Equipment: MRI: Track 1 Acquisition of NVIDIA DGX H100 GPU system for research and education at VCU

图形处理单元（GPU）已成为支持广泛研究领域的重要计算工具。该项目资助购买一个高性能GPU集群，安装在弗吉尼亚联邦大学（VCU）高性能研究计算（HPRC）核心用户设施上，该设施为研究和教育目的提供对高性能计算集群的共享访问。GPU仪器将有利于22个研究小组的研究和培训活动，并影响整个大学的400多个用户。此次收购推动了人工智能、建模和模拟领域的下一代研究，涉及计算机科学、工程、生命科学和物理科学等广泛学科。进一步的好处包括前沿研究，研究生和本科生的研究培训，课程和课程开发，K-12推广影响以及代表性不足的少数民族的参与。新资源还将加强跨学科研究，并拓宽与当地工业和联邦实验室的跨学科合作活动。收购NVIDIA DGX H100 GPU系统将显着扩展VCU的GPU计算能力，以帮助满足不断增长的高性能计算需求各个科学工程学科。将从该设备中受益的关键研究项目涉及高速数据流的机器学习、深度学习和量子机器学习、神经调节等领域。（经颅磁刺激和脑深部电刺激），计算化学（量子化学），光学和半导体缺陷（氮化镓）、使用深度学习的软件漏洞预测、纳米磁性材料和纳米级磁性设备、实时流行病管理架构、安全灵活的医疗物联网基础设施（保护部署在网络边缘组件的网络攻击），以及孤立有机分子阳离子的超快解离动力学。该项目还将支持培训高中生、本科生、研究生和博士后研究员，从事计算机科学、工程、物理和化学等前沿跨学科研究，加强与附近HBCU的现有联系，以及扩展K-该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识产权进行评估来支持。优点和更广泛的影响审查标准。

Graphic Processing Units (GPUs) have become an essential computational tool in support of a wide range of research areas. This project funds the acquisition of a high-performance GPU cluster to be installed at the Virginia Commonwealth University (VCU) High-Performance Research Computing (HPRC) core user facility, which provides shared university-wide access to high-performance computing clusters for research and education purposes. The GPU instrumentation will benefit the research and training activities of 22 research groups and impact 400+ users across the entire university. The acquisition advances next-generation research in artificial intelligence, modeling, and simulations across a broad range of disciplines including computer science, engineering, life sciences, and physical sciences. Further benefits include those to cutting-edge research, research training of graduate and undergraduate students, course and curriculum development, K-12 outreach impacts, and the participation of underrepresented minorities. The new resources will also strengthen interdisciplinary research and broaden collaborative activities across disciplines with local industry and federal laboratories.The acquisition of a NVIDIA DGX H100 GPU system will significantly expand the GPU computing capacity at VCU to help satisfy the increasing high-performance computing demand across various science & engineering disciplines. The key research projects that will benefit from this equipment are in the areas of machine learning for high-speed data streams, deep learning and quantum machine learning, neuromodulation (transcranial magnetic stimulation and deep brain stimulation), computational chemistry (quantum chemistry), optics and defects in semiconductors (gallium nitride), software vulnerability prediction using deep learning, nanomagnetic materials and nanoscale magnetic devices, real-time pandemic management architecture, secure and flexible medical IoT infrastructure (protection from cyberattacks deployed at network edge components), and ultrafast dissociation dynamics of isolated organic molecular cations. This project will also support the training of high-school, undergraduate, graduate students and postdoctoral fellows in cutting-edge interdisciplinary research spanning computer science, engineering, physics, and chemistry, strengthening existing ties with nearby HBCUs, as well as expanding K-12 minority outreach programs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.