MRI: Development of Heterogeneous Cluster for Cyber-Physical System Hybrid Analytics

University Of Tulsa, Tulsa OK

Investigators

Abstract

The proposed instrument provides a foundation for new research activities enhancing existing research efforts, and fuels new collaboration within and the beyond institution. It comprise a uniquely capable high performance computing resource in the state and in the region. The heterogeneous cluster will be leveraged to yield superior modeling and understanding of seismic events, improve neuro-image analysis capabilities, enhance cyber-security tools, and inspire new vehicle crash-reconstruction methodologies. The educational activities augment the offerings of the institution and provide a template for development of a curriculum to prepare individuals for careers in the field of heterogeneous computing. Further, access to the cluster and the analytic tools developed for it fortify theoretic and applied courses, allowing students to approach and study real-world problems of a larger scale. This project builds a novel computational resource in the form of a heterogeneous cluster (CPU/MIC co-processor /FPGA), as a platform for research and innovation spanning several lines of inquiry across multitude fields in science and engineering. Specifically, this experimental hybrid cluster aims to service and advance research in emerging cyber-physical systems that have diverse computational needs. This work addresses current computing problems that continue to grow in size and scope, and quickly exhaust the capabilities of traditional homogeneous architectures in terms of execution time and cost. While various computing platforms exist, including the traditional CPU, field programmable gate arrays (FPGAs), many integrated core (MIC) co-processors, and graphic processing units (GPUs), these problems often possess traits that would benefit from a distribution of work based on the algorithmic needs and the capabilities of the underlying hardware. Thus, this development combines traditional CPUs with FPGAs, MICs, and GPUs forming a heterogeneous architecture capable of delivering the next advance in computational performance. The instrument allows investigators to address larger and more complex problems through computer simulation and analysis spanning the areas of cyber-physical system security, seismic modeling, neuroinformatics, crash reconstruction, and chemical reaction modeling. CPUs excel at complex multi-threaded applications with significant numbers of control (branch) instructions; MICs excel at problems with high spatial locality and that fit the SIMD mold; and FPGAs provide a blank canvas that can be configured to best fit the needs of a particular problem. Current hard problems require the strengths of each of these types of devices and this instrument provides a platform to solve such problems and to research how best to use the proposed heterogeneous platform. These results will advance the theoretical understanding of these processes. The heterogeneous cluster will expand understanding in the areas of the design of future heterogeneous clusters and interconnect architecture, in unified programming platforms and languages, and in workload division among diverse computational elements. Finally, the heterogeneous cluster will support advances in the science of Honeynets for security analysis, the implementation of bump-in-the-wire cyber-security monitoring tools, and advanced security vulnerability discovery.