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Java implementation of the Ziggurat algorithm for generating Gaussian distributed pseudorandom numbers. The Ziggurat algorithm is significantly faster than the more commonly encountered Polar method, and has some other desirable statistical properties. The ZigguratGaussian class is a Java port of the GNU Scientific Library's C implementation (Voss, 2005) of the Ziggurat method. In porting to Java, we have made several optimizations, the details of which can be found in the source code comments, which highlights any differences between this Java implementation and the C implementation on which it is based. This package also includes an implementation of the Polar Method, included to enable comparing speed advantage of the Ziggurat algorithm.

A scalable, concurrent, in-memory Key Value (KV) map. Oak implements a concurrent Key-Value map that can keep all keys and values off-heap. This enables working with bigger heap sizes than JVM's managed heap. OakMap implements an API similar to the industry standard Java8 ConcurrentNavigableMap API. It provides strong (atomic) semantics for read, write, and read-modify-write, as well as (non-atomic) range query (scan) operations, both forward and backward. OakMap is optimized for big keys and values, in particular, for incremental maintenance of objects (update in-place). It is faster and scales better with additional CPU cores than the popular Java ConcurrentNavigableMap ConcurrentSkipListMap

This module provides algorithms to compare sets, that is, order-invariant lists. These algorithms are implementations of the AlignmentAlgorithm interface defined in the algorithms module. In particular, this module contains the StrictSetAlignmentScoreAlgorithm for computing the cost of the optimal unordered alignment of two sets, the StrictSetAlignmentFullAlgorithm which provides the Alignment itself as well, and the GreedySetAlignmentScoreAlgorithm as well as the GreedySetAlignmentFullAlgorithm for computing a potentially sub-optimal but faster alignment of two sets. The optimal alignments rely on the HungarianAlgorithm for solving the assignment problem in bipartite graphs. Here, we rely on the implementation provided by Kevin L. Stern which is provided within this distribution.