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Supercomputing Around Us: Sensors and Data 1
SUPERCOMPUTING CHALLENGEKICKOFF 2015
A Model for Computational Science Investigations
Oct 2015 © [email protected]
Supercomputing Around Us: Sensors and Data 2
Computational Science is the use of mathematics and computers to model “real world” problems in science, and conduct simulation experiments.
Oct 2015 © [email protected]
Computational Science?
Supercomputing Around Us: Sensors and Data 3
• Computational Science (CS) complements, but does not replace, field experimentation in scientific research. Each approach is appropriate in certain situations.
• CS is ideally suited to exploration of problems which are too expensive, too dangerous, too difficult to control, too fast, too slow, too… etc. for extensive experimentation in the field.
• CS allows us to perform large numbers of experiments, using alternative scenarios with different inputs. This can be used for “what if” analyses, as well as output-driven solutions to complex problems.
Oct 2015 © [email protected]
Computational Science
Supercomputing Around Us: Sensors and Data 4Oct 2015 © [email protected]
Real World Problem
WorkingModel
Mathematical/
BehavioralModel
Computational
Model
Results/Conclusions
Simplify
Represent
TranslateSimulate
Interpret
Computational Science Process
Supercomputing Around Us: Sensors and Data 5Oct 2015 © [email protected]
Role of Modeling
Real World Problem
WorkingModel
Mathematical/
BehavioralModel
Computational
Model
Results/Conclusions
Simplify the “real world” into an
abstracted form.
Represent the model in formal
mathematical and/or algorithmic terms.
Translate the equations and algorithms into computer code.
Simulate
Interpret
Supercomputing Around Us: Sensors and Data 6Oct 2015 © [email protected]
Implementation Approach:Modeling Orientation
Mathematical formulas and/or logical rules describing the global
behavior of the “world” as a whole.
Logical rules and/or mathematical formulas describing the local
behavior of the different kinds of individual objects in the “world”
How we describe the “world” of our chosen problem …
Procedural Programming (e.g. Fortran, C, BASIC)
Object-Oriented Programming (e.g. Java, C++, VisualBasic)
Agent-based Programming (e.g. StarLogo)
Supercomputing Around Us: Sensors and Data 7Oct 2015 © [email protected]
Implementation Approach:Technical Application
Device Control
Numerical Computing
Monte Carlo Simulation
Continuous Simulation
Discrete Event Simulation
Cellular Automata
Agent-based Simulation
Fortran
C
C++
Java
StarLogo
Supercomputing Around Us: Sensors and Data 8Oct 2015 © [email protected]
Research&Simplify
2. Develop an idea for a Working Model
3. Select Mathematical or Agent-based ModelRepresent
&Explain
* If no data could be collected from a model like this, go back to step #1.
Setup the Experiments
4. Design & Implement the Computational Model.
5. Run the Computational Model
ProduceData
6. Analyze the Data
* If the data doesn’t make sense, go back to step #4.
* If you cannot talk about your model, do not move on to the next step.
Does the data describe the real world phenomena
Project Title: __________________________Team #: ____ School:___________________Team Members: _______________________Scientist: _____________________________
1. Select a Real World Problem:
TranslateIntoCode
Supercomputing Around Us: Sensors and Data 9Oct 2015 © [email protected]
