II-New: A Research Platform for Heterogeneous, Massively Parallel Computing

计算世界已经进入多核时代。除了多核CPU之外，在单个芯片中包含数千个计算核心的协处理器已经成为通用计算的流行平台。随着聚合计算能力的急剧增长，计算社区仍处于开发软件系统、框架和应用程序的早期阶段，以充分利用这些新平台。几种不同的多核系统的共存，包括图形处理单元（GPU），英特尔？许多集成核心（MIC）卡和加速处理单元（APU）使问题进一步复杂化。另一方面，这为跨越软件堆栈的不同层的有趣研究提供了机会。 该基础设施将支持多个协调的研究项目，这些项目将开发框架和软件系统，以实现需要高性能计算能力的新一类应用程序。大规模并行计算能力，以加速现有的研究，并使地面，在南佛罗里达大学（USF），一项突破性的新研究与密集计算有着同样的需求。该项目汇集了八名USF研究人员，他们在计算机科学与工程的几个核心学科开展研究项目：大数据管理，科学计算，系统安全，硬件设计，数据挖掘，计算机视觉和模式识别。具体而言，所请求的集群支持以下方面的研究：（1）在异构众核硬件环境中设计和优化新型数据流管理系统架构;（2）粗粒度分子模拟方法，允许精确模拟大规模原子系统;（3）部署安全策略的新系统，在策略组合和运行时性能方面都很出色;（4）高效建模和设计节能和安全的硬件系统;（5）使用模式理论自动解释活动;（6）快速大规模聚类;以及（7）生物医学图像数据的模式识别。该项目的智力价值来自于单个项目的创新和潜在的交叉-学科的思想，它可以在未来发芽。该基础设施预计将促进各个项目领域的算法，模型，表示和数据集的协作和交叉授粉，在研究人员之间建立协作网络。 此外，该集群预计将影响超过12个应用领域，通过正在进行和计划的研究项目之间的研究人员和他们的合作者在整个USF系统。教育和研究的直接利益也将通过项目，教学和培训的应用方面扩展到更大的社区。该集群的项目成果和媒体内容将在广受欢迎的USF工程博览会上展示，该博览会旨在教育和激励K-12学生学习数学、科学、工程和技术科目。

The world of computing has entered the multi-core age. In addition to multi-core CPUs, co-processors containing thousands of computing cores in a single chip have become popular platforms for general-purpose computing. With the aggregated computing capabilities increasing at a steep rate, computing communities are still in an early stage in developing software systems, frameworks and applications to take full advantage of these new platforms. The co-existence of several different multi-core systems, including the Graphics Processing Units (GPUs), Intel?s Many Integrated Core (MIC) cards, and Accelerated Processing Units (APUs), further complicates the issue. This, on the other hand, provides opportunities for interesting research that spans different layers of the software stack. This infrastructure will support multiple, coordinated research projects that will develop frameworks and software systems enabling a new class of applications requiring high-performance computing capabilities.The main goal of this project is to build a computer cluster with heterogeneous, massive parallel computing capabilities to accelerate existing research and enable ground-breaking new research that shares the same need for intensive computation at the University of South Florida (USF). This project brings together eight USF investigators with research projects in several core disciplines of computer science and engineering: big data management, scientific computing, system security, hardware design, data mining, computer vision and pattern recognition. Specifically, the requested cluster supports research in: (1) design and optimization of a novel data stream management system architecture in a heterogeneous many-core hardware environment; (2) coarse-grained molecular simulation approach that allows accurate simulation of large-scale atomistic systems; (3) new system to deploy security policies that excel in both policy composition and runtime performance; (4) efficient modeling and design of energy-efficient and secure hardware systems; (5) automated interpretation of activities using pattern theory; (6) fast large scale clustering; and (7) pattern identification from biomedical image data.The intellectual merit of this project derives from the innovations of the individual projects and from the potential cross-disciplinary ideas it can germinate in the future. The infrastructure is expected to facilitate collaboration and cross-pollination of algorithms, models, representations, and data sets across individual project areas, building a collaborative network across the investigators. Furthermore, the cluster is expected to impact over a dozen application domains via on-going and planned research projects among the investigators and their collaborators throughout the USF system.Direct benefits to education and research will also be extended to the larger community through the applied aspects of projects, teaching and training. Project results and media content of the cluster will be showcased in the popular USF Engineering EXPO event, which seeks to educate and motivate K-12 students on math, science, engineering, and technology subjects.