The MEDEA Experiment

Can You Accelerate Simulation-based Learning by

Combining Information Visualization and Interaction Design Principles?

Christopher J. Garasi

, Richard R. Drake

, John-Mark Collins

Rafael Picco

and Benjamin E. Hankin

Sandia National Laboratories, Albuquerque, New Mexico, U.S.A.

Ideum, Coralles, New Mexico, U.S.A.

Keywords: Scientific Visualization, Interaction Design, Accelerated Learning, High-performance Computing.

Abstract: The intent of the multipurpose display engineering analysis (MEDEA) experiment was to apply the

principles of computer-mediated learning and “play” in the context of high-performance computing (HPC)

modeling analysis. Our approach involved the development of software workflow based on interaction

design principles using a team of graphic artists, experts in graphics- and touch-based displays, computer

programmers, and scientists. The desired outcome was to develop software to overcome perceived HPC

modeling usage and learning barriers common to scientific modeling and visualization. Using multiple

interaction types, a variety of user workflow experiences were captured (novice/learner, analyst, expert)

resulting in a more intuitive and enjoyable experience with a workflow which fosters accelerated learning.

1 INTRODUCTION

High-performance computing (HPC) simulation

codes have been developed to study both simple and

complex physical phenomena such as gravity,

motions of springs, electricity and magnetism,

weather, and fluid motion. Due to their pedigree

these codes invoke an antiquated workflow

paradigm to setup and execute a simulation. A

simulation “input deck” is the ASCII maturation of a

“card deck” once used to program computers (Jones,

2014). An input deck can contain hundreds of lines

of specialized syntax (sometimes cryptic) which a

software input parser then interprets to select the

appropriate physics, define the computational

domain, establish boundary and initial conditions,

initialize materials and their geometry, and specify

variable definitions and output frequency. The input

deck driven simulation workflow can be

summaryzed as both functional and miserable from

an interaction design point of view.

Interaction design entails “designing interactive

products to support the way people communicate

and interact in their everyday and working lives”

(Preece, Sharp, and Rogers, 2015). In the most

successful cases, interactive software is designed

with the user experience in mind (resulting in

engagement and enjoyment). Learnability is a key

element of interaction design as users commonly

dislike spending a lot of time learning how to use the

software.

The typical HPC simulation code workflow

involves the disjointed steps of editing an input

deck, exiting, executing the code (via command

line), and then using an external software package

for results visualization. Novice users experience

multiple barriers to using HPC codes. These barriers

include access to machines with the required

operating systems to run the codes (e.g. Linux), lack

of familiarity with editing software on those

platforms, command line syntax, as well lack of

familiarity with sophisticated visualization software

(e.g. Paraview, Visit, GiD).

Contrast the novice HPC code user experience

with a user installing and running an application on

their smartphone. The level of sophistication of the

smartphone application is not comparable to a HPC

code, however there is a precedent for ease-of-

installation, ease-of-use (or learnability) and

complete functionality contained within the

application. Smartphone applications are not

designed to stovepipe workflow such that the user

has to enter information in one application, then exit,

and then enter another application to run or post-

Garasi C., Drake R., Collins J., Picco R. and Hankin B.

The MEDEA Experiment - Can You Accelerate Simulation-based Learning by Combining Information Visualization and Interaction Design Principles?.

DOI: 10.5220/0006228202990304

In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), pages 299-304

ISBN: 978-989-758-228-8

299

process. In fact, the smartphone application drive for

quality visualization, interaction, speed, and

availability has been established by feedback from

the two-thirds of the American population (Smith,

2015) who own smartphones and a median value of

54% of smartphone users (billions) in emerging or

developing countries (Poushter, 2015).

It is clear that new application interaction and

design practices which are commonly accepted in

social and recreational smartphone application

activities are a paradigm beyond traditional

approaches (Ito, 2009) for HPC modeling. These

new interaction design practices impact what forms

of learning younger generations value and potential-

ly point the way for new workflow practices to be

adopted. Adoption of these new practices can impro-

ve the quality of the workflow for more mature

generations and creates workflow which is already

natural to the younger developing generations.

