In this screencast BioTeam shows how it can orchestrate an Accelrys Pipeline Pilot experiment running on a remote cloud (BT Compute) via Apple iOS Siri voice control.
In December the DOE Office of Advanced Scientific Computing Research (ASCR) published a report on Cloud Computing for Science. The key findings were
- Cloud approaches provide many advantages, including customized environments that enable users to bring their own software stack and try out new computing environments without significant adminis- tration overhead, the ability to quickly surge resources to address larger problems, and the advantages that come from increased economies of scale. Virtualization is the primary strategy of providing these capabilities. Our experience working with application scientists using the cloud demonstrated the power of virtualization to enable fully customized environments and flexible resource management, and their potential value to scientists.
- Cloud computing can require significant initial effort and skills in order to port applications to these new models. This is also true for some of the emerging programming models used in cloud computing. Scientists should consider this upfront investment in any economic analysis when deciding whether to move to the cloud.
- Significant gaps and challenges exist in the areas of managing virtual environments, workflows, data, cyber-security, and others. Further research and development is needed to ensure that scientists can easily and effectively harness the capabilities exposed with these new computing models. This would include tools to simplify using cloud environments, improvements to open-source clouds software stacks, providing base images that help bootstrap users while allowing them flexibility to customize these stacks, investigation of new security techniques and approaches, and enhancements to MapReduce models to better fit scientific data and workflows. In addition, there are opportunities in exploring ways to enable these capabilities in traditional HPC platforms, thus combining the flexibility of cloud models with the performance of HPC systems.
- The key economic benefit of clouds comes from the consolidation of resources across a broad community, which results in higher utilization, economies of scale, and operational efficiency. Existing DOE centers already achieve many of the benefits of cloud computing since these centers consolidate computing across multiple program offices, deploy at large scales, and continuously refine and improve operational efficiency. Cost analysis shows that DOE centers are cost competitive, typically 3–7x less expensive, when compared to commercial cloud providers. Because the commercial sector constantly innovates, DOE labs and centers should continue to benchmark their computing cost against public clouds to ensure they are providing a competitive service.
Eagle Genomics have a nice summary, that addresses many of the highlighted issues.