Cloud Computing

Cloud computing is now the dominant approach for deployment of scalable web services, and recent advancements in GPU virtualization technology now make it possible to use cloud computing for large-scale scientific computing, data analysis, and visualization tasks. Cloud computing involves the use of computational equipment provided by a third-party, accessed through an internet connection, and paid for on an on-demand, as-needed basis. The cloud computing model provides researchers with access to powerful computational equipment that would otherwise be too costly to procure and maintain on their own. Furthermore, structural modeling often involves the use of different software suites, and bundling them together on a cloud platform gauruntees their availablity and interoperability on a standardized system.

We have made MDFF available on the Elastic Compute Cloud (EC2) of Amazon Web Services (AWS) to highlight the platform's capability in providing easily accessible computational power sufficient for rapidly fitting structures to EM density with MDFF. EC2 provides a cost-effective and practical solution for many MDFF applications across a wide range of computational hardware.

One-click launch in the Amazon Marketplace

Our cloud virtual machine image is availble in the Amazon Marketplace, which allows users to use a very simple one-click launch using pre-configured choices of instance types that have been tested with our software.

Hardware details on the available instance types of EC2 can be found here, while pricing information can be found here. We recommend using one of the GPU-accelerated instance types (p3 or p2) for running MDFF simulations, and g3 instance types for setup, analysis, and visualization. For ReMDFF simulations which require running many replicas, we recommend the compute optimized instance types (c5 or c4).