01.02.2013 Aufrufe

Trafo #132 - Fachschaft Elektrotechnik und Informationstechnik - TUM

Trafo #132 - Fachschaft Elektrotechnik und Informationstechnik - TUM

Trafo #132 - Fachschaft Elektrotechnik und Informationstechnik - TUM

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Professoreninterviews<br />

22<br />

Science the main challenge is to <strong>und</strong>erstand the limits<br />

of computation, for example how efficiently you<br />

can solve a certain problem. This is the essential<br />

question of computational complexity. Imagine you<br />

have a given problem and you would like to develop<br />

a very efficient algorithm for this problem. Now it’s<br />

not clear whether you are not intelligent enough to<br />

develop this algorithm or whether it is just not possible<br />

to develop this algorithm. People are now trying<br />

to prove theoretically how fast you can solve certain<br />

problems. But there are still a lot of unanswered<br />

questions, for example, can all problems be solved in<br />

polynomial time? Answers to these questions will also<br />

have a significant impact on Electrical Engineering;<br />

for example when you do your floor planning and<br />

then routing in a chip, the relevant algorithms might<br />

now take two days to run. This is a major problem,<br />

because you will only know two days later if you did<br />

a good job with the floor planning. If we have very<br />

efficient algorithms, a designer’s life would be much<br />

easier and design productivity would be a lot higher.<br />

The same thing is true for many other problems in<br />

Computer Sciences and Electrical Engineering. I’m<br />

<strong>Fachschaft</strong> <strong>Elektrotechnik</strong> <strong>und</strong><br />

<strong>Informationstechnik</strong> e.V.<br />

<strong>Trafo</strong> Ausgabe 132<br />

also very interested in low-power design, to see what<br />

kind of algorithms could be developed in order to<br />

economize energy, depending on the current situation.<br />

Here, one might ask the question: What is the<br />

minimum energy needed for a given computation or<br />

can you at least theoretically perform a computation<br />

with zero energy? I’m very interested in what kind of<br />

progress will be possible in these areas.<br />

What piece of advice would you give the students to<br />

take along in one sentence?<br />

I have been to many different places and I have met<br />

many different students. One advice I should give<br />

to students here is that they should think beyond<br />

Germany. There are students in the US, in Japan, in<br />

China – there are researchers all aro<strong>und</strong> the world. I<br />

think currently we have to be aware of the fact that<br />

research and education are global activities: Even sitting<br />

in Munich you have to compete with someone<br />

sitting in Japan. So I think it is very important not to<br />

restrict your thoughts to just your environment, but<br />

to think beyond your city and your country.

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