probably be relaxed in a future release of ParaGraph.

The interprocessor communication model supported by ParaGraph is
typical of interrupt-driven, loosely synchronous message passing
systems from a variety of vendors.  If a message is sent before it has
been requested by the receiving user process, then the message is
buffered and queued by the communication system.  When the receiving
user process subsequently requests the message, its contents are then
transferred from a system buffer into an array provided by the user
process.  If a message is requested before it has arrived, then the
receiving user process blocks further execution until the requested
message arrives, at which point the message is transferred into the
receiving array in the user process and execution resumes.  In any
case, the sending user process resumes execution immediately after the
send and does not block.  Currently, ParaGraph does not explicitly
support fully synchronous communication (in which the sender blocks
until the receive is executed) or fully asynchronous communication (in
which neither sender nor receiver blocks, and probes must be done to
detect whether messages have arrived).  It may still be possible for
ParaGraph to visualize programs that use such communication, but the
visual simulation and the figures of merit produced may not be very
accurate.  Explicit support for these and other communication protocols
may be added to ParaGraph in the future.

It is assumed that each message has an integer type or tag.  The value
for the type is assigned by the sending user process and can be used by
the receiving user process to search the queue of incoming messages
selectively for a particular kind of message.  Such tags can play an
important role in synchronization and control of the parallel program.

Some message passing systems support ``global sends,'' that is,
messages that go from one processor to all other processors as a result
of a single send command.  Such a global send is usually indicated by a
special value, such as -1, for the destination in the usual send
function.  The actual implementation of such global sends varies from
one machine to another, depending on the most efficient way of using a
given interconnection network topology (e.g., a spanning tree in a
hypercube).  ParaGraph handles global sends (i.e., send event records
with destination -1) as if there were a whole set of separate messages,
one for each possible destination processor, with each message having
the same source and contents.  This may or may not accurately reflect
how the given communication system actually implements global sends,
but is about all that ParaGraph can do in representing global sends
pictorially, given its lack of knowledge of the underlying
interconnection network topology.  Note that PICL includes a special
routine, {\tt bcast0}, for global broadcasting that is optimized for
various particular topologies, and this routine in turn generates
individual send and receive event records, which are therefore
accurately depicted by ParaGraph.  For this reason, as well as for
greater portability, the user may prefer to use the explicit
broadcasting facility of PICL rather than a simple send with a special
destination value.

\section{Software Design}

ParaGraph is an interactive, event-driven program.  Its basic structure
is that of an event loop and a large switch that selects actions based
on the nature of each event.  There are in fact two separate event
queues: a queue of X events produced by the user (mouse clicks,
keypresses, window exposures, etc.) and a queue of trace events
produced by the parallel program under study.  Thus, ParaGraph must
alternate between these two queues to provide both a dynamic depiction
of the parallel program and responsive interaction with the user.
Menu selections determine the execution behavior of ParaGraph, both
statically (initial selection of displays, options, parameter
values) and dynamically (pause/resume, single-step mode, etc.).

ParaGraph is written in C, and the source code contains about 18,000
lines.  The {\tt main} program of ParaGraph calls the {\tt preprocess}
function to determine necessary parameters, initializes many variables,
allocates graphical resources such as windows and fonts, and then goes
into a {\tt while} loop that repeatedly calls the functions
{\tt get\_event} and {\tt get\_trace}, which check the X event queue
and the trace event queue, respectively, for the next event upon which
to act.  The {\tt get\_event} routine is simply a switch containing a
series of calls to appropriate routines to handle the various X events.
The {\tt get\_trace} routine calls {\tt scan} to read a trace event
record, and then calls {\tt draw} to update the drawing of the displays
that have been selected.

The X event queue must be checked frequently enough to provide good
interactive responsiveness, but not so frequently as to degrade the
drawing speed during the simulation.  On the other hand, the trace
event queue should be processed as rapidly as possible while the
simulation is active, but need not be checked at all if the next
possible event must be an X event (e.g., before the simulation starts,
after the simulation finishes, when in single-step mode, or when the
simulation has been paused and can be resumed only by user input).
To address these issues, the alternation between the two queues is not
strict.  Since not all trace event records produced by PICL are of
interest to ParaGraph, it ``fast forwards'' through any series of such
``uninteresting'' records before rechecking the X event queue.
Moreover, both blocking and nonblocking calls are used to check the
X event queue, depending on the circumstances, so that workstation
resources are not consumed unnecessarily when the simulation is
inactive.

The relationship between the apparent simulation speed and the original
execution speed of the parallel program is necessarily somewhat
imprecise.  The speed of the graphical simulation is determined
primarily by the drawing speed of the workstation, which in turn is
a function of the number and complexity of displays that have been
selected.  There is no way, in general, to make the apparent simulation
speed uniformly proportional to the original execution speed of the
parallel program.  The reason is that the time required to compute some
event on the parallel machine and the time required to draw some
graphical depiction of that event on the workstation screen have no
particular correlation with each other.  For the most part, ParaGraph
simply processes the event records and draws the resulting displays as
rapidly as it can.  If there are gaps between consecutive timestamps,
however, the intervening time is ``filled in'' by a spin loop so that
there is at least a rough (but not uniform) correspondence between
simulation time and original execution time.  Fortunately, this issue
does not seem to be of critical importance in visual performance
analysis.  The most important consideration in understanding parallel
program behavior is simply that the correct relative order of events
be preserved in the graphical replay.  Moreover, the figures of merit
produced by ParaGraph are based on the actual timestamps, not the
apparent speed with which the simulation unfolds.

Since ParaGraph's speed of execution is determined primarily by the
drawing speed of the workstation, it can be slowed down or speeded up
by selecting more or fewer displays, and by the options used within
those displays (e.g., jump vs. smooth scrolling).  For a given fixed
configuration of displays and options, there is no way to speed up the
simulation, since it is already drawing as fast as it can.  However,
a ``slow-motion'' slider is provided for precise control over the
simulation speed if slower execution is desired without resorting to
opening additional displays.  Further, one can always use single-step
mode if arbitrarily slow drawing speed is desired for very close study
of program behavior.

\section{Using ParaGraph}

ParaGraph supports the following command-line options:

\begin{itemize}

\item[{\tt -c}] to specify color display mode,
\item[{\tt -d}] to specify a hostname and screen (e.g., {\tt hostname:0.0})
for remote display across a network,
\item[{\tt -e}] to specify an environment file (default: {\tt .pgrc}),
\item[{\tt -f}] (or no switch) to specify the path name of a tracefile
directory or of an individual tracefile,
\item[{\tt -g}] to specify grayscale display mode,
\item[{\tt -l}] to specify an animation layout file (default: {\tt .pganim}),
\item[{\tt -m}] to specify monochrome display mode,
\item[{\tt -n}] to specify a name for the base window
(default: {\tt ParaGraph}),
\item[{\tt -o}] to specify a file defining an alternate order and/or optional
names for the processors (default: {\tt .pgorder}),
\item[{\tt -r}] to specify a file of RGB color values for use in color-coding
user-defined tasks (default: {\tt .pgcolors}).

\end{itemize}

It is not normally necessary to specify the display mode (color,
grayscale, or monochrome), as ParaGraph by default will detect the most
appropriate choice for the workstation in use.  Overriding this
automatic choice of display mode can be useful, however, for making
black-and-white hardcopies from a color screen or to accommodate
workstations with multiple screens of different types.  The environment
file, if present, defines the initial selection of displays and options
with which ParaGraph begins execution.  Typically, such an environment
file is created and saved during a previous ParaGraph session.
Specifying a unique name for the base window (i.e., the main menu
window) is useful for distinguishing among multiple instances of
ParaGraph when running them simultaneously.  These and other options
are explained in greater detail below.

The tracefile can be specified on the command line, or it can be
selected using the {\tt tracefile} submenu available from the
main menu.  The tracefile directory can be specified on the
command line, or it can be entered (or changed) during execution by
typing the path name in the subwindow provided in the {\tt tracefile}
menu.  If the path name of a tracefile is specified on the command
line, then the directory portion of that path name is taken as the
tracefile directory.

Once a tracefile has been selected, ParaGraph preprocesses the
tracefile to determine relevant parameters automatically (e.g., time
scale, number of processors) before the graphical simulation begins;
most of these values can be overridden by the user, if desired, by
using the {\tt options} menu.  Faulty tracefiles are usually detected
during the preprocessing stage, in which case ParaGraph will issue an
error message and terminate before going into the graphical simulation.
To produce the necessary trace records for optimal use in ParaGraph,
tracing in PICL should be done with {\tt tracelevel(4,4,0)}.  For
graphical animation with ParaGraph, the tracefile needs to be sorted
into time order.  Since the tracing option of PICL produces a tracefile
with records in node order, the necessary reordering can be
accomplished with the Unix sort command:

\vspace{0.5cm}
{\tt \% sort +2n -3 +0n -1 +1rn -2 tracefile.raw > tracefile.trf}
\vspace{1.0cm}

By default, ParaGraph initially displays only its main menu, which
contains buttons for controlling execution and for selecting various
additional menus.  The submenus available include those for three
types, or families, of displays ({\tt utilization}, {\tt communication},
and {\tt tasks)}, an {\tt other} menu of miscellaneous additional
displays, a {\tt tracefile} menu for selecting a tracefile, an
{\tt options} menu for specifying various options and parameters, and a
{\tt record options} menu for selecting displays that are to produce
numerical output to files, if desired.  As many displays can be
selected as will fit on the screen; the displays can be resized within
reasonable bounds.  Although it is difficult to pay close attention to
many displays at once, it is still useful to have several available
simultaneously for comparison and selective scrutiny with repeated
replays.

