Data from: The phylogenetic likelihood library

We introduce the Phylogenetic Likelihood Library (PLL), a highly optimized application programming interface for developing likelihood-based phylogenetic inference and post-analysis software. The PLL implements appropriate data structures and functions that allow users to quickly implement common, error-prone, and labor-intensive tasks, such as likelihood calculations, model parameter as well as branch length optimization, and tree space exploration. The highly optimized and parallelized implementation of the phylogenetic likelihood function and a thorough documentation provide a framework for rapid development of scalable parallel phylogenetic software. By example of two likelihood-based phylogenetic codes we show that the PLL improves the sequential performance of current software by a factor of two to ten while requiring only one month of programming time for integration. We show that, when numerical scaling for preventing floating point underflow is enabled, the double precision likelihood calculations in the PLL are up to 1.9 times faster than those in BEAGLE. On an empirical DNA dataset with 2,000 taxa the AVX version of PLL is 4 times faster than BEAGLE (scaling enabled and required). The PLL is available at http://www.libpll.org under the GNU General Public License (GPL).我们推出了系统发育似然库（Phylogenetic Likelihood Library，PLL），这是一款经过高度优化的应用程序编程接口，专用于开发基于似然的系统发育推断及后分析软件。该库实现了适配的数据结构与函数，可帮助用户快速完成常见、易出错且耗时耗力的任务，例如似然计算、模型参数与分支长度优化，以及树空间探索。其针对系统发育似然函数的高度优化并行化实现，辅以详尽的文档资料，为可扩展并行系统发育软件的快速开发提供了完整框架。我们通过两款基于似然的系统发育分析工具示例证实，PLL可将现有软件的串行性能提升2至10倍，且仅需一个月的编程时长即可完成集成。实验结果表明，当启用防止浮点下溢的数值缩放功能时，PLL的双精度似然计算速度最高可比BEAGLE快1.9倍。针对包含2000个分类单元的实证DNA数据集，在启用且需要数值缩放的场景下，PLL的AVX版本性能是BEAGLE的4倍。PLL可通过http://www.libpll.org获取，遵循GNU通用公共许可证（GPL）发布。