Bioinformatics | 2021
HOPS: high-performance library for (non-)uniform sampling of convex-constrained models
Abstract
SUMMARY\nThe C\u2009++ library HOPS (Highly-Optimized Polytope Sampling) provides implementations of efficient and scalable algorithms for sampling convex-constrained models that are equipped with arbitrary target functions. For uniform sampling, substantial performance gains were achieved compared to the state-of-the-art. The ease of integration and utility of non-uniform sampling is showcased in a Bayesian inference setting, demonstrating how HOPS interoperates with third-party software.\n\n\nAVAILABILITY AND IMPLEMENTATION\nSource code is available at https://github.com/modsim/hops/, tested on Linux and MS Windows, includes unit tests, detailed documentation, example applications, and a Dockerfile.\n\n\nSUPPLEMENTARY INFORMATION\nSupplementary data are available at Bioinformatics online.