Research Initiation Award: Advancing Research on Data Analysis with High Performance Computing

研究启动奖为传统黑人学院和大学的初级和中期职业教师提供支持，他们正在建立新的研究项目或重新指导和重建现有的研究项目。期望该奖项有助于进一步提高教师的研究能力和效率，改善其所在机构的研究和教学，并使本科生参与研究经验。该奖项授予Prairie View A&amp；M大学在许多领域具有潜在的更广泛的影响。该项目的目标是通过高性能计算研究来推进大数据分析。该项目的源代码将在开源许可下作为库的一部分提供，以促进信号处理社区内的可重复研究。这项研究可以应用于国土安全、精准农业和地理空间应用等领域。该项目还将提高Prairie View A&amp；M大学本科生的研究经验和培训。研究目标是利用基于高性能计算（HPC）的新型信号处理技术，提高分析数字数据集的能力，包括图像、视频、天气数据和DNA数据序列压缩。该项目将研究如何在高性能计算环境中提高数据分析的效率，包括图像处理、视频处理和计算机可视化。通过这些技术的有效整合，大数据分析过程的速度将大大提高，分析质量将显著提高。该项目侧重于建立基于HPC的数字信号处理系统的策略，最终将这些算法和模拟扩展到其他类型的数据集。

Research Initiation Awards provide support for junior and mid-career faculty at Historically Black Colleges and Universities who are building new research programs or redirecting and rebuilding existing research programs. It is expected that the award helps to further the faculty member's research capability and effectiveness, improves research and teaching at his home institution, and involves undergraduate students in research experiences. The award to Prairie View A&M University has potential broader impact in a number of areas. The goal of the project is to advance big data analysis with research in high performance computing. Source code from the project will be provided as part of a library under an open-source license in an effort to promote reproducible research within the signal-processing community. This research can have applications in areas such as homeland security, precision agriculture, and geospatial applications. The project will also enhance the research experience and training of undergraduate students at Prairie View A&M University. The research goal is to advance the ability of analyzing digital data sets, including image, video, weather data, and DNA data sequence compression, with novel high performance computing (HPC) based signal processing techniques. The project will investigate how to increase the efficiency of data analysis, including image processing, video processing, and computer visualization, in a high performance computing environment. By efficiently integrating such technologies, the speed of the big data analysis processes will be dramatically increased and the analysis quality will be significantly improved. The project focuses on strategies for establishing an HPC based digital signal processing system, eventually extending these algorithms and simulations to other types of data sets.