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Systems research is easy to criticize, but much harder to do right. For starters, systems research deals with the real world. The real world is messy. How woul
by bbb 17y ago
Systems research is easy to criticize, but much harder to do right.
For starters, systems research deals with the real world. The real world is messy. How would you comprehensively represent every interesting workload in an analytical model? How would you derive it from real world applications? It is impossible in the general case (halting problem), and really, really hard to do even in specialized cases. If you think otherwise, the field of worst-case execution time analysis awaits your contribution eagerly (try modeling L1 and L2 instruction and data cache interactions in a multicore CPU).
Thus, in many cases evaluating different interesting workloads empirically is unavoidable. In such cases, 100 pages of setup, methodology, and analysis are a feature, and not necessarily a sign of mediocrity. There is a great danger of overlooking substantial flaws in brief descriptions.
So, yes, mediocrity can lead to inflated sections, but a good PhD committee will not led that slide. In your page cache example, I would absolutely expect to see significant experiments and analysis; I would probably not be convinced by just a few selected benchmarks. Presenting benchmarks well requires many more pages than a succinct proof might.
- coffeemug 17y agoI'm probably biased because I do what might qualify as systems research for a living. It's hard to do right - much harder than a novice might think, but it's no rocket science. A reasonably intelligent person who has the stomach for rigor can be taught to do it well. However, I cannot easily get into computation theory - I tried my hand in it, and I just don't have the mathematical intuition. I could develop it to some degree with a lot of work, but I could never do first rate complexity research - that stuff requires real talent. I suppose it's common for people to slightly look down on what they do because they've experienced the mess first hand - the magic is always more spectacular on the other side of the fence :)
- scott_s 17y agoSaying you don't have a "talent" for something is another way of saying you don't enjoy doing it. If you don't enjoy it, you won't practice it, and if you won't practice it you won't be good at it. I've known CS-theory people - who I know are very bright - say similar things about systems research.
- coffeemug 17y agoActually, I really enjoyed studying complexity theory. It just took far more effort than anything I've ever done before - it's really mind bending, and that's why I loved it. I just know that to get to the real meat, I'd have to work very hard for five years or so to develop the intuition and to get up to speed, and even then I'm not sure if I'd be able to cut it to do real first-rate work (a cop-out, I know). I agree with you that people, especially laymen, tend to overrate talent - it's a good defense strategy that helps people avoid doing difficult things. But I disagree with you that there is no natural talent or inclination towards certain subjects in general. When it comes to hard math, I know people that just pick it much quicker and easier than I do, and it has been the case since I was very young (long story short, for a few years I went to school for gifted children, and some kids were just better than me no matter how hard I worked). I'm also convinced that some fields require more natural talent than others.