NSF Award
1726500
As traditional data processing devices are no longer adequate to handle complex data sets and large computations due to the continuing information explosion, a high performance computing cluster (HPCC) has become an essential instrument for a wide variety of leading-edge research and educational activities. Lamar University (LU), a medium-sized non-PhD granting four-year university with more than 15,000 students will acquire and deploy a HPCC to enhance compute-intensive and data-intensive studies and to facilitate discipline-specific and multidisciplinary research through a shared state-of-the-art computing platform. The instrumentation will strongly support LU's high priority current and future research needs as well as benefit a variety of regional academic institutions and industries.<br/><br/>Specifically, the project will acquire a hybrid CPU/GPU HPCC which will make it possible to deploy the best suited computing nodes to perform traditional CPU-based, GPU-based, and hybrid CPU/GPU-based data-intensive computing tasks at LU. The resource will enable the exploration of creative research areas and establish new cross-disciplinary studies in the areas of imaging genomics, deep learning, big data, computational neuroscience, molecular physics, advanced materials research, scientific optimization, water and air quality analysis, transportation systems, electronic structure calculations, nucleic acid biomarker discovery and epigenetics, and many more. <br/><br/>Furthermore, as a shared research resource, the HPCC will not only promote cross-disciplinary collaborations among faculty members from different departments within the university, but also enable LU to promote and strengthen collaborative opportunities with other research institutions. In addition, the instrument will also become an essential educational tool with the potential to foster interest among faculty in the development of new courses that will integrate state-of-the-art research into undergraduate and graduate curricula. Additionally, the project will provide access to the resource to users from other academic institutions and industrial partners in the Golden Triangle area in Southeast Texas. Finally, the project will organize outreach activities for K-12 students from local Independent School Districts (ISDs) that have high minority and low-income ratios to study in science, technology, engineering, and mathematics (STEM) areas.
