Acquisition of Large-Memory, Many-Core Compute Node for Mathematical Science Research

购买大内存、多核计算系统并将其集成到大型、分布式、高性能计算集群中，为克莱姆森的研究人员提供了机会，以增加在数学科学的几个研究领域中可以解决的问题的规模，并扩大共享内存、并行算法的规模，以应对芯片制造商正在开发的新的多核计算系统。此外，它还为开发创新的、异质的、共享分布的算法来解决问题创造了可能性，而这种方法是有希望的。在大内存和异质计算系统有望有效的重要领域包括：计算优化、3-D过滤系统的模拟、可靠性和存活率的统计模型、计算细胞生物学、生化建模、量子分子动力学和组合数论。大内存、多核系统在美国的研究人员并不广泛使用。这一资源将是对美国科学计算资源池的宝贵补充。

The purchase of a large-memory, many-core computing system and its integration into a large, distributed, high-performance computing cluster provides the opportunity for researchers at Clemson to increase the size of problems that can be solved in several research areas in the mathematical sciences and to scale up shared-memory, parallel algorithms in anticipation of new, many-core computing systems under development by chip manufacturers. In addition, it creates the possibility of developing innovative, heterogeneous, shared-distributed algorithms for problems where that approach is promising. Among the important areas where large-memory and heterogeneous computing systems promise to be effective are: computational optimization, simulation of 3-D filter systems, statistical models of reliability and survival, computational cell biology, biochemical modeling, quantum molecular dynamics, and combinatorial number theory. Large-memory, many-core systems are not widely available to researchers in the US. This resource will be a valuable addition to the pool of resources for scientific computing in the United States.