Many of the displays have various options that can be selected by
clicking on the appropriate subwindow button.  Pressing the right or
middle mouse button cycles forward through the choices, while pressing
the left mouse button cycles backward.  The selection of displays,
their sizes, their locations on the screen, and the options in effect
can be saved in an environment file for use in subsequent ParaGraph
sessions, as explained below.

The {\tt tracefile} menu provides a graphical means for browsing a
directory from which to select a desired tracefile.  If a directory
path name is supplied on the command line when invoking ParaGraph, then
it will appear in the {\tt path name} subwindow; otherwise, the current
working directory when ParaGraph is invoked is taken as the default
directory.  A new path name can be typed into the {\tt path name}
subwindow of the {\tt tracefile} menu at any time.  The filenames in
the given directory are displayed, and the user selects the desired
tracefile (or another directory) by clicking the mouse pointer on the
corresponding name.  If the name selected is a directory, then it
becomes the new tracefile directory and the files it contains are
displayed.  If the name selected is a tracefile, then the filename is
highlighted in reverse video, and the corresponding tracefile is
processed by ParaGraph.  A new tracefile can be selected at any time
simply by clicking again on a different filename.  Note that the
directory may contain the names of files that are not in fact
legitimate tracefiles.  It is the responsibility of the user to select
only valid tracefiles for processing by ParaGraph.  You may wish to
adopt some standard filename suffix, such as {\tt .trf}, to help
distinguish tracefiles from other files.  To provide greater selectivity
in listing filenames, a {\tt pattern} subwindow is provided that supports
the wildcard characters {\tt *}, which stands for any string, and {\tt ?},
which stands for any single character.  The pattern can be changed by
typing in the {\tt pattern} subwindow.  Only those filenames in the
current tracefile directory that fit the given pattern are displayed
for possible selection.  Typical patterns might be {\tt *.trf} or
{\tt run??}.

After selecting the desired displays, options, and tracefile, the user
presses {\tt start} to begin the graphical simulation of the parallel
program based on the tracefile specified.  The animation proceeds
straight through to the end of the tracefile, but it can be interrupted
for detailed study by use of the {\tt pause/resume} button.  Repeated
use of this button alternates between pausing and resuming the
simulation.  For even more detailed study, the {\tt step} button
provides a single-step mode that processes the tracefile one event (or
a user-specified number of events) at a time.  A particular time
interval can be singled out for study by specifying starting and
stopping times (the defaults are the beginning and ending of the
tracefile), or the simulation can be optionally stopped each time a
user-specified event occurs in the tracefile.  The entire animation can
be restarted at any time (whether in the middle or at the end of the
tracefile) simply by pressing the {\tt start} button again.  Most of
the displays show program behavior dynamically as individual events
occur, but some show only overall summary information at the end of the
run (a few displays serve both purposes, as will be discussed below).

The {\tt slow motion} button opens a window containing a ``slider''
for controlling the simulation speed.  Clicking or dragging the mouse
cursor along the slider slows down execution as much as desired.  The
position of the slider can be altered dynamically during the animation,
and such changes take effect immediately.

The {\tt save env} button causes a record of the current screen
configuration and the various option settings in ParaGraph to be
written in a file, so that, if desired, the same selection of displays
and options can be established immediately upon subsequent invocations
of ParaGraph.  By default, the environment file is called {\tt .pgrc},
but a different name can be specified using the {\tt -e} command-line
option.  The screen locations of all displays are among the information
saved in the environment file, but this placement may or may not be
honored by a given window manager.  Regardless of user requests, some
window managers insist on interactive placement of windows and others
insist on choosing their own locations beyond the user's control.

The {\tt open env/close all} button alternately opens whatever set of
displays are specified in the current environment file, or closes all
currently open displays except the main menu.  The intent is to allow
for quick reconfiguration of displays, including reestablishment of the
initial setup, without having to close or open many windows
individually or restart ParaGraph.

The {\tt screen dump} button enables any window (e.g., a single display
or the entire screen) to be printed on a hardcopy output device,
usually a laser printer.  After pressing the {\tt screen dump} button,
a particular window is selected for printing by clicking the mouse with
the cross-hairs cursor in the desired location.  The appropriate local
command for routing the resulting screen dump to a suitable output
device must appear in the {\tt print command} subwindow of the
{\tt options} menu (see below).

The {\tt reset} button clears all displays and returns to the beginning
of the current tracefile, without restarting the animation.
The {\tt quit} button terminates ParaGraph.

\section{Displays}

In this section we describe the individual displays provided by
ParaGraph.  For color illustrations of many of the displays, see
\cite{hea91a,hea91b}.  Some of the displays change in place
dynamically as events occur, with execution time in the original run
represented by simulation time in the replay.  Others depict time
evolution by representing execution time in the original run by one
space dimension on the screen.  The latter displays scroll as necessary
(by a user-controllable amount) as simulation time progresses, in
effect providing a moving window for viewing what could be considered a
static picture.  No matter which representation of time is used, all
displays of both types are updated simultaneously and synchronized with
each other.

As stated earlier, most of the displays fall into one of three basic
categories -- utilization, communication, and task information --
although some displays contain more than one type of information, and
a few do not fit these categories at all.  Below we provide brief
descriptions of the displays.  Most of the displays scale to reasonably
large numbers of processors, but a few contain too much detail to scale
up well.  The current limit for most of the displays is 512 processors;
the few exceptions are noted specifically below.

\subsection{Utilization Displays}

The displays described in this section are concerned primarily with
processor utilization.  They are helpful in determining the
effectiveness with which the processors are used and how evenly the
computational work is distributed across the processors.

\subsubsection {Utilization Count}
This display shows the total number of processors in each of three
states -- busy, overhead, and idle -- as a function of time.  The
number of processors is on the vertical axis and time is on the
horizontal axis, which scrolls as necessary as the simulation
proceeds.  The color scheme used is borrowed from traffic signals:
green (go) for busy, yellow (caution) for overhead, and red (stop)
for idle.  By convention, we show green at the bottom, yellow in the
middle, and red at the top along the vertical axis.  At any given time,
ParaGraph categorizes each processor as {\em idle} if it has suspended
execution awaiting a message that has not yet arrived (or if it has
ceased execution at the end of the run), {\em overhead} if it is
executing in the communication subsystem (but not awaiting a message),
and {\em busy} if it is executing some portion of the program other
than the communication subsystem.  Since the three categories are
mutually exclusive and exhaustive, the total height of the composite
is always equal to the total number of processors.

Ideally, we would like to interpret {\em busy} as meaning that a
processor is doing useful work, {\em overhead} as meaning that a
processor is doing work that would be unnecessary in a serial program,
and {\em idle} as meaning that a processor is doing nothing.
Unfortunately, the monitoring required to make such a determination
would almost certainly be nonportable and/or excessively intrusive.
Thus, the ``busy'' time we report may well include redundant work or
other work that would not be necessary in a serial program, since our
monitoring detects only overhead associated with communication.
However, we find that the definitions we have adopted based on the data
provided by PICL are quite adequate in practice to convey the
effectiveness of parallel programs pictorially.

\subsubsection{Gantt Chart}
This display, which is patterned after graphical charts used in
industrial management, depicts the activity of individual processors by
a horizontal bar chart in which the color of each bar indicates the
busy/overhead/idle status of the corresponding processor as a function
of time, again using the traffic-signal color scheme.  Processor number
is on the vertical axis and time is on the horizontal axis, which
scrolls as necessary as the simulation proceeds.  The Gantt chart
provides the same basic information as the Utilization Count display,
but on an individual processor, rather than aggregate, basis; in fact,
the Utilization Count display is simply the Gantt chart with the green
sunk to the bottom, the red floated to the top, and the yellow
sandwiched between.

\subsubsection{Kiviat Diagram}
This display, which is adapted from related graphs used in other types
of performance evaluation, gives a geometric depiction of the
utilization of individual processors and the overall load balance
across processors.  Each processor is represented by a spoke of a
wheel.  The recent average fractional utilization of each processor
determines a point on its spoke, with the hub of the wheel representing
zero (completely idle) and the outer rim representing one (completely
busy).