The intent of the MEDEA experiment was to

establish a seamless workflow between the user and

the HPC code. To the extent possible the input deck

paradigm should be transparent to the user, requiring

only key values of parametric input and a “run

button”. Post-processing of results should be

provided as part of the workflow with elements that

are aesthetically pleasing. Part of the MEDEA

experiment also involved the creation of the team

with the right expertise to make interaction design

and visualization choices to improve the HPC code

user workflow.

Figure 1: MEDEA introductory view. Placing the power in

the hands of the user is the metaphor being invoked. The

user selects from the three options listed.

2 MEDEA DESIGN OBJECTIVES

Prior to the coding of MEDEA, design objectives

were identified which shaped the development of the

application. There was a strong desire to place the

final tool in the hands of the user in such a way that

the disenfranchised (Ito, 2015) who saw nothing but

barriers to HPC code simulation would become

excited and want to explore physical phenomena

using simulation. The user experience had to bypass

both issues with operating system availability (run

on Microsoft Windows) and the hundreds of lines in

the input deck. Simulation execution should entail

simple and clean parameter input and one-touch

simulation execution.

Advancing the ease-of-use (learnability) of the

application was important. Previous efforts to teach

HPC code users have involved days of training.

Training using simplified input decks with variables

defined within the top 25 lines could take 20 minutes

to teach someone how to run the code. The objective

of MEDEA was to determine if the time to learn

how to load a simulation model and enter the

required input could be reduced to minutes, or even

tens of seconds.

Another important element to MEDEA was that

the interface and results should look “cool”.

Spectacle and fun are commonly used in children’s

software to demonstrate style and status, they are

part of the economy of “cool” (Ito, 2009).

Children’s software typically employs “fun” in order

to maintain focus for a sufficient amount of time in

order to solve problems (exploration). Enthusiasm

associated with fun involves sharing and

demonstrating with others. These are inherent

responses we wished to evoke with scientific

simulation visualization. The child may say a view

looks “cool”. To the more mature individual it is

“cool” not only because of aesthetics but because it

provides visualizations that can be used to explain

physical phenomena and why you obtained a certain

level of system performance. An experience is also

“cool” when one can easily learn from it which is

also pleasing. Learning with increased ease is “fun”.

View establishment and simplicity was also a

desired objective. For a given simulation type there

might exist a commonly accepted view of the

results. This type of analysis should be able to

generated easily and should be a natural result from

the simulation. In the case of a new analysis which

might have been published or presented in another

forum, that view should be easily appended to the

views already generated. In either case, the views

should not be cluttered and the user should be

allowed to interact with the resulting analysis in

order to query points, make comparisons, or

simultaneously view multiple variables and how

they relate to one another.

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3 INTERACTION DESIGN

PRINCIPLES

The workflow for MEDEA was selected in order to

foster user activities in the areas of instruction,

manipulation, and exploration (Preece, Sharp, &

Rogers, 2015). The introductory screen for MEDEA

(see Figure 1) allows the user to select from three

options. These options allow the user to 1)

experience views of information vital to simulations,

2) select and run a simulation, or 3) analyze results

from a simulation through pre-defined visualiza-

tions.

Figure 2: MEDEA view option image. The equation of

state surface which relates pressure to density and

temperature is shown. Distinct boundary lines represent

material phase changes incorporated into the material

model. The user can interact with the 3D surface in terms

of orientation as well as querying points on the surface

using the mouse or touch-screen device.

3.1 View Option

High-performance computing models of physical

phenomena require representations of material

properties (equations of state or constitutive

relationships) as a means of specifying physically-

meaningful responses from materials (e.g. density,

phase changes, temperature, pressure). The resulting

quality of a numerical simulation (which can distort

material both geometrically and through multiple

phase changes) is directly related to the accuracy of

the physics description (discretized mathematically)

as well as the accuracy of the material model

representation. The accessibility of material models

to the user community is typically limited to a list of

available material models with terse descriptions of

tabulated numerical bounds. This method of

operating leaves the user in “in the dark” with

respect to the actual details and assembly of the

material model.

