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== Matrix Package ==
 The Matrix Package for Map/Reducebased Parallel Matrix Computations will be useful for
LargeScale Numeric Analysis and Data Mining which need the computation system of the Inverse
Matrix (e.g. linear regression, PCA, SVM, ..., etc) and many scientific computations.
+ The Matrix Package for Map/Reducebased Parallel Matrix Computations will be useful for
LargeScale Numeric Analysis and Data Mining which need the computation system of the Inverse
Matrix (e.g. linear regression, PCA, SVM, ..., etc) and many scientific computations (e.g.
physics, linear algebra, computational fluid dynamics, statistics, graphics rendering and
others).
Generally, The current sharedmemory based parallel matrix solution provides a scalable
and high performance matrix operations, but, matrix resources can't be scalable. But, Using
Hbase's 2 dimensional Row and Column(Qualifier) space, we are able to store large sparse
matrix. Also, autopartitioned sparsity substructure will be efficiently managed and serviced
by Hbase. Row or Column operations can be done in linear time and algorithms such as structured
Gaussian elimination or iterative methods run in O(~the number of nonzero elements in the
matrix~ / ~number of mappers (processors/cores)~) time on Hadoop Map/Reduce.
=== Initial Contributors ===
* [:udanax:Edward Yoon] (R&D center, NHN corp.)

 === Applications ===

 It can be support a broad variety of applications in the domain of Physics, Linear Algebra,
 [[BR]]Computational Fluid Dynamics, Statistics, Graphics Rendering and others.

 * Scientific simulation and modeling
 * Matrixvector/matrixmatrix multiply
 * Soving linear systems
 * Information retrieval
 * Sorting
 * Finding eigenvalues and eigenvectors
 * Computer graphics and computational geometry
 * Matrix multiply
 * computing matrix determinate
=== Download ===
