Development of a low-cost 64 bit cluster supercomputer for engineering and physics simulations

Utah State University, Logan UT

Investigators

Abstract

ABSTRACT Proposal No. CTS-0321170 Principal Investigator: J. T. Hauser, Utah State University This grant focuses on combining two leading-edge technologies, dual-processor AMD Opteron systems and Flat Neighborhood Networks (FNNs) based on Gigabit Ethernet, to develop a uniquely designed cluster supercomputer. In addition to providing a 64-bit memory address space, the Opteron uses a new memory architecture that should avoid the memory performance degradation normally associated with shared-memory multiprocessors. Similarly, using a FNN interconnection pattern makes it possible to achieve single-switch latency despite having more nodes than a low-cost network switch has ports. FNNs also provide the possibility to optimize the networking characteristics toward the communication patterns of applications running on the proposed cluster supercomputer. This project will provide a low-cost alternative to commercially available high performance cluster networking solutions such as Myrinet and Quadrics. The software to design and optimize such a network will be made available for free, so that other research groups can design and build their own cluster with FNNs. The proposed system will also provide valuable insight in the performance of a newly designed memory system for large applications compared to other available memory system designs. The research to be conducted includes computational fluid dynamics, ecohydraulics, fusion plasmas, geophysical fluid dynamics and computational chemistry. To meet the rising demand for students skilled in high-performance computing, the College of Engineering will introduce a course in parallel computing for engineering applications targeted at senior level undergraduate and beginning graduate students. This course as well as a one-week workshop on cluster computing will also be open to students in mathematics, physics, chemistry and computer science. In addition, the proposed cluster supercomputer will enhance current relationships with nearby national laboratories such as the Idaho National Engineering and Environmental Laboratory (INEEL). USU faculty and graduate students are developing very computationally intensive CFD models in conjunction with INEEL engineers. The visibility arising from this cooperative effort will further enhance the goal of attracting more students and faculty.