LSP 120 Technological Literacy

1. LSP 120Technological Literacy Some of the tools and forces driving the evolution of science and technology G. P. Labedz DePaul University Spring 2011

2. Outline Today you will see how every major topic from this course helps you to understand one of the most powerful forces in the world. It affects almost every human alive You could call it a trend

3. First, the work of a masterof the “old school”(flat paper) display of data Edward Tufteis regarded as one ofthe most insightful creators of the graphic display of data alive and working today

4. A Graphing Master: Edward TufteClarifies the Challenger DisasterTo launch or not? The engineers saw this: Visual Explanations: Images and Quantities, Evidence and Narrative. Edward Tufte

5. Tufte charted the SAME dataTo launch or not? Notice the low end “prediction” on the graph (dotted) Visual Explanations: Images and Quantities, Evidence and Narrative. Edward Tufte

6. The “virtuous cycle” The virtuous cycle is one in which the cycle is self-reinforcing The self-reinforcing makes things better and better (hence, “virtuous”) Driving many sciences, and “technology” today there is a virtuous cycle, the one we’ll examine today

7. At the core: Semiconductor “chips” Source: Intel, Inc

8. Where “chips” come from: wafersThey are made from sand Source: Intel, Inc

9. Moore’s “Law” Moore’s “Law” is really an observation made in 1967 Who is Gordon Moore? Co-founder of Intel It says, based on experience at the time, that the number of transistors/area (note, a rate) doubles approximately every 24 months Hmmm. And how would we model that?

10. The number of transistors on heredoubles every 24 monthsbut the wafer costs the same Source: Intel, Inc

11. So the cost of making thisgoes in half every 24 months Source: Intel, Inc

12. Anybody sense A TREND?Moore’s “Law”is a description of a trendbased on experienceand (originally)extended into the FUTURE

13. Note vertical axis Is exponentialincreasing by 10x Each interval

14. The virtuous cycle As the number of transistors/area grows The transistors shrink. The circuits get much cheaper, all electronics get cheaper And when they shrink, they get faster When the transisitor get faster, everything speeds up All the computers and controllers speed up When the computers speed up, more can be computed When more can be computed, sceintific and engineering calculation becomes more sophisticated When science becomes more sophisticated, Science and engineering advance at a more rapid pace.

15. It is possible to:Build computer models allowingCrashing a car in a computer (GM, Ford);building earth-moving equipment;creating an entire cellular system;testing a helicopter;studying wind-turbinesand on and on . . .

16. These computer simulationcreate enormous amounts ofdata output to be studiedBillions and billions of numbers to“graph”It’s incomprehensible to humans

17. Prof. Donna Cox An art professor married her visual skills to the data sets of scientists at the National Center for Supercomputing Applications (NCSA) in the mid-1980s Using newly-created computer graphics from the movie industry Scientific Visualization was born http://www.ncsa.illinois.edu/~cox/

18. Tonado multivariate simulation and visualization. Prof. Bob WilmhelmsonNational Center for Supercomputing Applications http://www.youtube.com/watch?v=EgumU0Ns1YI

19. Some bumps in the road:end of Moore’s Law?Gene Amdahl’s Law Heat on the integrated circuits has killed the speedups! It’s the unexpected end of a trend!! The micoprocessor industry can no longer just Add more transistors and expect everything to go faster So they put multiple “computers” in the computers That’s what “multicore” means

20. Lousy citation from Wikipedia

21. Moore’s “Law” is alivebut it’s companion speedup is not This trend CANNOT be projected forward. It’s over

22. In Biological Science:Human Genome ProjectBenefiting from massive computing speedupsbut benefits are early and small The Human Genome Project originally aimed to map the nucleotides contained in a human haploid reference genome (more than three billion). But, except for identical twins, no two humans are alike! Bibliographic details for "Human Genome Project" Page name: Human Genome Project Author: Wikipedia contributors Publisher: Wikipedia, The Free Encyclopedia. Date of last revision: 23 May 2011 01:17 UTC Date retrieved: 28 May 2011 13:42 UTC Permanent link: http://en.wikipedia.org/w/index.php?title=Human_Genome_Project&oldid=430439003 Primary contributors: Revision history statistics Page Version ID: 430439003

23. If they can put a man on the moonwhy can’t they cure the cold? It’s becauseTHEYare not the same peoplewith the same tools

24. The people who put humans on the moon had the benefit, even in the 1960s, of highly accurate mathematical models of motion in space, and the ability to use computing to predict what would happen in all the important aspects of building and launching the equipment Biologists don’t have that yet.

25. From this little talkyou have learned . . . That the shrinkage, and speedup of semiconductor-based circuits is the driver of a “virtuous cycle” It enables radical cost reduction and performance increase In computing and control of many things

26. . . . from this little talkyou have learned . . . Which in turn enables radical increase in scientific computing; In turn creating huge data sets; But also creating the ability of people to comprehend the huge data sets using Complex computer-driven animation of data

27. . . . from this little talkyou have learned . . . And in turn enhancing knowledge At an incredible rate in some fields of thought.

28. . . . from this little talkyou have learned . . . An expression of the underlying force behind these advancements Is called “Moore’s Law” From which predictions up to now have held true But which may be in a disruption.

29. From this little talkyou have also learned . . . That “Moore’s Law” is an exponential process, That the rate of increase of transistors on a semiconductor die is what matters, And that visual representation of data, modern graphing, is moving knowledge forward. And that this trend, which has so enhanced and disrupted the world, may be over

30. SO In other words . . . . . . . This is the math class you’ve all been waiting for!

31. The only three thingsyou need to know aboutPowerPoint Or, Bonus material on the DVD About how I made this presentation And how you can quickly make yours.