There has been quite a flutter recently in the iterative world about an algorithm that speeds up the classical Jacobi method by as much as 200 times using a scheduled relaxation method where a combination of over and under relaxation is employed. The results as shown in this paper are remarkable and are indicative of a resuscitation of Jacobi method as a method for practical purposes.

However, when I implemented it I cannot get it to work. I was wondering if anybody else in this community has tried implementing this method and if so was the attempt successful. It would be interesting to hear if there is anything special that needs to be taken care of when implementing this algorithm.

  • $\begingroup$ Are you asking about how your program should be debugged, or is this a question about the method in general? $\endgroup$ – Kirill Dec 16 '14 at 19:47
  • $\begingroup$ I don't see an actual question here. Just a vague wondering about the method in general. I doubt that can lead to a useful answer. $\endgroup$ – Doug Lipinski Dec 16 '14 at 19:57
  • $\begingroup$ Keep in mind that discrepancies between a paper's purported performance and your own performance can be attributed to a myriad of causes, including coding styles, data structures, vectorization, compilers, etc... In general it is difficult to isolate a cause without a lot of additional information (both from you and from the author's results) which may not be easily attainable. $\endgroup$ – Paul Dec 16 '14 at 20:30
  • $\begingroup$ I've closed this question because its scope is far too open-ended to fit the Q&A format of the stack exchange. On the other hand, the algorithm you linked to sounds very interesting and you may want to consider corresponding with the authors of the paper about your implementation issues. $\endgroup$ – Paul Dec 16 '14 at 20:40
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    $\begingroup$ @Trinath I would recommend that you fix your own implementation first. It is overwhelmingly likely that it is your program that is incorrect, rather than the paper. $\endgroup$ – Kirill Dec 17 '14 at 7:00