Taken together, the points for all the processors determine the
vertices of a polygon whose size and shape give a pictorial indication
of both processor utilization and load balance across processors.
Low utilization causes the polygon to be concentrated near the center,
while high utilization causes the polygon to lie near the perimeter.
Poor load balance across processors causes the polygon to be strongly
skewed or asymmetric.  Any change in load balance is clearly shown
pictorially; for example, with many ring-oriented algorithms the moving
polygon has the appearance of a rotating camshaft as the heavier
workload moves around the ring.  Other algorithms show a rhythmic
oscillation of the polygon, much like a systolic ``heartbeat.''

The current utilization is shown in dark shading, while the ``high
water mark'' seen thus far is shown in lighter shading.  Since the
Kiviat polygon may not be convex, and the high water mark for different
processors may occur at different times, the outer figure may not have
simple straight sides connecting the spokes.  The ``current''
utilization used in this diagram is in fact a moving average over a
time interval of user-specified width, since instantaneous utilization
would of course always be either zero or one for each processor.  The
width of this smoothing interval can be changed via the {\tt options}
menu.  A button is provided for the user to choose whether the
utilization plotted includes only busy time, or both busy and
overhead (i.e., not idle).

\subsubsection{Streak}
This display is based loosely on newspaper listings of team sports
standings that often include data on winning and losing streaks.
Processor numbers are on the horizontal axis, and the length of the
current streak for each processor is on the vertical axis.  Busy is
always considered winning and idle is always considered losing.
Overhead (perhaps analogous to ties in sports) can be lumped in with
either winning or losing, as selected using the button provided (so
that the streaks might be more accurately termed undefeated or winless,
respectively).  By convention, winning streaks rise from the horizontal
axis and losing streaks fall below the horizontal axis.  This
distinction is further emphasized by color coding (green for winning
and red for losing).  As the current streak for each processor grows,
the corresponding vertical bar rises (or falls) from the horizontal
axis.  When a streak for a processor ends, its bar returns to the
horizontal axis to begin a new streak.  At the end of the run, the
longest streaks (both winning and losing) at any point during the run
are shown for each processor.  This display often provides insight into
rhythmic patterns in parallel programs or imbalances across processors.

\subsubsection{Utilization Summary}
This display shows the cumulative percentage of time, over the entire
run, that each processor spent in each of the three busy/overhead/idle
states.  The percentage of time is shown on the vertical axis and the
processor number on the horizontal axis.  Again, the green/yellow/red
color scheme is used to indicate the three states.  In addition to
giving a visual impression of the overall efficiency of the parallel
program, this display also gives a visual indication of the load
balance across processors.

\subsubsection{Utilization Meter}
This display uses a colored vertical bar, with the usual
green/yellow/red color scheme, to indicate the percentage of the total
number of processors that are currently in each of the three
busy/overhead/idle states.  The visual effect is similar to that of
a thermometer or some automobile speedometers.  This display provides
essentially the same information as the Utilization Count display, but
saves screen space (which may be needed for other displays) by changing
in place rather than scrolling with time.

\subsubsection{Concurrency Profile}
For each possible number of processors $k$, $0 \leq k \leq p$, where
$p$ is the maximum number of processors for this run, this display
shows the percentage of time during the run that {\em exactly} $k$
processors were in a given state (i.e., busy/overhead/idle).  The
percentage of time is shown on the vertical axis and the number of
processors $k$ is shown on the horizontal axis.  The profile for each
possible state is shown separately, and the user can cycle through the
three states by clicking the mouse on the appropriate subwindow.  This
display is defined only at the end of the run.  The actual concurrency
profile for real programs shown by this display is usually in marked
contrast to the idealized conditions that are the basis for Amdahl's
Law, where the concurrency profile is assumed to be bimodal, with
nonzero values at $k = 1$ and $k = p$ and zero elsewhere (i.e., at any
given time the computational work is either strictly serial or fully
parallel).

\subsection{Communication Displays}

The displays described in this section are concerned primarily with
depicting interprocessor communication.  They are helpful in
determining the frequency, volume, and overall pattern of
communication, and whether there is congestion in the message queues
or on the links of the interconnection network.

\subsubsection{Communication Traffic}
This display is a simple plot of the total traffic in the communication
system (interconnection network and message buffers) as a function of
time.  The curve plotted is the total of all messages that are
currently pending (i.e., sent but not yet received), and can be
optionally expressed either by message count or by volume in bytes.
The communication traffic shown can also optionally be either the
aggregate over all processors or just the messages pending for any
individual processor the user selects.  Message volume or count is
shown on the vertical axis, and time is shown on the horizontal axis,
which scrolls as necessary.

\subsubsection{Spacetime Diagram}
This display is patterned after the diagrams used in physics,
particularly in relativity theory, to depict interactions between
particles through space and time.  This type of diagram has been used
by Lamport for describing the order of events in a distributed
computing system.  The same pictorial concept was used over a century
ago to prepare graphical railway schedules.  In our adaptation of the
Spacetime Diagram, processor number is on the vertical axis, and time
is on the horizontal axis, which scrolls as necessary as time
proceeds.  Processor activity (busy/idle) is indicated by horizontal
lines, one for each processor, with the line drawn solid if the
corresponding processor is busy (or doing overhead), and blank if the
processor is idle.  Messages between processors are depicted by slanted
lines between the sending and receiving processor activity lines,
indicating the times at which each message was sent and received.
These sending and receiving times are from user process to user process
(not simply the physical transmission time), and hence the slopes of
the resulting lines give a visual indication of how soon a given piece
of data produced by one processor was needed by the receiving
processor.

The communication lines are color coded according to the Color Code
display (see below).  Each message line is drawn when its receive time
has been reached, so this display may appear to be ``behind'' other
displays that depict messages as soon as the send event is
encountered.  The Spacetime Diagram is one of the most informative of
all the displays, since it depicts both individual processor
utilization and all message traffic in full detail.  For example, it
can easily be seen which particular message ``wakes up'' an idle
processor that was previously blocked awaiting its arrival.
Unfortunately, this fine level of detail does not scale up well to
large numbers of processors, as the diagram becomes extremely
cluttered, and its current limit is 128 processors.

\subsubsection{Message Queues}
This display depicts the size of the queue of incoming messages for
each processor by a vertical bar whose height varies with time as
messages are sent, buffered, and received.  The processor number is
shown on the horizontal axis.  At the user's option, the queue size can
be measured either by the number of messages or by their total length
in bytes.  The input queue size for a given processor is incremented
each time a message is sent to that processor, and decremented each
time the user process on that processor receives a message.

On most message-passing parallel systems, the physical transmission
time between processors is negligible compared to the software overhead
in handling messages, so that the time interval between the send and
receive events is a reasonable approximation to the time a given
message actually spends in the destination processor's input queue.  Of
course, depending on message types, the messages may not be received in
the same order in which they arrive for queuing, so the queues may grow
and shrink in complicated ways.  As before, dark shading depicts the
current queue size on each processor, and lighter shading indicates the
``high water mark'' seen so far.  The Message Queue display gives a
pictorial indication of whether there is communication congestion in a
parallel program (i.e., whether messages are accumulating in the input
queue), or the messages are being consumed at about the same rate as
they arrive.  Of course, it is best if messages arrive slightly before
they are actually needed, so that the receiving processor does not
become idle awaiting a message.  But a large backlog of incoming
messages can consume excessive buffer space, so a happy medium
(analogous to ``just in time'' manufacturing) is desirable.

\subsubsection{Communication Matrix}
In this display, messages are represented by squares in a
two-dimensional array whose rows and columns correspond to the sending
and receiving processors, respectively, for each message.  During the
simulation, each message is depicted by coloring the appropriate square
at the time the message is sent, and erasing it at the time the message
is received.  The color used is determined by the Color Code display
(see below).  Thus, the durations and overall pattern of messages are
depicted by this display.  The nodes can be ordered along the axes in
either natural, Gray code, or user-defined order, and the choice may
strongly affect the appearance of the communication pattern.  At the
end of the simulation, the Communication Matrix display shows the
cumulative statistics (e.g., communication volume) for the entire run
between each pair of processors, depending on the particular choice of
color code.

\subsubsection{Communication Meter}
This display uses a vertical bar to indicate the percentage of maximum
communication volume (or number of messages) currently pending (i.e.,
sent but not yet received).  This display provides essentially the same
information as the Communication Traffic display, but saves screen
space (which may be needed for other displays) by changing in place
rather than scrolling with time.  Conceptually, this thermometer-like
display is similar to the Utilization Meter display, except that it
shows communication instead of utilization, and the two are interesting
to observe side by side.

\subsubsection{Animation}
In this display, the parallel system is represented by a graph whose
nodes (depicted by numbered circles) represent processors, and whose
arcs (depicted by lines between the circles) represent communication
between processors.  The status of each node (busy, idle, sending,
receiving) is indicated by its color, so that the circles can be
thought of as the ``front-panel lights'' of the parallel computer.
A line is drawn between the source and destination processors when
each message is sent, and erased when the message is received.  Thus,
both the colors of the nodes and the connectivity of the graph change
dynamically as the simulation proceeds.  The lines represent the
logical communication structure of the parallel program and do not
necessarily reflect the actual interconnectivity of the underlying
physical network.  In particular, the possible routing of messages
through intermediate nodes is not depicted unless the program being
visualized does such forwarding explicitly.

