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From "Thomas Jungblut (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HAMA-524) [GSoC 2012] Sparse Matrix-Vector multiplication (SpMV) on Hama
Date Tue, 21 Aug 2012 19:39:38 GMT

    [ https://issues.apache.org/jira/browse/HAMA-524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13438978#comment-13438978

Thomas Jungblut commented on HAMA-524:

Hi Mikalai, since we want to commit this soon, I give you a little feedback.

- In WritableUtil you could define the methods as static (actually you should because this
is a utility class). also if you have a log, don't output to STDOUT, this will vanish in distributed
mode to /dev/null.
- By convention (do we have a common sense here?) I name all the BSP's with the suffix BSP,
e.G. KMeansBSP. Maybe (SpMV-)Executor is not a so good suffix here.
- In SpMVExecutor there is a not needed double cast on line 170, also in the random gen arround
line 204.

Also I see a few performance hits, but I would rather profile it than guessing arround it.
Will take a look at bigger inputs next time and profile with yourkit.

In general, we should try to consider moving it to ml module, so it can share the math stuff
and writables so we can move some stuff out of example utils.

In the end, very clean code, well formatted and documented. Thanks Mikalai, great contribution.
> [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
>         Attachments: broken_pipe_exception.zip, eof_exception.zip, HAMA-524.patch, HAMA_524_v1.patch,
HAMA_524_v2.patch, spmv.png, SpMV_v01.patch
> 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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