MEDEA’s view option allows the user to

directly access and visualize a material model. The

simple act of viewing the material model itself with

ease is a major leap forward for the HPC

community. The experience is expanded by allowing

the user to interact with and explore the material

model using either mouse- or touch-based

manipulation. Details of the tabulated numerical

values can be easily accessed by selecting points on

the three-dimensional surface (see Figure 2).

Examination of the material model surface

shows areas with both smooth and discontinuous

transitions. For this particular example these

transitions are a result of phase changes of the

material. This view immediately fosters a learning

experience including which phase transitions have

been captured, their location, and potential regions

where the table is valid (extrapolation off of the

table is often allowed but not necessarily physically

meaningful). The view section was also planned to

be used to present two-dimensional performance

data generated by an individual or a community

which can be used for informational purposes, or to

be used in comparison with numerical results.

Figure 3: View of MEDEA’s simulate options. Each XML

file has a corresponding PNG file which provides a

summary of the purpose of the simulation.

3.2 Simulate Option

For some user communities, the simple steps

required to access, read, and edit a HPC code input

deck are so unfamiliar that they form a barrier to

utilization. Attempts to modify already existing

input decks so that the user only has to vary

parameter values at the top few lines of the input

deck have equally failed to overcome the distasteful

workflow of editing, exiting, and then invoking

other commands (typically on a Linux command

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line) to run the code. It was concluded that a simple

set of interactive parameters with no view of the

input deck was desired to overcome the perceived

barrier.

The simulate option begins by providing a user

with a list of available simulation types to run. Each

option represents an input deck which a super-user

has created for the larger community. In conjunction

with the HPC code input deck is a MEDEA XML

file which specifies which variables require input

values (as well as their default values) and the

correct execution command for the HPC code. Users

can identify which simulation template they desire to

run via PNG file images with graphical and text

information detailing the purpose of the simulation

(see Figure 3). Once a template is selected variable

groupings are displayed (with default values

inserted) which can then be altered using the

keyboard or a touchscreen editor (see Figure 4).

Execution of the template is accomplished by the

user selecting the “simulate” bar.

Figure 4: Example of MEDEA’s simulation input option.

The variables and units for this view are established via

keywords in the XML file. A single or multiple pages of

variable grouping can be established. Once completed the

user selects the “simulate” bar to execute the simulation.

3.3 Analyze Option

Visualization of simulation output can occur

immediately after a simulation has been initiated by

the user, or if a user selects a previously completed

simulation. The visualization is created via output

commands listed in the same MEDEA XML file

which contained information as to which variables

should be input and sent to the HPC simulation.

Prescribed visualizations were chosen to be

displayed immediately after the simulation is

executed. MEDEA currently supports 2D & 3D

plotting of X-Y and surface data.

Visualization is an inherent part of the MEDEA

workflow. A novice can begin to study the results of

a simulation as well as obtain views which have

been generated by a super-user (an individual with

greater experience associated with the simulation).

The prescribed views highlight variables of interest

as well as causal relationships between the variables

thus providing a learning experience via

visualization. Experimental results can also be read

into the visualization in order to perform validation

comparisons (see Figure 5).

Figure 5: Visualization of a simulation as prescribed by

output commands in the MEDEA XML file. Experimental

data (circles) has been added to the image and can be

shifted horizontally in time using the mouse or touch-

screen.

Using the flexibility in the XML file, more

advanced users can then create new visualizations

based on the simulation output. Once created, these

new images can be appended to the previous view

descriptions stored in the XML file. Users have

access to both multiple plots per view as well as

multiple views per analysis. Views can be accessed

by clicking or touching the arrows at the bottom of

the screen.