The nodes can be arranged in ring, mesh, or user-defined configurations
by clicking on the appropriate subwindow.  For the mesh, the user can
also select the desired aspect ratio and row-wise or column-wise
numbering by clicking on the appropriate buttons.  In addition, the
nodes can be arranged in natural, Gray code, or user-defined order, and
the user's choice may strongly affect the appearance of the
communication pattern among processors.  The various arrangements of
the nodes are merely pictorial conveniences, and do not necessarily
imply anything about the structure of the underlying interconnection
network topology on which the parallel program was run.

If a user-defined layout is selected, then the processors can be placed
arbitrarily within the display by using the mouse.  Initially, the
nodes are arranged in a default layout.  A given node can be moved
anywhere within the window by first clicking on the chosen node to
select it, and then clicking again at the desired new location.  If
desired, a layout determined in this way can be saved in a file for
future use.  The default name for such an animation layout file is
{\tt .pganim}, but a different name can be specified using the {\tt -l}
command-line option or by typing the name into the appropriate
subwindow when using the {\tt read file} or {\tt write file} options
of the display.

Note that various combinations of states are possible for the sending
and receiving processors on either end of a message line.  For example,
both processors could be busy, one having already sent the message and
resumed computing, while the other has not yet stopped computing to
receive the message.  Upon conclusion, this display shows a summary of
all (logical) communication links used throughout the run.  Because of
its level of detail, this display is currently limited to depicting up
to 128 processors.

\subsubsection{Hypercube}
This display is similar to the Animation display, except that it
provides a number of additional layouts for the nodes in order to
exhibit more clearly communication patterns corresponding to the
various networks that can be embedded in a hypercube.  Note that this
display does not require that the interconnection network of the
machine on which the parallel program executed actually be a hypercube;
it merely highlights the hypercube structure as a matter of potential
interest.  The scheme for coloring nodes and drawing arcs is the same
as that for the Animation display, except that curved arcs are often
used to avoid, as much as possible, intersecting other nodes.  To help
the user of a hypercube to determine if the network's physical
connectivity is correctly honored by the communication in the parallel
program, message arcs corresponding to genuine physical hypercube links
are drawn in a different color from message arcs along ``virtual''
links that do not exist in a hypercube and therefore entail indirect
routing through intermediate processors.  If the actual number of
processors is not a power of two, then any ``unused'' nodes in the
selected layout are indicated by black shading.  Upon conclusion, this
display shows a summary of all (logical) communication links used
throughout the run.  Unfortunately, the method used to draw this rather
elaborate display does not scale up well to large numbers of
processors, so it is currently limited to 16.

\subsubsection{Network}
This display depicts interprocessor communication in terms of various
network topologies.  Unlike the Animation and Hypercube displays, the
Network display shows the actual path that each message takes, which
may include routing through one or more intermediate nodes between the
original source and ultimate destination.  Obviously, depicting message
routing through a network requires a knowledge of the interconnection
topology.  The user selects from among several of the most common
interconnection networks, each of which may also have a choice of
routing schemes.  Some of the available topologies are represented as
multistage networks, with duplicate sets of source and destination
nodes, between which are several ``stages'' of nodes or switches
through which intermediate routing occurs.  Networks depicted in this
manner include butterfly, hypercube, omega, baseline, and crossbar.
Other available topologies are represented by a single set of nodes
that serve as both sources and destinations, with messages moving in
either direction through the network.  Networks depicted in this manner
include binary tree, quadtree, and mesh.

Each physical link in the network is color coded according to the
number of messages currently sharing that link.  A temperature-like
color code is used, so that ``hot spots'' appear red while less heavily
used links appear blue.  In monochrome, the message count on a link is
indicated instead by the line width, so that, for example, the tree
networks look like ``fat'' trees, as the message count tends to be
higher nearer the root.  Unlike the Animation or Hypercube displays,
in the Network display the sending or receiving of a message does not
always cause the drawing or erasure of a given link, but will often
merely change its color to be one step hotter or cooler than it was
previously.  A given message may use several links, causing each link
involved to be incremented or decremented separately.  On conclusion,
the coloring of the links indicates the cumulative message count over
the entire run, and the color-code legend is recalibrated accordingly
to indicate the range of cumulative totals for the various links.

The choices of network and routing scheme (and also the aspect ratio
and row-wise or column-wise ordering for the mesh) are selected by
clicking on the appropriate subwindow.  The choice of network topology
and routing scheme need not match those of the machine on which the
parallel program actually ran, but the representation is obviously most
accurate if they do match.  On the other hand, one might want to choose
a different network deliberately in order to get some idea how a
program that ran on one topology might perform on a different
topology.  Thus, for example, the user of an Intel Paragon (mesh) can
see a visual simulation of the behavior his program might have on a
Thinking Machines CM-5 (quadtree), or vice versa.

The node numbers of the peripheral nodes are always shown, but to avoid
excessive clutter amid the message lines, by default the the interior
node numbers are omitted in the multistage and mesh networks.  All of
the node numbers can be shown, however, by clicking on the appropriate
option subwindow.  Due to its high degree of detail, this display is
currently limited to 128 processors.

\subsubsection{Node Data}
This display provides, in graphical form, detailed communication data
for any single processor the user selects.  The choices of data plotted
are the source/destination, type, length, and distance traveled for all
messages sent to or from the chosen processor.  The length of a message
is in bytes, and the distance traveled is in hops from source to
destination as determined by the distance function chosen using the
{\tt options} menu.  Time is on the horizontal axis, and the chosen
statistic is on the vertical axis, with incoming and outgoing messages
shown in separate subwindows.  This display is helpful in analyzing
communication behavior in detail, especially in perceiving trends or
patterns in the communication structure that improve understanding of
program behavior and performance.  It has been used as an aid in
designing ``synthetic programs,'' which are simple programs that mimic
the behavior and performance of much more complex programs, and are
useful for performance modeling and benchmarking.  This display is
currently limited to depicting 256 processors.

\subsubsection{Color Code}
This display permits the user to select which statistic will determine
the color code for coloring the messages in displays such as Spacetime
and Communication Matrix.  The choices include the size of the message
in bytes, the distance between the source and destination nodes
(according to the distance function chosen using the {\tt options}
menu), and the message type.  Clicking on the subwindow cycles through
the choices, and the resulting color code is displayed to enable proper
interpretation of the other displays that use it.

\subsection{Task Displays}

The displays we have considered thus far depict a number of important
aspects of parallel program behavior that help in detecting performance
bottlenecks.  However, they contain no information indicating the
location in the parallel program at which the observed behavior occurs.
To remedy this situation, we considered a number of automated
approaches to providing such information (e.g., picking up line numbers
in the source code from the compiler), but all of these encounter nasty
practical difficulties (such as dealing with multiple source files).
Thus, we reluctantly made an exception to our rule that the user need
do nothing to instrument the parallel program under study in order to
use ParaGraph.

We developed a number of ``task'' displays that use information
provided by the user, with the help of PICL, to depict the portion of
the user's parallel program that is executing at any given time.
Specifically, the user defines ``tasks'' within the program by using
special PICL routines to mark the beginning and ending of each task and
assign it a user-selected, nonnegative task number.  The scope of what
is meant by a task is left entirely to the user: a task can be a single
line of code, a loop, an entire subroutine, or any other unit of work
that is meaningful in a given application.  For example, in matrix
factorization one might define the computation of each column to be a
task, and assign the column number as the task number.  Tasks are
defined simply by calling PICL's {\tt traceblockbegin} and
{\tt traceblockend} routines, with the desired task number as argument,
immediately before and after the selected section of code.  This causes
PICL to produce event records that are interpreted appropriately by
ParaGraph to depict the given task, using displays to be described in
this section.  We emphasize that task definitions are required {\em
only} if the user wishes to view the task displays.  If the tracefile
contains no event records defining tasks, then the task displays will
simply be blank, but the remaining displays in ParaGraph will still
show their normal information.

Tasks can be nested, one inside another, but if so these should be
properly bracketed by matching task begin and end records.  More than
one processor can be assigned the same task (or, more accurately, each
processor can be assigned its own portion of the same task); indeed,
the model we have in mind is that all processors collaborate on each
task, rather than that each task is assigned to a single processor.
In many contexts, such as the matrix factorization example mentioned
above, there is a natural ordering and corresponding numbering of the
tasks in a parallel program.

