About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast.

Changes from 1.0:

• Added singular value decomposition
• Fixed bug with returning complex values
• Many other minor improvements

About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use. Matrix decompositions are provided through optional integration with LAPACK and ATLAS.

• Added detection of MKL & ACML (high speed LAPACK) during installation
• Added MSVC project files for compiling examples
• Added conversions to/from std::vector
• Added convolution operation
• Added toeplitz()
• Added matrix initialisation via the << operator
• More flexible reshape()
• More consistent success indication by decomposition functions
• Faster compilation by omitting Boost where possible
• Various speedups and bug fixes

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Initial Announcement on mloss.org.