Fast native-speed matrix and linear algebra in Clojure
On the GPU: more than 1000x faster for large matrices than the fastest optimized Java libraries!
Works on AMD, Nvidia, and Intel hardware!
On the CPU: 10x - 60x faster than optimized Java libraries.Get Started! » Check the benchmarks » Learn to use it. » Join the community »
Seamless support for GPU computing. Many times faster than any code running on the CPU.
Considerably faster than JBlas, and faster than pure Java core.matrix vectorz even for small matrices: see the benchmarks and comparisons.
Built with Clojure in mind, and implemented in Clojure.
Sane interface and functions that fit into functional style while still respecting the reality of number crunching.
Comes with fast primitive versions of map and reduce.
Pluggable engine implementations - even a pure Java engine could be plugged in for the cases when speed is not the priority.
Does not try to poorly reinvent the wheel. Respects decades of BLAS and LAPACK standardization. Does the number crunching part with native BLAS and/or GPU, but provides a tiny Clojure layer for sanity. Win-win :)
Licensed under the Eclipse Public License, same as Clojure.
GPU engine supports AMD, Nvidia, Intel, and Mac OSX!I hang around at Uncomplicate group at Slack's Clojurians