This is the LIBASKIT set of scalable machine learning and data analysis tools.  Currently we provide codes for kernel sums, nearest-neighbors, kmeans clustering, kernel regression, and multiclass kernel logistic regression. All codes use OpenMP and MPI for shared memory and distributed memory parallelism.

  • ASKIT :  (Approximate Skeletonization Kernel Independent Treecode) Code for fast approximate kernel summation. It finds applications in kernel machines. It supports treecode and fast-multipole versions.
  • RKDT : (Randomized KD-trees)  Set of core algorithms for nearest-neighbor searches
  • GSKS :  (General Stride Kernel summation) X86 optimized libraries for direct, O(N^2), kernel summation.
  • GSKNN :  (General Stride K-nearest-neighbors)  X86 optimized libraries for direct, O(N^2) nearest-neighbor searches.
  • PNYSTR : (Parallel Nystrom method) Code for kernel summation using the Nystrom method.

All software is available under the the GNU General Public License
GPL license