The Computational Modeling Core will focus on building, supporting, and extending the computational modalities used by COBRE Pi's for biomaterials synthesis and characterization. The Core Director, in conjunction with the Core Advisor will oversee daily operations of the Core, long-term planning for sustainability and growth, user training and support, and software/hardware management, and faculty mentoring/guidance in the context of using available resources. The COBRE cluster will integrate with the NSF MRl supported GPU (Graphics Processing Unit) cluster housed in the Chemistry and Biochemistry Department. During the course of this COBRE, we will plan to continue growing and updating the current cluster through replacement with 1) high-density (large core count) nodes with faster interconnects and 2) faster, adaptive, extensible storage capacities. We will anticipate increased user usage with newer faculty, and the CORE will support users with training via staff consultation, CORE director interactions with users, and numerous courses on campus to utilize the facilities. Proposed specific aims for the Computational Modeling Core are: 1) to provide reliable, flexible heterogeneous computational infrastructure (hardware, software, storage, networking) to support biomaterials design, synthesis, and characterization;2) to extend Computational capabilities to exploit Graphics Processing Units (GPU's) for biomaterials modeling;3) to develop a robust storage and archival infrastructure accommodating increasing data-storage loads incurred with faster hardware and additional users;and 4) to supply training for faculty, graduate students, post-doctoral researchers, and undergraduate students in contemporary and emerging high-performance computing paradigms.
Biomaterials are important in many applications affecting human health, including delivering drugs or creating new body tissues following injury. Making and studying these materials at the scale of atoms and molecules is tremendously important in allowing us to design, modify, and ultimately understand how these materials work. This CORE will support and provide infrastructure for application and development of methods based on computers thatwill aid in understanding the properties of these advanced biomaterials.
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|Ou, Shu-Ching; Cui, Di; Patel, Sandeep (2014) Association of alkanes with the aqueous liquid-vapor interface: a reference system for interpreting hydrophobicity generally through interfacial fluctuations. Phys Chem Chem Phys 16:26779-85|