TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods

Brent Edmunds, Zhimen Peng, and Wotao Yin

Working draft

Overview

TMAC is a toolbox written in C++11 that implements algorithms based on a set of modern methods for large-scale optimization. It covers a variety of optimization problems, which can be both smooth and nonsmooth, convex and nonconvex, as well as constrained and unconstrained.

The algorithms implemented in TMAC, such as the coordinate update method and operator splitting method, are scalable as they decompose a problem into simple subproblems. These algorithms can run in a multi-threaded fashion, either synchronously or asynchronously, to take advantages of all the cores available.

TMAC is separated into several layers, and this architecture mimics how a scientist writes down an optimization algorithm. Therefore, it is easy for one to obtain a new algorithm by making simple modifications such as adding a new operator and adding a new splitting, while maintaining the multicore parallelism and other features.

Citation

B. Edmunds, Z. Peng, and W. Yin, TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods, UCLA CAM Report 16-38, 2016.


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