[prev in list] [next in list] [prev in thread] [next in thread] 

List:       incubator-cvs
Subject:    [Incubator Wiki] Trivial Update of "HamaProposal" by udanax
From:       Apache Wiki <wikidiffs () apache ! org>
Date:       2008-04-21 3:59:41
Message-ID: 20080421035941.843.80361 () eos ! apache ! org
[Download RAW message or body]

Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Incubator Wiki" for change \
notification.

The following page has been changed by udanax:
http://wiki.apache.org/incubator/HamaProposal

------------------------------------------------------------------------------
  Hama will develop a parallel matrix computational package, which provides an \
library of matrix operations for the large-scale processing development environment \
and Map/Reduce framework for the large-scale Numerical Analysis and Data Mining, \
which need the intensive computation power of matrix inversion, e.g. linear \
regression, PCA, SVM and etc. It will be also useful for many scientific \
applications, e.g. physics computations, linear algebra, computational fluid \
dynamics, statistics, graphic rendering and many more.   
  == Background ==
- Currently, several shared-memory based parallel matrix solutions can provide a \
scalable and high performance matrix operations, but matrix resources can not be \
scalable in the term of complexity. And, Hadoop HDFS Files and Map/Reduce can only \
used by 1d blocked algorithm.   + Currently, several shared-memory based parallel \
matrix solutions can provide a scalable and high performance matrix operations, but \
matrix resources can not be scalable in the term of complexity. And, Hadoop HDFS \
Files and Map/Reduce can only used by 1D blocked algorithm.    == Rationale ==
  
  Hama approach proposes the use of 3-dimensional Row and Column (Qualifier), Time \
space and multi-dimensional Columnfamilies of [http://hadoop.apache.org/hbase Hbase], \
which is able to store large sparse and various type of matrices (e.g. Triangular \
Matrix, 3D Matrix, and etc.) and utilize the 2D blocked algorithm. its \
auto-partitioned sparsity sub-structure will be efficiently managed and serviced by \
Hbase. Row and Column operations can be done in linear-time, where several \
algorithms, such as ''structured Gaussian elimination'' or ''iterative methods'', run \
in O(the number of non-zero elements in the matrix / number of mappers) time on \
Hadoop Map/Reduce.

---------------------------------------------------------------------
To unsubscribe, e-mail: cvs-unsubscribe@incubator.apache.org
For additional commands, e-mail: cvs-help@incubator.apache.org


[prev in list] [next in list] [prev in thread] [next in thread]