Physical Sciences and Mathematics Commons^™

A Cost-Benefit Analysis Of A Campus Computing Grid, Preston M. Smith

Purdue Polytechnic Masters Theses

Any major research institution has a substantial number of computer systems on its campus, often in the scale of tens of thousands. Given that a large amount of scientific computing is appropriate for execution in an opportunistic environment, a campus grid is an inexpensive way to build a powerful computational resource. What is missing, though, is a model for making an informed decision on the cost-effectives of a campus grid. In this thesis, the author describes a model for measuring the costs and benefits of building a campus computing resource based on the institution’s existing investment in computing hardware.

For …

Cloud Computing: Architectural And Policy Implications, Christopher S. Yoo

All Faculty Scholarship

Cloud computing has emerged as perhaps the hottest development in information technology. Despite all of the attention that it has garnered, existing analyses focus almost exclusively on the issues that surround data privacy without exploring cloud computing’s architectural and policy implications. This article offers an initial exploratory analysis in that direction. It begins by introducing key cloud computing concepts, such as service-oriented architectures, thin clients, and virtualization, and discusses the leading delivery models and deployment strategies that are being pursued by cloud computing providers. It next analyzes the economics of cloud computing in terms of reducing costs, transforming capital expenditures …

Quality Of Service Based Data-Aware Scheduling, Archit Kulshrestha

LSU Doctoral Dissertations

Distributed supercomputers have been widely used for solving complex computational problems and modeling complex phenomena such as black holes, the environment, supply-chain economics, etc. In this work we analyze the use of these distributed supercomputers for time sensitive data-driven applications. We present the scheduling challenges involved in running deadline sensitive applications on shared distributed supercomputers running large parallel jobs and introduce a ``data-aware'' scheduling paradigm that overcomes these challenges by making use of Quality of Service classes for running applications on shared resources. We evaluate the new data-aware scheduling paradigm using an event-driven hurricane simulation framework which attempts to run …