Cloud-Ready Research Applications
Building Cloud Images
CAC consultants build ready-to-use cloud images to help Cornell researchers get started using the cloud faster and more efficiently, enhancing their research productivity and results.
For example, CAC built five cloud images for Cornell social science researchers: a Windows image with IBMSPSS, MATLAB, Mathematica. R, Rscript, RStudio, SAS, and Stata/MP, and four custom Linux images with
Python, Miniconda, PostgreSQL, DataGrip, Kate editor, QIME2, PICRUSt, and R. Researchers use these images on Cornell’s on-premise Red Cloud, where the availability of 28 core instances with 224GB RAM is ideal for certain statistical analyses. Use of the images continues to grow; the Cornell Institute for Social and Economic Research (CISER) has purchased over 250 Red Cloud subscriptions to meet researcher demand.
Ready-to-use cloud images can also be built to take advantage of the availability of Red Cloud instances that now feature NVIDIA GPUs.
Containerizing Applications for Research Efficiency and Portability
CAC will containerize your research application so it will run efficiently on Cornell’s Red Cloud platform as well as on public clouds such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure, or even your laptop.
We have experience building a variety of scientific containers, from web-services (e.g., containers used by arXiv.org)
to high-performance computing containers, some of which employ MPI, including WRF. CAC also has experience developing applications that manage and use containers. Containerization and related technologies employed include Docker, Singularity, and Nix.
Supporting Cloud-Based Web Applications
CAC can assist you in making your research applications available over the internet, either locally or globally, through a Web browser. The computing power and data storage needed to run the application are hosted on Red Cloud or one of the public clouds.
For example, CAC supports a service to denoise Electron Spin Resonance (ESR) data using techniques developed in Cornell’s Dept. of Chemistry and Chemical Biology. Working interactively with the researchers, CAC consultants built the graphical interface for the Web front end and co-wrote the back-end code to filter out the noise from ESR datasets uploaded by collaborators. Results are plotted at each stage of the process, adjustments to parameters are made using a point-and-click interface, and the final, denoised data are downloaded by clicking a button.
Visit services available to learn more about related services such as Red Cloud computing. Exploratory accounts are available for free on Red Cloud.
if you have questions about our cloud-ready research applications services.