Computational Core

计算核心

• 批准号: 8735402
• 负责人: Sandeep Patel
• 金额: $ 13.03万
• 依托单位: UNIVERSITY OF DELAWARE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8735402
• 关键词: Affect; Biochemistry; Biocompatible Materials; Centers of Research Excellence; Chemistry; Computer Simulation; Computer software; Computers; Consultations; Data Storage and Retrieval; Faculty; Growth; Health; High Performance Computing; Housing; Human; Injury; Mentors; Modality; Modeling; Molecular; Pharmaceutical Preparations; Postdoctoral Fellow; Process; Property; Research Infrastructure; Research Personnel; Resources; Teacher Professional Development; Tissues; Training; Training Support; Update; Work; base; computer infrastructure; density; design; flexibility; graduate student; method development; operation; undergraduate student

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.

计算建模核心将专注于构建、支持和扩展计算