TMAC：现代异步并行、协调、分裂和随机方法的集合
TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods
摘要：
TMAC是一个用C++11编写的工具箱，它实现了基于一组现代方法的大规模优化算法。它涵盖了各种各样的最优化问题，这些问题可以是光滑的和非光滑的，凸的和非凸的，以及有约束的和无约束的。在TMAC中实现的算法，如坐标更新方法和算子分裂方法，是可扩展的，因为它们将问题分解为简单的子问题。这些算法可以以多线程的方式同步或异步运行，以利用所有可用的内核。TMAC架构模仿科学家如何写下优化算法。因此，人们很容易通过简单的修改（例如添加新运算符和添加新分裂）来获得新算法，同时保持多核并行性和其他功能。该软件包可在https://github.com/uclaopt/TMAC上获得。
英文摘要：
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 up- date 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 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. The package is available at https://github.com/uclaopt/TMAC.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
