Autonomic Computing

HECURA: Collaborative Research: QoS-driven Storage Management for High-end Computing Systems

In today's high-end computing (HEC) systems, the parallel file system (PFS) is at the core of the storage infrastructure. PFS deployments are shared by many users and applications, but currently there are no provisions for differentiation of service - data access is provided in a best-effort manner. As systems scale, this limitation can prevent applications from efficiently utilizing the HEC resources while achieving their desired performance and it presents a hurdle to support a large number of data-intensive applications concurrently.

Center for Cloud and Autonomic Computing

This award establishes the Industry/University Cooperative Research Center (I/UCRC) for Cloud and Autonomic Computing at the University of Florida, University of Arizona and Rutgers University. The I/UCRC will focus on multi university research on improving the design and engineering systems that are capable of funding themselves, adapting their resources and operations to current workloads and anticipating the needs of their users. The center will work on improving hardware, networks and storage, middleware, service and information layers used by modern industry.

Collaborative Research, II-NEW: An Instrumented Data Center Infrastructure for Research on Cross-Layer Autonomics

This project's goal is to acquire and develop an instrumented datacenter testbed spanning the three sites of the NSF Center for Autonomic Computing (CAC)-the University of Florida (UF), the University of Arizona (UA) and Rutgers, the State University of New Jersey (RU). Datacenters are a growing component of society's IT infrastructure, including services related to health, banking, commerce, defense, education and entertainment.

Autonomically Parallel and Distributed Semiconductor Data Analytics

The process of semiconductor manufacture will generate useful information to analyze the work procedure and environment changes, such as temperature, density, etc. The information is analyzed by measuring the factors of the manufacturing process using some statistical algorithms, such as process capability, etc.

During the semiconductor manufactural procedure, there are massive data generated every day. This project is to design and build an analysis system for processing massive semiconductor analytics data.

Grid Appliances: Simplifying Grid Computing with Self-organizing Wide-area Virtual Clusters

There is no doubt that a grid system is powerful; however, the expertise required and the complexity involved in setting up and maintaining one are deterrents to wider adoption of Grid computing, especially by non-experts. This project focuses on lowering the complexity and operator involvement required for the deployment and management of a wide-area Grid through the use of virtualization and self-organizing networks [2].

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