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From "Mikalai Parafeniuk (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HAMA-524) [GSoC 2012] Sparse Matrix-Vector multiplication (SpMV) on Hama
Date Fri, 08 Jun 2012 11:35:23 GMT

    [ https://issues.apache.org/jira/browse/HAMA-524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13291709#comment-13291709

Mikalai Parafeniuk commented on HAMA-524:

Hello everybody. I am glad to say that i finished the most tedious activities
in my university. So from now, implementation of this task is my priority.
I am currently working on creating different matrix and vector formats.

You can checkout current code from my github repository.
Actually changes related to this task were placed in examples.linearalgebra package:

Recently I have created some abstract interfaces and classes for supporting different 
matrix formats. Could anyone make a review and give a feedback? I know that the amount of
code is
not to big, but I think the earlier I'll receive feedback, the earlier I'll correct the code.

In the nearest future i plan to implement formats for dense matrices and vectors and one format
for sparse matrices and vectors.
Also I have a set of questions:
1) Is using of reflection is a good idea to exploit internals of matrix format in time of
Or it could be implemented simpler?
2) I want to use HamaConfiguration class to register some custom converters between some
matrix formats. Could anyone give me a starting point, where I can learn how Hadoop's configuration
> [GSoC 2012] Sparse Matrix-Vector multiplication (SpMV) on Hama
> --------------------------------------------------------------
>                 Key: HAMA-524
>                 URL: https://issues.apache.org/jira/browse/HAMA-524
>             Project: Hama
>          Issue Type: New Feature
>          Components: bsp core, examples, math
>            Reporter: Edward J. Yoon
>            Assignee: Mikalai Parafeniuk
>              Labels: gsoc, gsoc2012, newbie
> Implement Efficient and Fast SpMV algorithm which can be widely used in scientiļ¬c computing,
financial modeling, information retrieval, and others, using Hama Bulk Synchronous Parallel

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