Highly sophisticated views allowing the user to

perform detailed analysis of the simulation

simultaneously with the material view are also

possible (see Figure 6). On the left of the image is

the material phase view surface. Added to the phase

view is the trajectory of the simulation along the

surface (white dotted line). The nearly vertical red

line indicates the corresponding time between the

surface view and the X-Y plots on the right-hand

side. The right-hand side contains a summary view

of more detailed views which can be accessed using

the horizontal arrows. Each view can be time-

correlated with the surface image by touching any of

the summary plots, thereby moving the time-slider

(vertical bar). The size of the right-hand image can

also be expanded by grabbing the right-hand view

and dragging to the left. With simultaneous views of

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Figure 6: Example of highly sophisticated MEDEA analysis comparing the material model (left) with the simulation

trajectory (white line) with multiple time-based performance summaries (right).

material properties, trajectory on the material model

surface, and correlation to time using other output

seen in the right-hand window, the user can begin to

identify how material property variations impact the

global quantities of the simulation. This type of

detailed analysis is readily available to the user and

can be setup by the super-user in the XML file with

relative ease.

4 PORTABILITY &

INTERACTIVITY

MEDEA is an interface to HPC codes which should

provide the already existing simulation community

the opportunity to more effectively run simulations

and analyze their output. From a computing platform

standpoint this can occur using a Windows desktop

or even laptop computer. However, MEDEA was

also designed with increased portability in mind so

that it could also be deployed on a tablet device such

as the Microsoft Surface Pro.

Two portability scenarios were envisioned when

creating MEDEA. First, for a laboratory technologist

or experimentalist to run a simulation of their

experiment immediately prior to execution in order

to prepare for waveform magnitude and timing.

Second, the ability for a user to run a simulation

during a conference or meeting setting in order to

immediately assess performance based an assertion

made by the presenter.

This type of portability for HPC codes and the

ability to have accelerated cycles of learning is

viewed as a future path forward for high-

performance computational simulation. MEDEA

attempts to encapsulate both the best-practices setup

for simulations as well as corresponding

visualizations. This paradigm helps the novice user

obtain solution quickly and serves as a repository for

institutional knowledge on performance evaluation

and analysis. MEDEA was designed to assist both

the computational community as well as members of

the experimental community who want to perform a

quick analysis with minimal additional overhead.

5 CONCLUSIONS

The intent of the MEDEA experiment was to

radically change the workflow for a HPC code user.

Interaction design principles were incorporated with

information visualization techniques in order to

establish a seamless workflow akin to experiences

found with smartphone applications. For HPC codes

which are input deck driven, the MEDEA interface

can be used to run those applications with little

additional overhead. MEDEA’s use of an XML file

to handle input and output from the HPC code

provide a simple interface which generates a

seamless workflow for the user. This seamless and

aesthetically pleasing workflow is a result of

multidisciplinary collaboration between artists,

programmers, and scientists. Novice users can now

The MEDEA Experiment - Can You Accelerate Simulation-based Learning by Combining Information Visualization and Interaction Design

Principles?

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be introduced to HPC code simulations using the

MEDEA interface and can learn in 10’s of seconds

what would previously have taken hours to learn.

Since visualization is integral to the MEDEA

workflow the user’s time-to-result has been reduced

to minutes, thereby allowing the user to sample more

input conditions and thereby obtain accelerated

learning on parametric sensitivity.

ACKNOWLEDGEMENTS

The authors would like to thank Maddie Minnis

(Ideum) for the creation of the flaming-hand

animation.

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Jones, C., 2014. The Technical and Social History of

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Preece, J., Sharp, H., and Rogers, Y., 2015. Interaction

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West Sussex, 4

edition.

Smith, A., 2015, U.S. Smartphone Use in 2015, Pew

Research Center (www.pewresearch.org).

Poushter, J., 2016, Smartphone Ownership and Internet

Usage Continues to Climb in Emerging Economies,

Pew Research Center (www.pewglobal.org).

Ito, M., 2009. Engineering Play: A Cultural History of

Children’s Software, The MIT Press. Cambridge, 1

edition.

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