Evaluating polynomials


Evaluating polynomials is not a thing I do very often. When I do, it’s for interpolation and splines; and traditionally those are done with relatively low degree polynomials—cubic at most. There are a few rather simple tricks you can use to evaluate them efficiently, and we’ll have a look at them.

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Suggested Reading: Patterns for Parallel Programming


Timothy G. Mattson, Beverly A. Sanders, Berna L. Massingill — Patterns for Parallel Programming — Addison-Wesley, 2005, 356 pp. ISBN 0-321-22811-1

(Buy at Amazon.com)

If the Gang of Four changed the way we discuss about software design by introducing a catalogue of basic software patterns, this books vies to extend it to parallel patterns. But let us be clear, it’s not a book about parallel algorithms; no, it discusses parallelism in very general terms and present the few prototypical application types and how they can be efficiently broken down by data structure, command flow, and synchronisation, while remaining rather high level.

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Throwing in More Hardware?


In a recent blog entry, Jeff Atwood makes the case that “hardware is Cheap, Programmers are Expensive”, basically arguing that in a lot of cases, it’s cost-efficient to add cheap, faster, hardware to a performance problem rather than investing time to actually enhance the code at the algorithmic and implementation level.

I do, however, disagree with him on many points.

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