X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/Krylov_multi.git/blobdiff_plain/39bde1d3c3ce7554c25ced5618cc5b803629a30b..88b2678edbe687f2db9e03ef72d2f7aa0bb5e65c:/review.txt

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@@ -28,10 +28,27 @@ COMMENTS FOR THE AUTHOR:
 *                 Reviewer #2                      *
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 Reviewer #2: This work focus on an better algorithm that solves very large sparse linear systems. The presentation of this paper is clear and within the scope of the journal. However, the paper can be improved in the following ways:
-1. It is better to clearly state the major contributions of this paper in the introduction.
-2. Given that the focus of the paper is to provide a better solution on a well known problem with several well studied approaches. It is essential for the author to provide extensive comparison studies with those approaches. In Section 4 the paper provides some experiments with very limited scope (solving one simple problem and comparing with one well known problems). This seems not enough. Another way is to provide a qualitative comparison against other proposed approaches and explain why the proposed approach is better. But this is also not found.
-3. It is better if the paper can provide a quantitative study on the speed-up achieved by the proposed algorithm so that the reader can get insights on how much is the performance improvement in theory.
-4. In Section 3. it is better if the paper can explain the intuition of multi-splitting. Currently it is more like "Here is what I did" presentation but "why do we do this" is left for the reader to guess.
+,----
+|1. It is better to clearly state the major contributions of this paper in the introduction.
+`---
+In this work we develop a new parallel two-stage algorithm for large-scale clusters. Our objective is to mix between Krylov based iterative methods and the multisplitting method to improve the scalability. In fact Krylov subspace methods are well-known for their good convergence compared to others iterative methods. So our main contribution is to use the multisplitting method which splits the problem to solve into different sub-problems in order to reduce the communications and to implement both inner and outer iterations as Krylov subspace iterations improving the convergence of the multisplitting method.
+	
+
+
+,----
+|2. Given that the focus of the paper is to provide a better solution on a well known problem with several well studied approaches. It is essential for the 
+|author to provide extensive comparison studies with those approaches. In Section 4 the paper provides some experiments with very limited scope (solving 
+|one simple problem and comparing with one well known problems). This seems not enough. Another way is to provide a qualitative comparison against other 
+|proposed approaches and explain why the proposed approach is better. But this is also not found.
+`----
+
+,----
+|3. It is better if the paper can provide a quantitative study on the speed-up achieved by the proposed algorithm so that the reader can get insights on how |much is the performance improvement in theory.
+`----
+
+,----
+|4. In Section 3. it is better if the paper can explain the intuition of multi-splitting. Currently it is more like "Here is what I did" presentation but |"why do we do this" is left for the reader to guess.
+`----