1. SUPERCOMPUTING CHALLENGE KICKOFF 2015 A Model for Computational Science Investigations Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data1

2. Computational Science is the use of mathematics and computers to model “real world” problems in science, and conduct simulation experiments. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data2 Computational Science?

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 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data3 Computational Science

4. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data4 Real World Problem Working Model Working Model Mathematical/ Behavioral Model Mathematical/ Behavioral Model Computational Model Results/ Conclusions Results/ Conclusions Simplify Represent TranslateSimulate Interpret Computational Science Process

5. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data5 Role of Modeling Real World Problem Working Model Working Model Mathematical/ Behavioral Model Mathematical/ Behavioral Model Computational Model Results/ Conclusions 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

6. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data6 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)

7. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data7 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

8. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data8 Research & Simplify 2. Develop an idea for a Working Model 3. Select Mathematical or Agent-based Model Represent & 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 Produce Data 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: Translate Into Code

9. Oct 2015 © consult@supercomputing challenge.org Supercomputing Around Us: Sensors and Data9