Matrix Toolkits for Java

Matrix data structures, linear solvers, least squares methods, eigenvalue, and singular value decompositions. For larger random dense matrices (above ~ 350 x 350) matrix-matrix multiplication C = A.B is about 50% faster than MTJ.

License

License

Categories

Categories

Java Languages
GroupId

GroupId

com.github.hullbend
ArtifactId

ArtifactId

mt-java
Last Version

Last Version

1.1.0
Release Date

Release Date

Type

Type

jar
Description

Description

Matrix Toolkits for Java
Matrix data structures, linear solvers, least squares methods, eigenvalue, and singular value decompositions. For larger random dense matrices (above ~ 350 x 350) matrix-matrix multiplication C = A.B is about 50% faster than MTJ.
Project URL

Project URL

https://github.com/HullBend/mt-java/
Source Code Management

Source Code Management

https://github.com/HullBend/mt-java

Download mt-java

How to add to project

<!-- https://jarcasting.com/artifacts/com.github.hullbend/mt-java/ -->
<dependency>
    <groupId>com.github.hullbend</groupId>
    <artifactId>mt-java</artifactId>
    <version>1.1.0</version>
</dependency>
// https://jarcasting.com/artifacts/com.github.hullbend/mt-java/
implementation 'com.github.hullbend:mt-java:1.1.0'
// https://jarcasting.com/artifacts/com.github.hullbend/mt-java/
implementation ("com.github.hullbend:mt-java:1.1.0")
'com.github.hullbend:mt-java:jar:1.1.0'
<dependency org="com.github.hullbend" name="mt-java" rev="1.1.0">
  <artifact name="mt-java" type="jar" />
</dependency>
@Grapes(
@Grab(group='com.github.hullbend', module='mt-java', version='1.1.0')
)
libraryDependencies += "com.github.hullbend" % "mt-java" % "1.1.0"
[com.github.hullbend/mt-java "1.1.0"]

Dependencies

test (3)

Group / Artifact Type Version
junit : junit jar 4.12
net.sf.opencsv : opencsv jar 2.3
com.google.guava : guava jar 18.0

Project Modules

There are no modules declared in this project.

mt-java

Uber-jar of the MTJ Heimsund-Halliday Matrix Toolkit for Java: https://github.com/fommil/matrix-toolkits-java

For larger random dense matrices (above ~ 350 x 350) matrix-matrix multiplication C = A.B is about 50% faster than MTJ.

Release 1.1.0 supplements matrix-matrix multiplication with modest multicore capability for larger matrices yielding some performance improvements (a few dozen percent for big matrices) in multiplication-heavy algorithms like SVD.

Maven:

<dependency>
    <groupId>com.github.hullbend</groupId>
    <artifactId>mt-java</artifactId>
    <version>1.1.0</version>
</dependency>

Versions

Version
1.1.0
1.0.8
1.0.7
1.0.6
1.0.5
1.0.4