Download e-book for kindle: A guide to experimental algorithmics by Catherine C. McGeoch
By Catherine C. McGeoch
"Computational experiments on algorithms can complement theoretical research by means of displaying what algorithms, implementations, and speed-up tools paintings most sensible for particular machines or difficulties. This e-book publications the reader in the course of the nuts and bolts of the key experimental questions: What may still I degree? What inputs may still I try? How do I research the information? Answering those questions wishes principles from set of rules design and research, working structures and reminiscence hierarchies, and data and knowledge research. The wide-ranging dialogue contains a instructional on process clocks and CPU timers, a survey of thoughts for tuning algorithms and knowledge buildings, a cookbook of equipment for producing random combinatorial inputs, and an illustration of variance aid recommendations. quite a few case experiences and examples convey the best way to observe those thoughts. all of the invaluable innovations in computing device structure and knowledge research are lined in order that the publication can be utilized by way of somebody who has taken a path or in facts constructions and algorithms. A spouse site, AlgLab (www.cs.amherst. edu/ccm/alglab) includes downloadable records, courses, and instruments to be used in projects"-- Read more...
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Additional info for A guide to experimental algorithmics
From this graph we can observe the following: • Factor F1 has a positive main effect because every line has positive slope. • Factor F2 has a positive main effect since both solid lines are above both dotted lines. • The main effect of F3 is also positive, since in each pair the line marked (+) is above the line marked (−). • Factor F2 has the greatest main effect, since the distance between solid and dotted lines is greater than the distances that represent the effects of F1 (left vs. right points) and F3 (as labeled).
All three implementations gave different behaviours . .. Naturally our conﬁdence went out the window. ” We now have two modes of running our experiments, one with the paranoid ﬂag on. In this mode, we put efﬁciency aside and make sure that the algorithms and their heuristics do exactly the same thing, as far as we can tell. • Pseudorandom number generators can produce patterns of nonrandomness that skew results. I once spent a week pursuing the theoretical explanation for an interesting property of the move-to-front algorithm described in Chapter 6: the interesting property disappeared when the random number generator was swapped out in a validation test.
We now have two modes of running our experiments, one with the paranoid ﬂag on. In this mode, we put efﬁciency aside and make sure that the algorithms and their heuristics do exactly the same thing, as far as we can tell. • Pseudorandom number generators can produce patterns of nonrandomness that skew results. I once spent a week pursuing the theoretical explanation for an interesting property of the move-to-front algorithm described in Chapter 6: the interesting property disappeared when the random number generator was swapped out in a validation test.
A guide to experimental algorithmics by Catherine C. McGeoch