In most of the task displays described below, the task numbers are
indicated by a color coding.  Since the number of tasks may be larger
than the number of colors that can be easily distinguished, we recycle
a limited number of colors to depict successive task numbers.  We use a
maximum of 64 different colors for indicating individual tasks.  To aid
in distinguishing consecutively numbered tasks (the most common case)
we stride through these 64 colors in groups of eight rather than in
strict rainbow sequence.  If desired, the user can override these
default task colors by supplying a file containing up to 64 sets of RGB
values.  The default name for such a file is {\tt .pgcolors}, but an
alternative filename can be specified on the command line by using the
{\tt -r} option.  Each line of the color file contains four integers,
the first of which is the color number (0-63) that is being replaced,
and the other three are the R, G, and B values (0-255) for the
substitute color.  In monochrome mode, stipple patterns are used to
distinguish tasks.  The eight different stipple patterns available are
recycled as needed for larger numbers of tasks.

\subsubsection{Task Count}
During the simulation, this display shows the number of processors that
are executing a given task at the current time.  The number of
processors is shown on the vertical axis and the task number is shown
on the horizontal axis.  At the end of the run, this display changes to
show a summary over the entire run.  Specifically, it shows the average
number of processors that were executing each task over the lifetime of
that task (i.e., the time interval starting when the first processor
began the task and ending when the last processor finished the task).

\subsubsection{Task Gantt}
This display depicts the task activity of individual processors by a
horizontal bar chart in which the color of each bar indicates the
current task being executed by the corresponding processor as a
function of time.  Processor number is on the vertical axis and time is
on the horizontal axis, which scrolls as necessary as the simulation
proceeds.  This display can be compared with the Utilization Gantt
chart to correlate busy/overhead/idle status with the task
information.

\subsubsection{Task Status}
In this display the tasks are represented by a two-dimensional array
of squares, with task numbers filling the array in row-wise order.
Initially, all of the squares are white.  As each task is begun, its
corresponding square is lightly shaded to indicate that the task is
now in progress.  When a task is subsequently completed, its
corresponding square is then darkly shaded.

\subsubsection{Task Summary}
This display, which is defined only at the end of the simulation run,
indicates the duration of each task (from earliest beginning to last
completion by any processor) as a percentage of the overall execution
time of the parallel program, and furthermore places the duration
interval of each task within the overall execution interval of the
parallel program.  The percentage of the total execution time is shown
on the vertical axis, and the task number is shown on the horizontal
axis.

\subsection{Other Displays}

In this section we describe some additional displays that either do not
fit into any of the three categories above or else cut across more than
one category.

\subsubsection{Clock}
This display provides both digital and analog clock readings during the
graphical simulation of the parallel program.  The current simulation
time is shown as a numerical reading, and the proportion of the full
tracefile that has been completed thus far is shown by a colored
horizontal bar.  The clock reading is updated synchronously with the
other displays, and it ``ticks'' through all integral time values,
not just those that happen to correspond to event timestamps.

\subsubsection{Trace}
This is a non-graphical display that prints an annotated version of
each trace event as it is read from the tracefile.  It is primarily
useful in the single-step mode for debugging or other detailed study of
the parallel program on an event-by-event basis.  Although the trace
records are drawn in this display one at a time, space is allowed to
show several consecutive trace records in context, and the display
scrolls vertically as necessary with time.  By default, all trace
events are printed, but events can be printed selectively by node or
type by changing the appropriate setting in the {\tt options} menu.

\subsubsection{Statistical Summary}
This is a non-graphical display that gives numerical values for various
statistics summarizing processor utilization and communication, both
for individual processors and aggregated over all processors.  The data
provided include percentage of busy, overhead, and idle time; total
count and volume of messages sent and received; maximum queue size; and
maxima, minima, and averages for the size, distance traveled (according
to the distance function chosen using the {\tt options} menu), transit
time, and overhead incurred for both incoming and outgoing messages.
While this tabular display may yield less insight than the graphical
displays provided by ParaGraph, exact numerical quantities are
occasionally useful in preparing tables and graphs for printed reports,
or for analytical performance modeling.  Due to limited space on the
screen, this display shows data for at most 16 processors at a time,
but the subset of processors shown can be varied by clicking the mouse
on the subwindow provided, which enables one to browse the entire data
array.

\subsubsection{Processor Status}
This is a comprehensive display that attempts to capture detailed
information about processor utilization, communication, and tasks,
but in a compact format that scales up well to large numbers of
processors.  This display contains four subdisplays, in each of which
the processors are represented by a two-dimensional array of squares,
with processor numbers filling the array in row-wise order.
The upper left subdisplay shows the current state of each processor
(busy/overhead/idle), using the usual green/yellow/red color scheme.
The upper right subdisplay shows the task currently being executed
by each processor, using the same task coloring scheme as discussed
previously.  The lower left subdisplay shows the volume of messages
currently being sent by each processor, and the lower right subdisplay
shows the volume of messages currently awaiting receipt by each
processor; both of these communication subdisplays indicate message
volume in bytes using the same color code as discussed previously for
the other communication displays.  Although this comprehensive display
is somewhat difficult to follow due to the large amount of information
it contains, it has the virtue of readily scaling to very large numbers
of processors.

\subsubsection{Critical Path}
This display is similar to the Spacetime display described earlier, but
uses a different color coding to highlight the longest serial thread in
the parallel computation.  Specifically, the processor and message
lines along the critical path are shown in red, while all other
processor and message lines are shown in light blue.  This display is
intended to aid in identifying performance bottlenecks and tuning the
parallel program by focusing attention on the portion of the
computation that is currently limiting performance.  Any improvement in
performance must necessarily shorten the longest serial thread running
through the computation, so this is a primary place to look for
potential algorithm improvements.  For larger numbers of processors,
the noncritical message lines are suppressed so that they do not
obscure the critical path.

\subsubsection{Phase Portrait}
This display is patterned after the phase portraits used in
differential equations and classical mechanics to depict the
relationship between two variables (e.g., position and velocity) that
depend on some independent variable (e.g., time).  In our case, we are
attempting to illustrate pictorially the relationship over time between
communication and processor utilization.  At any given point in time,
the current percentage utilization (i.e., the percentage of processors
that are in the busy state), and the percentage of the maximum volume
of communication currently in transit, together define a single point
in a two-dimensional plane.  This point changes with time as
communication and processor utilization vary, thereby tracing out a
trajectory in the plane that is plotted graphically in this display,
with communication and utilization on the two axes.  To filter out
noise in plotting the trajectory, this display uses the same smoothing
interval as the Kiviat diagram, and thus the amount of smoothing can be
controlled via the {\tt options} menu.

Since the overhead and potential idleness due to communication inhibit
processor utilization, one expects communication and utilization
generally to have an inverse relationship.  Thus one expects the phase
trajectory to tend to lie along a diagonal of the display.  This
display is particularly useful for revealing repetitive or periodic
behavior in a parallel program, which tends to show up in the phase
portrait as an orbit pattern.  The color used for drawing the
trajectory is determined by the current task number on processor 0
(default is black if no such task is active), so by setting task
numbers appropriately, the user can color code the trajectory to
highlight either major phases or individual orbits.

\subsubsection{Coordinate Information}
The Info display is a non-graphical display used to write information
produced by mouse clicks on the other displays.  Many of the displays
respond to mouse clicks by printing in the Info display the coordinates
(in units meaningful to the user) of the point at which the cursor is
located at the time the button is pressed.  This feature is intended to
enable the user to determine precisely information that may be
difficult to read accurately from the axis scales alone.  In addition,
clicking a mouse button with the cursor placed on one of the nodes in
the Animation display causes the following information to be printed in
the Info display: node number, task number (if any), number of incoming
messages pending, number of outgoing messages pending.  The latter
information can be used in conjunction with the color code in the
Animation display to determine the exact state of the nodes more
precisely.

\subsection{Application-Specific Displays}

All of the displays we have discussed thus far are generic in the sense
that they are applicable to any parallel program based on message
passing and do not depend on the particular application or problem
domain that the program addresses.  While this wide applicability is
generally a virtue, knowledge of the specific application can often
enable one to design a special-purpose display that reveals greater
detail or insight than generic displays alone would permit.  In
studying a parallel sorting algorithm, for example, generic displays
can show which processors are communicating with each other, and the
volume of communication, but they cannot show which specific data items
are being exchanged between processors.  Since we obviously could not
provide such application-specific displays as part of ParaGraph, we
instead made ParaGraph extensible so that users can add
application-specific displays of their own design that can be selected
from a menu and viewed along with the usual generic displays.

The mechanism we use for supporting this capability works as follows.
ParaGraph contains calls at appropriate points to routines that provide
initialization, data input, event handling, drawing, etc., for
application-specific displays.  If the corresponding routines for such
displays are not supplied by the user when the executable module for
ParaGraph is built, then dummy ``stub'' routines are linked into
ParaGraph instead, and the {\tt user} submenu selection does not appear
on the main menu in the list of available submenus.  If
application-specific displays have been linked into ParaGraph and the
resulting module is executed, then a {\tt user} item appears in the
main menu, and its selection opens a {\tt user} submenu that is
analogous to the other submenus of available displays.  The {\tt user}
submenu may contain any number of separate user-defined displays that
can be selected individually.  Each such user-supplied display is given
access to all of the event records in the tracefile that ParaGraph
reads, as well as all X events, and can use them in any manner it
chooses.  Thus, the user-supplied displays can receive input
interactively via the mouse or keyboard.

