Multiple voice disorders in the same individual: Investigating handcrafted features, multi-label classification algorithms, and base-learners

Abstract

At the heart of this platform is a database archiving the performance and execution environment related data of standard parallel algorithm implementations run on different�computing architectures�using different programming environments. The online plotting and analysis tools of our platform can be combined seamlessly with the database to aid self-learning, teaching, evaluation and discussion of different HPC related topics, with a particular focus on a holistic system�s perspective. The user can quantitatively compare and understand the importance of numerous deterministic as well as non-deterministic factors of both the software and the hardware that impact the performance of parallel programs. Instructors of HPC/PDC related courses can use the platform�s tools to illustrate the importance of proper data collection and analysis in understanding factors impacting performance as well as to encourage peer learning among students. Scripts are provided for automatically collecting performance related data, which can then be analyzed using the platform�s tools. The platform also allows students to prepare a standard lab/project report aiding the instructor in uniform evaluation. The platform�s modular design enables easy inclusion of performance related data from contributors as well as addition of new features in the future.