CC* Compute: Acquisition of a Lehigh University HPC cluster to enhance collaboration, research productivity and educational impact

该项目正在利哈伊大学构建和部署高性能计算能力，这将使物理学，化学，生物学，计算机科学，工程学等新的研究合作成为可能。 这项工作直接支持了NSF的使命，即通过为科学和工程研究中更广泛的计算提供关键基础设施来促进科学的进步。 此外，新资源的一部分专门用于围绕计算的教育，包括支持增加STEM相关专业中代表性不足的人口数量的努力。最后，一部分资源专门用于为国家开放科学网格（OSG）做出贡献。新资源结合了CPU和GPU节点，进一步拓宽了支持的应用程序和相关研究，包括电子结构计算、原子和粗粒度分子模拟、蒙特卡罗模拟、数据科学和深度学习模型。 它还允许传统上使用基于CPU架构的研究人员探索基于GPU的计算。 围绕新合作建立的一些具体科学驱动因素包括：（i）理解异质催化过程的基本机制，（ii）实现本体异质结有机太阳能电池的预测设计，（iii）预测先进材料的热机械性能，以及（iv）阐明人类血液中流动响应蛋白质背后的机制。 在这种支持下开展的工作扩大了利哈伊社区的研究联系，并提高了利哈伊开展高影响力研究、教育下一代科学家和工程师的能力，并扩展高性能计算和模拟的使用-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智力价值和更广泛的影响进行评估来支持审查标准。

This project is constructing and deploying high performance computational capability at Lehigh University that will enable new research collaborations across Physics, Chemistry, Biology, Computer Science, Engineering. The work directly supports NSF’s mission to promote the progress of science by also providing critical infrastructure for broader incorporation of computation in science and engineering research pursuits. Further, a portion of the new resources is dedicated to education around computation, including support of efforts to increase the number of members of underrepresented populations in STEM-related professions. Finally, a portion of the resources is dedicated to contributing to the national open science grid (OSG). The new resource combines CPU and GPU nodes to further broaden the applications and associated research that are supported including electronic structure calculations, atomistic and coarse-grained molecular simulations, Monte Carlo simulations, data science, and deep learning models. It also allows researchers who have traditionally utilized CPU-based architectures to explore GPU-based computation. Some of the specific scientific drivers around which new collaborations will be built include (i) understanding fundamental mechanisms of heterogeneous catalytic processes, (ii) realizing predictive design of bulk heterojunction organic solar cells, (iii) predicting thermo-mechanical properties of advanced materials, and (iv) elucidating mechanisms behind flow responsive proteins in human blood. Work under this support expands the Lehigh community’s research connections and advances Lehigh’s ability to generate high impact research, educate the next generation of scientists and engineers, and expand the usage of high performance computation and simulation-guided science in research and education.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.