The usual events generated by PICL may suffice for the
application-specific displays, or the user may wish to insert
additional events during execution of the parallel program in order to
supply additional data for the application-specific display.  The
{\tt tracedata} command of PICL is perhaps the most useful for this
purpose, as it allows the user to insert into the tracefile timestamped
records containing arbitrary lists of integers, which might be used to
provide loop counters, array indices, memory addresses, identifiers of
particles or transactions, or any other information that would enable
the user-supplied display to convey more fully and precisely the
activity of the parallel program in the context of the particular
application.

Unfortunately, writing the necessary routines to support
application-specific displays is a decidedly nontrivial task that
requires a general knowledge of X Window System programming.  But at
least the potential user of this capability can concentrate on only
those portions of the graphics programming that are relevant to his
application, taking advantage of the supporting infrastructure of
ParaGraph to provide all of the other necessary facilities to drive the
overall graphical simulation.  As an aid to users who may wish to
develop application-specific displays to add to ParaGraph, we have
developed several prototype displays for depicting such applications as
parallel sorting algorithms, recursive matrix transposition, general
matrix computations, and graph algorithms, and for displaying operation
counts (e.g., flops, particles, transactions).  These example routines
are distributed along with the source code for ParaGraph.

\section{Options}

The execution behavior and visual appearance of ParaGraph can be
customized in a number of ways to suit each user's taste or needs.
The individual items in the {\tt options} menu are described in this
section.  Some of the menu items cycle through the available choices
as the mouse is clicked on the corresponding subwindow, while others
accept keyboard input to specify numerical values or character
strings.  The type of user input expected for a given menu entry is
indicated by the type of mouse cursor it displays.  For the menu items
that take keyboard input, existing values can be erased by the
{\tt backspace} or {\tt delete} keys.  When typing a new value, the
characters are echoed in reverse video.  Hitting the {\tt return} key
completes the keyboard input and makes the new value take effect, at
which point the new characters revert to normal video display.

In this section, we briefly discuss some of the choices available in
the {\tt options} menu.

\begin{itemize}

\item Order: In many of the displays, the user can choose to have the
processors arranged in natural, Gray code, or user-defined order, and
the choice will affect the appearance of communication patterns.  The
Gray code order is not permitted if the number of processors is not a
power of two.  If desired, a user-defined ordering can be supplied by
means of an order file.  The default name for an order file is
{\tt .pgorder}, but an alternate filename can be given by using the
{\tt -o} command-line option.  An order file contains two numbers per
line, the first of which is a node number and the second of which
is the desired position of that node in the user-defined order.
Optionally, a third field can be specified on each line which, if
present, is interpreted as a character string to be used as the name
for that node.  The ability to rename the nodes is intended to support
heterogeneity in either the application program (e.g., master-slave) or
the underlying architecture (e.g., a network of various workstations),
in which case it may be desirable to be able to distinguish nodes of
different types.  Due to limited space available in the displays where
they will be used, node names are limited to three characters.  If no
order file is supplied by the user, then the {\tt user} item does not
appear among the choices for the ordering.

\item Scrolling: Those windows that represent time along the horizontal
dimension of the screen can smoothly scroll or jump scroll by a
user-specified amount as simulation time advances.  Smooth scrolling
provides an appealing sense of visual continuity, but results in a
slower drawing speed.

\item Time Unit: The relationship between simulation time and the
timestamps of the trace events is determined by the {\tt time unit}
chosen.  By convention, PICL provides event timestamps with a
resolution of microseconds.  Consequently, a value of 100 for the time
unit in ParaGraph, for example, means that each ``tick'' of the
simulation clock corresponds to 100 microseconds in the original
execution of the parallel program.  During preprocessing, ParaGraph
scans the timestamps in the the tracefile and attempts to determine a
reasonable value for the time unit.  The user can override this
automatic choice, however, simply by entering a different choice in the
{\tt time unit} subwindow.  Once the time unit is set, all displays (as
well as user input) are expressed in terms of this time unit rather
than the units of the original raw timestamps in the tracefile.

\item Magnification: This parameter determines the visual resolution of
the horizontal axis in the displays that scroll with time.  It specifies
the number of pixels on the screen that represent each unit of simulation
time.  A larger number of pixels per time unit magnifies the horizontal
dimension of the scrolling displays to bring out more detail, but with
less of the overall behavior of the program visible at once.  The
choices available for the magnification factor are 1, 2, 4, and 8.  The
user can override the default value chosen automatically by ParaGraph.
The visual effect of this parameter is much like that of using a
magnifying glass of the given power.  The magnification factor and the
time unit, as we have defined them, are related to each other in the
effect they have on the appearance of the displays that scroll with
time, but they serve distinct purposes: the choice of {\tt magnification}
determines the visual resolution of the drawing on the screen, while
the choice of {\tt time unit} determines the time resolution of trace
events.  Thus, these two quantities can be varied in concert to produce
any desired effect.

\item Start Time and Stop Time: By default, ParaGraph starts the
simulation at the beginning of the tracefile and proceeds to the end of
the tracefile.  By choosing other starting and stopping times, however,
the user can isolate any particular time period of interest for visual
scrutiny without having to view a possibly long simulation in its
entirety.  Once the specified stopping time is reached, the simulation
pauses, and then can be resumed by typing a new (still later) stopping
time, or by clicking on the {\tt pause/resume} menu button, or by
clicking on the {\tt step} menu button to proceed from this point in
single-step mode.

\item Step Increment: This parameter determines how many consecutive
records from the tracefile are processed each time the {\tt step}
button is pressed on the {\tt controls} menu.  The default value of one
provides the finest control for detailed scrutiny, but can be tedious
and time consuming to use, so the user may prefer a larger value.

\item Smoothing Interval: The user can select the amount of smoothing
used in the Kiviat Diagram and Phase Portrait displays to avoid an
excessively noisy or jumpy appearance.  The amount of smoothing is
determined by the width of a moving time interval, with a larger value
giving more smoothing and a smaller value giving less smoothing.  This
parameter is expressed in simulation time units and it can be changed
simply by typing a new value.

\item Pause on Tracemark/msg: Another way to stop the simulation for
detailed study at a given predetermined point is to insert
{\tt tracemark} or {\tt tracemsg} event records into the tracefile
during the original execution of the parallel program.  These special
records provided by PICL can be used to mark milestones in the user's
program, such as the completion of a major phase of the program or the
beginning of a new one, or a point at which a bug is suspected.  This
provides a program-dependent means of isolating particular points of
interest for close scrutiny.  After the simulation has stopped at a
{\tt tracemark} or {\tt tracemsg} event, it can be resumed by any of
the usual actions, including single stepping.

\item Pause on Error: This option determines whether the simulation is
paused if an error is detected, such as a mismatched send/receive pair
or incorrectly nested blocks.  Again, the simulation can be resumed by
any of the usual actions.

\item Trace Node and Trace Type: These parameters determine which trace
events are printed in the Trace display window.  This feature allows
the user to focus on events for a specific node and/or of a specific
type, since looking at every event for every processor can be tedious
and time consuming.  The default value for both parameters is {\tt all}.

\item Print Command: This specifies the command string used by the
{\tt screen dump} button on the {\tt controls} menu to route images to a
printer for hardcopy output.  The default print command is installation
dependent.  It can be changed simply by typing a new print command in
this subwindow.  The command string will often include invocation of a
remote shell and piping through a number of filters for converting
image formats, etc., before reaching the physical output device.

\item Distance Function: This option determines the network topology
used to compute the distance traveled by each message, which may be
used in some displays for color coding messages and is also tallied in
summaries of communication statistics.  The choices available include
Hamming distance (appropriate for hypercubes, for example), 1-D and 2-D
mesh (without wrap-around), 1-D and 2-D torus (with wrap-around),
binary tree, quadtree, and unit distance (appropriate for a fully
connected network, for example).  For the mesh and torus, the user also
selects the desired aspect ratio and whether the processors are
numbered row-wise or column-wise.  The choice of distance function
does not necessarily have to agree with the layout or topology chosen
for the Animation and Network displays.

\end{itemize}

\section{Record Options}

The data generated by ParaGraph for drawing the various displays can be
saved in files, if desired.  Such data may be useful for inclusion in
printed documents, for mathematical modeling or statistical analysis of
performance, or as input to other graphical packages.  The {\tt record
options} menu is used to select which displays, if any, are to have
their data recorded in files on disk during the simulation.  Each data
file created in this manner will have the name shown in the prefix
subwindow, with a suffix added to indicate the particular display
name.  The default filename prefix is the path name of the tracefile, if
one was specified on the command line when ParaGraph was invoked.  The
filename prefix can be changed by entering a new name into the prefix
subwindow.  Another subwindow allows the user to specify start and stop
times for saving data in files, which by default include the entire
run.  Each data file produced in this manner begins with a header that
identifies the subsequent fields, followed by one line of data per
event.

