Software:Parallel Colt: Difference between revisions
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DoubleMatrix2D result = alg.mult(matA,matB); | DoubleMatrix2D result = alg.mult(matA,matB); | ||
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==See also== | |||
* [[Software:List of free and open-source software packages#Mathematical libraries|List of open-source mathematical libraries]] | |||
== References == | == References == | ||
<references> | |||
<ref name=ProjectPage>{{cite web |url=https://sites.google.com/site/piotrwendykier/software/parallelcolt Official site |title=Parallel Colt Project Page |work=Parallel Colt|accessdate=June 15, 2013}}</ref> | <ref name=ProjectPage>{{cite web |url=https://sites.google.com/site/piotrwendykier/software/parallelcolt Official site |title=Parallel Colt Project Page |work=Parallel Colt|accessdate=June 15, 2013}}</ref> | ||
</references> | |||
[[Category:Java (programming language) libraries]] | [[Category:Java (programming language) libraries]] | ||
{{Sourceattribution|Parallel Colt}} | {{Sourceattribution|Parallel Colt}} | ||
Latest revision as of 06:54, 12 April 2026
| Original author(s) | Piotr Wendykier |
|---|---|
| Stable release | 0.9.4
/ March 21, 2010 |
| Operating system | Cross-platform |
| Type | Library |
| License | Various |
| Website | sites |
Parallel Colt is a set of multithreaded version of Colt. It is a collection of open-source libraries for High Performance Scientific and Technical Computing written in Java. It contains all the original capabilities of Colt and adds several new ones, with a focus on multi-threaded algorithms.
Capabilities
Parallel Colt has all the capabilities of the original Colt library, with the following additions.[1]
- Multithreading
- Specialized Matrix data structures
- JPlasma
- Java port of PLASMA (Parallel Linear Algebra for Scalable Multi-core Architectures).
- CSparseJ
- CSparseJ is a Java port of CSparse (a Concise Sparse matrix package).
- Netlib-java
- Netlib is a collection of mission-critical software components for linear algebra systems (i.e. working with vectors or matrices).
- Solvers and preconditioners
- Mostly adapted from Matrix Toolkit Java
- Nonlinear Optimization
- Java translations of the 1-dimensional minimization routine from the MINPACK
- Matrix reader/writer
- All classes that use floating-point arithmetic are implemented in single and double precision.
- Parallel quicksort algorithm
Usage example
Example of singular value decomposition (SVD):
DenseDoubleAlgebra alg = new DenseDoubleAlgebra();
DenseDoubleSingularValueDecomposition s = alg.svd(matA);
DoubleMatrix2D U = s.getU();
DoubleMatrix2D S = s.getS();
DoubleMatrix2D V = s.getV();
Example of matrix multiplication:
DenseDoubleAlgebra alg = new DenseDoubleAlgebra();
DoubleMatrix2D result = alg.mult(matA,matB);
See also
References
- ↑ Official site "Parallel Colt Project Page". Parallel Colt. https://sites.google.com/site/piotrwendykier/software/parallelcolt Official site. Retrieved June 15, 2013.
