Resources for researchers and institutions to work remotely
The rapidly changing and dynamic global health situation has impacted the lives of many people including researchers at universities and institutions worldwide. Many academic institutions are migrating to remote operations. Researchers are processing data, collaborating online, and trying to maintain labs remotely. Amazon and Amazon Web Services (AWS) are responding to these events in support of our communities and deploying resources and technology to enable remote learning and home working. Researchers can access the following to help them through this unprecedented situation:
High Performance Computing (HPC) and container-based resources
- AWS ParallelCluster is a fully supported and maintained open-source cluster management tool that makes it easy for scientists, researchers, and IT administrators to deploy and manage HPC clusters. It also supports a variety of job schedulers that are used in universities such as SGE, Torque, and SLURM, for easy job submissions.
- NICE DCV is a high-performance remote display protocol that provides researchers with a secure way to deliver remote desktops and application streaming to any device over varying network conditions.
- Cloud bursting using HTCondor allows researchers to elastically auto expand their university HPC resources to AWS using an HTCondor-based scheduler. HTCondor is a workload management system used by thousands of research institutions around the world and is funded by the National Science Foundation.
- AWS Batch is a cloud-native, container-based service that enables researchers to efficiently run hundreds of thousands of batch computing jobs in containers.
Virtual research environments
- Amazon AppStream 2.0 is a fully managed application streaming service that allows researchers to access the applications they need on any computer. Now AppStream provides desktop streaming as well, for qualified academic institutions. Researchers simply open a web browser, choose the application or desktop they need, and start working. This is useful for non-persistent desktop needs and/or open-access computer labs, where users can run desktops and applications chosen by the academic institution (or research collaboration environment).
- Amazon Web Services (AWS) Service Catalog allows academic organizations to create and manage catalogs of IT services with their university research environments.
- Amazon WorkSpaces is a managed, secure Desktop-as-a-Service (DaaS) solution that helps researchers access virtual, persistent Windows and Linux desktops anywhere with an internet connection.
Datasets, analytics tools, and machine learning resources
- Open data on AWS helps researchers to share datasets with anyone in the world.
- Globus for Amazon S3 allows researchers to share data with 120,000+ users, across 600+ Identity providers with 1000+ research institutions.
- AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud. For example: Academic researchers can subscribe and use the New York Times COVID-19 Data in the United States. Check out other AWS Data Exchange’s data related to COVID-19. AWS Data Exchange has more than 2000 data products from more than 100 qualified data providers across industries such as financial services, healthcare, retail, media & entertainment, and more. AWS Data Exchange includes over 800 free data sets too.
- Data Lake on AWS offers researchers a way to import data with different schemas and formats into flexible storage. The solution deploys a console that researchers and collaborators can access to search and browse available datasets for their research domains.
- AWS AI services including machine learning (ML) can help quickly build, train, and deploy ML models at scale; or build custom models supporting popular algorithms (including Linear Learning, K-Means, XGBoost, Image Classifications, Sequence to Sequence, and Latent Dirichlet Allocation ) and frameworks (such as TensorFlow, Apache MXNet, PyTorch and Scikit-learn).
Remote device monitoring
AWS Internet of Things (AWS IoT) and IoT 1-Click can be used to monitor labs, specimens, and reagents for temperature, humidity, and vibration, and to predict whether failures are imminent in labs with appropriate logging and alerts.
AWS programs and awards
- The AWS Machine Learning Research Awards fund university departments, faculty, PhD students, and post-docs that are conducting novel research in ML.
- AWS launched the HPC on AWS for COVID-19 Research and AWS Diagnostic Development Initiative (DDI) to provide support for diagnosis, treatment, and vaccine studies.
- The AWS Cloud Credits for Research Program supports researchers who seek to build cloud-hosted, publicly available science-as-a-service applHPC workshops ications, software, or tools to accelerate their scientific research and support research communities.
- AWS Promotional Credit can help research institutions around the world facilitate remote education, remote government work, and help accelerate healthcare research. AWS is also providing no-cost usage of Amazon Chime, Amazon WorkSpaces, and Amazon WorkDocs through June 30 worldwide.
Workshops and educational opportunities
In addition to the Jeff Barr’s list, these workshops and solutions can help researchers:
- AWS Research Workshops with a set of Jupyter Notebooks for hands on workshops in data lakes, AI + ML, IoT, and genomics
- AWS Security Workshops
- Elastic Kubernetes and HPC Workshops
- Amazon SageMaker Workshop
- A Scientist’s Guide to Cloud-HPC: Example with AWS ParallelCluster, SLURM, Spack, and WRF
For us and for many of our research collaborators across the world, this isn’t the way we imagined to start the new year. We are all learning as we go. Please contact us if there is anything we can do to help, especially during this critical period.