\section{General Advice}

In this section we provide a few tips that may make using ParaGraph
easier and more meaningful.  Perhaps the most important piece of advice
is to keep the tracefile to be viewed as small as possible without
losing the phenomenon to be studied.  The best way to accomplish this
is to use a relatively small number of processors and a brief execution
time.  Although ParaGraph currently supports the use of up to 512
processors, and has no limit on the duration of the simulation run, the
size of the tracefile for a large number of processors and/or a long
execution time can be enormous (many megabytes).  Such large tracefiles
can quickly consume large amounts of disk space and will require a
great deal of time for ParaGraph to preprocess and then animate
visually.  Fortunately, in our experience, basic algorithm behavior and
most fundamental bottlenecks and inefficiencies in parallel programs
are usually already apparent when viewed with small numbers of
processors and relatively small test problems that run quickly.
Moreover, many programs display repetitive behavior, so that only a few
iterations need be examined in detail in order to get the gist of their
behavior, rather than a long sequence of replicated behavior.  In a
lengthy program, it is also a good idea to invoke PICL's tracing
commands only for the portion of immediate interest.

On some machines, a more insidious problem with large numbers of
processors and/or long run times is the increasing probability of
``tachyons'' in the tracefile as the number of processors increases and
as individual processor clocks drift apart with time.  In creating
tracefiles for viewing with ParaGraph, be sure to use the highest
resolution clock and sharpest clock synchronization that PICL offers.
On machines with independent node clocks, PICL will try to compensate
for clock skew and drift by monitoring clock behavior during a brief
interval before the program begins execution.  To increase the accuracy
of this computation, you might try calling {\tt clocksync0} at the end
of your program, just before calling {\tt close0} on each node.  This
will cause the entire duration of your run to be used in determining
the appropriate adjustment for clock drift, improving its statistical
significance.  Tachyons may cause unpredictable behavior in ParaGraph,
possibly including outright failure.  Therefore, before reporting
``bugs'' in ParaGraph, check the tracefile for tachyons using the awk
script {\tt tachyon.awk} supplied in the ParaGraph distribution, which
will print any tachyons it finds and otherwise remain silent.  Other
common causes of faulty tracefiles include failure to sort into time
order, inadvertent concatenation of multiple tracefiles, and incomplete
tracefiles due to full trace buffers.

Another way to reduce the size of the tracefile is to refrain from
tracing on the host.  ParaGraph ignores all events involving the host
anyway, so tracing on the host pointlessly clutters the tracefile with
data that are irrelevant to the visualization.  The decision to ignore
the host in ParaGraph was based on a number of factors, including the
difficulty of representing a host pictorially without spoiling the
symmetry of many of the displays, the difficulty of obtaining accurate
and reliable timestamps on a time-shared multiuser host, the fact that
most parallel programs do not use the host for any substantive
computations anyway, and the fact that many vendors support multiple
hosts or are eliminating the need for separate hosts in their systems.

The various parameters given in the {\tt options} menu can have a
dramatic effect on the behavior of ParaGraph for a given tracefile, and
the user may or may not find the default values to be the most
desirable.  For example, during preprocessing a rough heuristic is used
to choose an appropriate {\tt time unit}, and the value chosen strongly
affects the appearance and behavior of the scrolling displays.  An
attempt is made to choose a value that will fill at least one window
width but not need to scroll more than a few window widths.  The value
chosen automatically may be so large that it obscures detail the user
would like to see, or so small that the simulation runs for too long.
So, the user should feel free to adjust the value for the {\tt time
unit}, if desired.  Note, however, that the {\tt magnification} parameter
also affects the visual resolution of the scrolling displays, so it may
also be changed to produce a desired effect.  In addition, the speed of
the drawing is strongly affected by the type and amount of scrolling
employed, so this is subject to experimentation as well.  In using the
Kiviat Diagram and Phase Portrait displays, some experimentation with
the {\tt smoothing interval}, as well as the {\tt time unit}, may be
required to produce the most meaningful visual results.

As pointed out previously, the execution speed of ParaGraph is normally
determined by how fast it can read trace records and perform the
resulting drawing.  If the visual simulation is too rapid for the eye
to follow, then its execution can be slowed down either by using the
{\tt slow motion} slider or else by selecting some additional displays,
especially those that scroll with time.  If the visual simulation is
too slow, it can be speeded up by using fewer displays at a time or by
selecting jump scrolling.  Changing the {\tt time unit} and/or
{\tt magnification} also affects the drawing speed, so these are subject
to experimentation as well.  Finally, the {\tt step} button or
repeatedly hitting {\tt pause/resume} can also be used to control the
speed with which the animation unfolds.  By some combination of these
means, the user should be able to produce an animation speed that can
be followed visually in sufficient detail, yet does not take an
inordinate amount time to finish.

In building an executable module for ParaGraph from the distributed
source code, there are a few compile-time parameters that the user
may wish to modify for a particular situation.  These parameters are
found in the {\tt defines.h} file.  The parameters most likely to
require modification are as follows:
\begin{itemize}
\item[{\tt ALL}] integer destination value used to indicate global
sends (default -1),
\item[{\tt HOST}] integer identifier for the host processor
(default -32768, consistent with PICL),
\item[{\tt MAXP}] maximum number of node processors allowed
(default 128, maximum possible 512).
\end{itemize}
The usual default for the maximum number of nodes allowed is set at
128 in order to conserve memory.  {\tt MAXP} can be increased up to 512
to accommodate larger systems, but this may cause sluggish performance
and should be avoided unless necessary.

By default, ParaGraph uses two fonts, namely {\tt 6x12} and {\tt 8x13},
which are both available in most distributions of X Windows.  In case
these fonts are not available, however, the names of alternate
constant-width fonts of similar size can be substituted into the
initialization of {\tt font1\_name} and {\tt font2\_name} in the
{\tt defaults.h} file.

\section{Future Work}

In terms of the number and appearance of displays it provides,
ParaGraph is a reasonably mature software tool, although we intend to
add more displays as helpful new perspectives are devised.  There are a
few technical points about ParaGraph that could stand improvement.  The
contents of many of the displays are lost if the window is obscured and
then reexposed.  This inability to repair or redraw windows, short of
rerunning the simulation from the beginning, was a deliberate design
decision based on a desire to conserve the substantial amount of memory
that would be required to save the contents of all windows for possible
restoration.  Nevertheless, this ``feature'' can be annoying at times
and should eventually be fixed.  A related problem is that ParaGraph
cannot reliably support dynamic changes in parameters during a
simulation run (e.g., dynamic zooming of the time resolution).

A more serious limitation of ParaGraph in its current form is the
number of processors that can be depicted effectively.  A few of the
current displays are simply too detailed to scale up beyond about 128
processors and still be comprehensible.  Most of the displays scale up
well to a level of 512 or 1024 processors on a normal sized workstation
screen, but at this point they are down to representing each processor
by a single pixel (or pixel line), and hence cannot be scaled any
further in their current form.  To visualize programs for massively
parallel architectures having thousands of processors, we must devise
new displays that scale up to this level, or else we must adapt the
existing displays, either by aggregating or selecting information.
For example, the current displays could depict either clusters of
processors or subsets of individual processors (e.g., cross sections).

While it is fairly easy to imagine how graphics technology might be
adapted to meet the needs of visualizing massively parallel
computations, it is much less obvious how to handle the vast volume of
execution trace data that would result from monitoring thousands of
processors.  Even with the more modest numbers of processors currently
supported by ParaGraph, storage and processing of the large volume of
trace data resulting from runs of significant duration are already
difficult problems.  To go beyond the present level will almost
certainly require some degree of abstraction of essential behavior in a
more concise and compact form, both in the data and in its graphical
presentation.  We simply cannot afford to continue to record or display
all communication events when they become so voluminous.  Unfortunately,
many of the current displays in ParaGraph depend critically on the
availability of data on each individual event.  Thus, the development
of new visual displays and new data abstractions must proceed in tandem
so that the execution monitoring facility will produce data that can be
visually displayed in a meaningful way to provide helpful insights into
program behavior and performance.

\section{Acknowledgements}  The original implementation of ParaGraph
was done almost entirely by undergraduate students during research
internships at Oak Ridge National Laboratory.  The overall structure of
the software and the conceptual designs of the individual displays were
developed by Michael Heath.  Most of the programming for the initial
release of ParaGraph was done by Jennifer Finger (then Etheridge) while
she was an undergraduate student, first at Roanoke College and later at
the University of Tennessee.  Heath and Finger have continued joint
development of ParaGraph since he moved from ORNL to the University of
Illinois and she became a regular staff member at ORNL.  Two other
undergraduate students also contributed to the development of
ParaGraph: Loretta Auvil, then of Alderson Broaddus College, originally
developed the Hypercube display, and Michelle Hribar, then of Albion
College, developed the first two application-specific displays (to
illustrate parallel sorting and matrix transposition) as extensions to
ParaGraph.  In each case these undergraduates began their work on
ParaGraph without any prior knowledge of Unix, C, workstations,
computer graphics, or the X Window System, and within a single term
each was contributing to the relatively sophisticated software tool
described in this manual.  Thus, the development of ParaGraph has been
an interesting educational experiment that has provided a useful tool
for the performance analysis of parallel programs.

