Reviewer #5: In this paper, the authors have implemented a Krylov multisplitting method to solve sparse linear systems on large-scale computing platforms. The technical approach and analysis of this paper is reasonable and the paper is clear, logical, and understandable.
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However, the paper does not take into considerate account relevant current and past research on the topic.
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+%Doing many experiments with many cores is not easy and requires to access to a supercomputer with several hours for developing a code and then improving it.-
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It is unclear from the paper whether the analysis includes the a comparison of their new method to the method of reference [9]. Does the new method do better than that one or is it similar or worse.
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+The experiments in Section 4 show a comparison between the performances of our Krylov multisplitting algorithm and those of GMRES method. As said previously, we consider that GMRES is one of the most used method to solve large-scale sparse linear systems. The method of reference [9] is semi-parallel. In fact the task of the minimization is decoupled from the resolution of the different splittings, such as we could fall on a situation where the minimization cannot be performed until all splittings are solved. In addition, the minimization task of reference [9] is performed in sequential.
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The paper should be rewritten to clearly explain what is being compared. It seems as if the method in [9] is not included in the comparison.
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Was the method of reference [9] implemented by the authors of [9]? How did they do against GMRES?
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+Authors of [9] have not implemented the method of reference [9]. They have mainly focused on the convergence analysis of various forms of the algorithm [9] and presented results of numerical examples on a sequential computer.
