BEAGLE 3:Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics

© 2019 The Author(s). BEAGLE is a high-performance likelihood-calculation library for phylogenetic inference. The BEAGLE library defines a simple, but flexible, application programming interface (API), and includes a collection of efficient implementations for calculation under a variety of evolutionary models on different hardware devices. The library has been integrated into recent versions of popular phylogenetics software packages including BEAST and MrBayes and has been widely used across a diverse range of evolutionary studies. Here, we present BEAGLE 3 with new parallel implementations, increased performance for challenging data sets, improved scalability, and better usability. We have added new OpenCL and central processing unit-threaded implementations to the library, allowing the effective utilization of a wider range of modern hardware. Further, we have extended the API and library to support concurrent computation of independent partial likelihood arrays, for increased performance of nucleotide-model analyses with greater flexibility of data partitioning. For better scalability and usability, we have improved how phylogenetic software packages use BEAGLE in multi-GPU (graphics processing unit) and cluster environments, and introduced an automated method to select the fastest device given the data set, evolutionary model, and hardware. For application developers who wish to integrate the library, we also have developed an online tutorial. To evaluate the effect of the improvements, we ran a variety of benchmarks on state-of-the-art hardware. For a partitioned exemplar analysis, we observe run-time performance improvements as high as 5.9-fold over our previous GPU implementation. BEAGLE 3 is free, open-source software licensed under the Lesser GPL and available at https://beagle-dev.github.io

Internal Governance Structures and Earnings Management

This paper investigates the role of a firm's internal governance structure in constraining earnings management. It is hypothesized that the practice of earnings management is systematically related to the strength of internal corporate governance mechanisms, including the board of directors, the audit committee, the internal audit function and the choice of external auditor. Based on a broad cross-sectional sample of 434 listed Australian firms, for the financial year ending in 2000, a majority of non-executive directors on the board and on the audit committee are found to be significantly associated with a lower likelihood of earnings management, as measured by the absolute level of discretionary accruals. The voluntary establishment of an internal audit function and the choice of auditor are not significantly related to a reduction in the level of discretionary accruals. Our additional analysis, using small increases in earnings as a measure of earnings management, also found a negative association between this measure and the existence of an audit committee.No Full Tex