This research was supported by the Applied Mathematical Sciences
Research Program, Office of Energy Research, U.S. Department of Energy
under contract DE-AC05-84OR21400 with Martin Marietta Energy Systems,
Inc.

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{\bf Biographies}

{\em Michael T. Heath} is Professor in the Department of Computer
Science and Research Scientist at the National Center for
Supercomputing Applications at the University of Illinois in
Urbana-Champaign.  Previously he was a Senior Research Staff Member and
Computer Science Group Leader in the Mathematical Sciences Section at
Oak Ridge National Laboratory.  He received a Ph.D. in Computer Science
from Stanford University in 1978.  His current research interests are
in large-scale scientific computing on parallel computers, numerical
linear algebra, and performance visualization.  He can be contacted by
email at the following address: {\tt heath@ncsa.uiuc.edu}.

{\em Jennifer E. Finger} is a Technical Research Associate in the
Mathematical Sciences Section at Oak Ridge National Laboratory.  She
received a B.S. degree from the University of Tennessee, Knoxville, in
1990, with a major in Mathematics.  Her current interests are in
computer graphics and visualization.  She can be contacted by email at
the following address: {\tt jenn@msr.epm.ornl.gov}.

\newpage
\begin{verbatim}
ParaGraph(L)             LOCAL COMMANDS              ParaGraph(L)



NAME
     ParaGraph - performance visualization of parallel programs

SYNOPSIS
     PG [-c | -g | -m] [-d hostname:0.0] [-e envfile] [-f  trace-
     file]  [-l  layoutfile]  [-n  windowname] [-o orderfile] [-r
     rgbfile]

DESCRIPTION
     ParaGraph is a graphical display system for visualizing  the
     behavior  and  performance  of parallel programs on message-
     passing parallel computers.  It  takes  as  input  execution
     trace  data provided by PICL (Portable Instrumented Communi-
     cation Library), developed at Oak Ridge National  Laboratory
     and available from netlib.  PICL optionally produces an exe-
     cution trace during an actual run of a parallel program on a
     message-passing  machine,  and  the resulting trace data can
     then be replayed pictorially with  ParaGraph  to  display  a
     dynamic, graphical depiction of the behavior of the parallel
     program.  ParaGraph provides several  distinct  visual  per-
     spectives from which to view processor utilization, communi-
     cation traffic, and other performance data in an attempt  to
     gain insights that might be missed by any single view.

     ParaGraph is based on the X Window System and runs on a wide
     variety of graphical workstations.  It uses no X toolkit and
     requires only Xlib.  Although ParaGraph is most effective in
     color,  it  also works on monochrome and grayscale monitors.
     It  has  a  graphical,  menu-oriented  user  interface  that
     accepts  user  input  via  mouse clicks and keystrokes.  The
     execution of  ParaGraph  is  event  driven,  including  both
     user-generated X Window events and trace events in the input
     data file provided by  PICL.   Thus,  ParaGraph  displays  a
     dynamic depiction of the parallel program while also provid-
     ing responsive interaction with the user.   Menu  selections
     determine  the  execution  behavior of ParaGraph both stati-
     cally (e.g., initial  selection  of  parameter  values)  and
     dynamically  (e.g.,  pause/resume, single-step mode).  Para-
     Graph preprocesses the input tracefile to determine relevant
     parameters (e.g., time scale, number of processors) automat-
     ically before the graphical  simulation  begins,  but  these
     values can be overridden by the user, if desired.

     ParaGraph currently provides about 25 different displays  or
     views, all based on the same underlying trace data, but each
     giving a  distinct  perspective.   Some  of  these  displays
     change dynamically in place, with execution time in the ori-
     ginal run represented by  simulation  time  in  the  replay.
     Other  displays represent execution time in the original run
     by one space dimension on the screen.  The  latter  displays
     scroll  as  necessary  (by  a  user-controllable  amount) as
     visual simulation time progresses.  The  user  can  view  as
     many  of  the  displays  simultaneously  as  will fit on the
     screen, and all visible windows are updated appropriately as
     the  tracefile  is read.  The displays can be resized within
     reasonable bounds.  Most of the displays depict  up  to  512
     processors in the current implementation, although a few are
     limited to 128 processors and one is limited to 16.

     ParaGraph is extensible so that users can add  new  displays
     of  their  own  design  that  can be viewed along with those
     views already provided.  This capability  is  intended  pri-
     marily to support application-specific displays that augment
     the insight that can be gained from the generic  views  pro-
     vided  by  ParaGraph.   Sample application-specific displays
     are supplied with the  source  code.   If  no  user-supplied
     display  is  desired,  then dummy "stub" routines are linked
     with ParaGraph instead.

     The ParaGraph source code comes with several  sample  trace-
     files for use in demonstrating the package and verifying its
     correct installation.  To create  your  own  tracefiles  for
     viewing  with  ParaGraph,  you will need PICL, which is also
     available from netlib.  The tracing option of PICL  produces
     a  tracefile with records in node order.  For graphical ani-
     mation with ParaGraph, the tracefile needs to be sorted into
     time  order,  which  can  be accomplished with the Unix sort
     command:

     % sort +2n -3 +0n -1 +1rn -2 tracefile.raw > tracefile.trf

     When using PICL to produce tracefiles for viewing with Para-
     Graph,  set  tracelevel(4,4,0)  to  produce the trace events
     required by ParaGraph.  You may also want  to  define  tasks
     using the traceblockbegin and traceblockend commands of PICL
     to delimit sections of code and assign them task numbers  to
     be  depicted  by ParaGraph in some of its displays as an aid
     in correlating the visual simulation with your parallel pro-
     gram.   ParaGraph does not depict a "host" processor graphi-
     cally and ignores all trace events involving  the  host,  so
     tracing  on the host is not encouraged when the tracefile is
     to be viewed using ParaGraph.

OPTIONS
     The following command-line options are  supported  by  Para-
     Graph.
     -c   to force color display mode.
     -d   to specify a hostname and screen (e.g., hostname:0.0)
          for remote display across a network.
     -e   to specify an environment file (default: .pgrc).
     -f   (or no switch) to specify a tracefile directory path or
     filename.
     -g   to force grayscale display mode.
     -l   to specify an animation layout file (default: .pganim).
     -m   to force monochrome display mode.
     -n   to specify a name for the base window  (default:  Para-
     Graph).
     -o   to specify an order file (default: .pgorder).
     -r   to specify a file containing RGB values of task colors
          (default: .pgcolors).

     By default, ParaGraph automatically detects the  appropriate
     display  mode  (color, grayscale, or monochrome), but a par-
     ticular display mode can  be  forced,  if  desired,  by  the
     corresponding command-line option.  This facility is useful,
     for example, in making  black-and-white  hardcopies  from  a
     color monitor.

FILES
     The following environment files can optionally  be  supplied
     by   the   user  to  customize  ParaGraph's  appearance  and
     behavior.  The default filenames given below can be  changed
     by the appropriate command-line options.
      .pgrc         defines the initial state of ParaGraph upon
                    invocation, including which menus and
                    displays are open and various options.
      .pgorder      defines an optional order or alternative
                    names for the processors.
      .pgcolors     defines the color scheme to be used for
                    identifying tasks.
      .pganim       defines an animation layout file.

     The following files are provided in the ParaGraph  distribu-
     tion from netlib.
      *.c           several C source files.
      *.h           several include files.
      Makefile.*    sample makefiles for several machine
                    configurations, which should be modified to
                    incorporate the local location for Xlib, etc.
      manual.tex    a user guide in Latex format.
      pg.man        a Unix man page.
      tracefiles    a directory containing several sample
                    tracefiles.
      u_*           several directories containing example
                    application-specific displays.

SEE ALSO
     A machine-readable manual for ParaGraph, in Latex format, is
     provided along with the source code from netlib.  Additional
     information is contained in the article "Visualizing Perfor-
     mance  of  Parallel Programs" in the September 1991 issue of
     IEEE Software, pages 29-39,  and  in  the  technical  report
     ORNL/TM-11813.   Documentation  for  PICL  is available from
     netlib  and  in  the  technical  reports  ORNL/TM-11130  and
     ORNL/TM-11616.

BUGS
     Some of the displays are not repaired when re-exposed  after
     having been partially obscured.  Changing parameters dynami-
     cally while the visual animation is active may give  erratic
     results.   The  apparent speed of visual animation is deter-
     mined primarily by the drawing speed of the workstation  and
     is  not  necessarily  uniformly proportional to the original
     execution speed of the parallel program.

AUTHORS
     Michael T. Heath and Jennifer E. Finger

\end{verbatim}

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