Parallel Haskell Tutorial: The Par Monad
Parallel programming will become largely transparent at some point but not today. 😉
Walk through parallel processing of Sudoku and k-means, as well as measuring performance and debugging. Code is available.
I think the debugging aspects of this tutorial stand out the most for me. Understanding a performance issue as opposed to throwing resources at it seems like the better approach to me.
I know that a lot of time has been spent by the vendors of topic maps software profiling their code, but I wonder if anyone has profiled a topic map?
That is we make choices in terms of topic map construction, some of which may result in more or less processing demands, to reach the same ends.
As topic maps grow in size, the “how” a topic map is written may be as important as the “why” certain subjects were represented and merged.
Have you profiled the construction of your topic maps? Comments appreciated.