Enabling Cloud Computing for Seamless Research Computation

The provision of computing resources to researchers using a cloud computing delivery model can lower costs and reduce barriers for researchers, while increasing utilization and uptake for infrastructure providers. However, this model of access to infrastructure still requires technical expertise, custom software development or re-engineering, and often the need to work remotely in an unfamiliar environment. This proposal seeks to instead treat the cloud as a natural extension of a researcher's preferred computing device, with no specialized knowledge required. This is the next step in the evolution of cloud resources.Researchers of all disciplines and backgrounds have long used computing resources to support and augment their research. The broad umbrella of "cloud computing" as an emerging mechanism for resource delivery has shifted how researchers acquire and utilize computing resources. Of particular interest is on-demand, service-driven access to computing infrastructure (infrastructure-as-a-service, IaaS). In lieu of acquiring physical machines, a researcher is granted temporary access to virtual or physical resources, using only what they need, and (if applicable) paying only for what they use. For those with sporadic but intensive computation needs, this approach reduces costs. In addition to various public cloud providers (Amazon, IBM), institutions and coalitions with a long history of providing high-performance computing are making their resources available in a similar model.Despite the advantages of IaaS for research, making use of these resources still requires technical expertise (through training, hiring, or outsourcing) which imposes barriers of time and cost. For example, research software might be re-engineered to work in batch mode with checkpoints, or Matlab jobs might be ported to Matlab Distributed Computing, or an analysis task re-written to use the Map-Reduce paradigm.This proposal seeks to enable the cloud as a seamless extension of a personal device and workspace. For example, a researcher might proceed as normal using their preferred software packages, until a longer computation begins. This task would be pushed to remote resources for execution, then pulled back to the local machine some time after completing. To achieve this goal, this project will a) Understand current research workflows systematically, using observation, instrumentation, and interviews. The objective is to understand how researchers currently use computation resources and how that process meets their expectations. b) Advance the state of the art in moving tasks from one physical machine to another, drawing on virtual machine migration, process migration, and machine cloning. c) Create a workflow augmented with usable technology to enable researchers to push work to the cloud. d) Extract from this implementation and detailed analysis the requirements and design for a similar approach to general users.These objectives will advance the state-of-the-art in cloud-style access to computing resources, addressing usability concerns. The described approach moves beyond task-specific software offered as a service, allowing researchers to use their preferred software, without the latency impact of remote desktop solutions. Reducing barriers to using computation to extend and enhance research will also have a broader impact on other disciplines.