Computational Chemical Engineering on a Dedicated Beowulf Cluster

摘要：大卫S. Sholl，Lorenz T. Biegler and Steinar Hauan Institution：Carnegie Mellon UniversityProposal Number：0094407这是一项设备赠款，用于提供资金购买32节点Beowulf集群，以支持卡内基梅隆大学三个研究小组使用的高级计算研究。 Beowulf集群代表了先进计算的有利架构：它们构建成本低，配置灵活，并为各种科学计算任务提供强大的计算环境。 共享集群的三个研究小组将进行分子动力学和计算化学，建模和可视化研究，以支持过程合成和大规模离散和连续过程优化。 因此，集群将为需要在分钟和小时的时间尺度上的高峰性能的计算提供服务，同时沿着在天的时间尺度上的持续计算性能。 这些互补的特征意味着，通过共享集群，其能力将比任何单独的小组得到更充分的利用。 集群也可以很容易地以在不同使用模式之间分配资源的方式操作，而不会产生显著的计算开销。 该集群最初将使PI的计算能力提高约三倍，并将在随后的几年中扩展，并将在未来五年内将其计算能力提高一个数量级以上，而不会使现有节点过时。具体而言，三个小组的研究包括开发新的算法：计算化学中的计算，特别是在分子动力学和蒙特卡罗模拟中，从原子尺度结构的细节确定宏观材料性质;用于工艺设计和合成的精确工艺建模，包括相平衡、工艺备选方案的表示和评估以及设计见解的可视化;和优化大规模的稳态和动态过程，涉及离散和连续决策沿着与先进的分解策略。

ABSTRACTPI: David S. Sholl, Lorenz T. Biegler and Steinar Hauan Institution: Carnegie Mellon UniversityProposal Number: 0094407This is an equipment grant to provide funds to purchase a 32 node Beowulf cluster to support research in advanced computing to be used by three research groups at Carnegie Mellon University. Beowulf clusters represent an advantageous architecture for advanced computing: they are inexpensive to construct, flexible to configure, and provide a powerful computing environment for a broad variety of scientific computing tasks. The three research groups that will share the cluster will be conducting research on molecular dynamics and computational chemistry, modeling and visualization to support process synthesis and large-scale discrete and continuous process optimization. The cluster will thus serve computations that require high peak performance on time scales of minutes and hours, along with sustained computational performance on time scales of days. These complementary profiles mean that by sharing the cluster, its capabilities will be used more fully than they would be by any group individually. The cluster can also easily be operated in a way that distributes resources between different usage modes without significant computational overhead. The cluster will initially increase the PIs' computational capabilities by about a factor of three and will be expandable over succeeding years and will increase their computing power by over an order of magnitude within the next five years, without rendering existing nodes obsolete.Specifically, the research of the three groups consists of the development of new algorithms for: Calculation in computational chemistry, particularly in molecular dynamics and Monte Carlo simulations to determine macroscopic material properties from details of atomic-scale structure;Accurate process modeling for process design and synthesis that includes phase equilibrium, representation and evaluation of process alternatives and visualization of design insights; andOptimization of large-scale steady state and dynamic processes that involve both discrete and continuous decisions along with advanced decomposition strategies.