Amazon Web Services (AWS) offers a scalable cloud infrastructure to research scientists. It delivers a suite of integrated services, which you can use to build and manage high-performance computing clusters in the cloud streamline workloads, such as seismic imaging, weather prediction, financial risk modeling, computational chemistry, and genomics.
High-performance computing on AWS leads to zero-wait times and improved productivity. It offers virtually unlimited scalability and flexible configuration, enabling you to grow and shrink the infrastructure depending on your workload. Researchers can also access Machine Learning, Artificial Intelligence, Data analytics, and other cloud-based services to redesign high-performance computing workflows. Read on!
Scalability
AWS is an excellent platform for research scientists to use different tools for running genomic workloads. AWS high-performance computing allows you to store and compute data dynamically, efficiently, and reliably. It also offers tools that you use to collaborate with years. Similarly, using AWS, you can incorporate machine learning algorithms and analytics for your big genomic data.
Zero Wait Time
Research scientists integrate AWS with their research projects to successfully move their higher-performance workloads. AWS enables you to access the infrastructure capacity to run high-performance computing applications.
Unlike on-premise resources, AWS eliminates long job queues and wait times, supporting you to achieve results efficiently and quickly. You can integrate high-performance workflows with machine learning, artificial intelligence, data analytics, and other related technologies because you have access to a wide range of cloud services.
Risk Management & Analysis
AWS offers flexible grid-computing tools and features that can be used by research scientists to run simulations quickly. It helps them identify risks with data and provide tools for data optimization.
Likewise, it helps research scientists process complex workloads through highly-scalable and secure databases, storage, compute, and networking capabilities. So, you can analyze massive data pipelines quickly and share your results with your institution effectively.
Latest Analytics Tools
AWS allows scientists access to the latest computing architectures and frameworks to maintain their projects. It enables a researcher to get access to advanced analytics, artificial intelligence, and machine learning tools.
For example, Amazon Athena is a state-of-the-art tool for managing databases and pooling data from different sources into the AWS Lake Formation. Using a Data Lake, a researcher can successfully perform various queries to streamline the process.
Moreover, as a researcher, you can build and maintain a “Research, Electronic, and Data Capture” environment (Redcap) to collect and organize your research data. For instance, analytic tools in biomedical research can allow for large-scale endeavors to integrate clinical, genomic, and behavioral data to innovate your precision medicine findings.
Final Words
Scientific research these days is considered a compute-intensive activity, but most scientists do not have IT expertise and skills; this is where AWS comes in. It helps scientists and researchers focus on their projects and not servers. Clovertex is an innovative platform that offers unique AWS solutions to researchers and scientists to achieve more productivity with less effort and more confidence. We have advanced AWS solutions that will surely help you streamline your research project. Contact us today!
