Tag: research computing

Pathologists have been looking at morphological patterns in patients’ tissue sections highlighted by hematoxylin and eosin (H&E) staining for more than a century. However, as the pathology transformation from glass slides to digital imaging gains momentum, it opens the door to artificial intelligence (AI) tools to complement expert assessment with quantitative measurements to enable data-driven medicine. Yet, challenges remain with handling digital imaging files such as storage and pre-processing prior to application of AI tools. Genomics England have utilised Amazon Web Services (AWS) and tools such as Amazon SageMaker to demonstrate how to prepare digital pathology images for research and the development of machine learning models.

Amazon Web Services (AWS) works with higher education institutions, research labs, and researchers around the world to offer cost-effective, scalable, and secure compute, storage, and database capabilities to accelerate time to science. In our work with research leaders and stakeholders, users often ask us about best practices for leveraging cloud for research. In this post, we dive into five common questions we field from research leaders as they build the academic research innovation centers of the future.

In 2022, Emory launched the AI.Humanity initiative to explore the societal impacts of artificial intelligence (AI) and influence its future development to serve humanity. Emory aims to be a leading advocate for ethical use of AI and a top destination for students and faculty seeking to understand and apply its transformative technologies. Read this blog post to learn how Emory uses Amazon Web Services (AWS) to support the computing needs of AI.Humanity.

Japan’s Mount Fuji is famous for its height and width but it’s also reachable by novice hikers without lots of time on their hands due to the nation’s efforts to make it accessible. Now, the researchers behind one of the world’s fastest supercomputers, Fugaku, which is another name for Mt. Fuji, are trying to make the supercomputer just as accessible on the Amazon Web Services (AWS) Cloud. Read this post to learn more.

Dr. Kevin Leyton-Brown and Neil Newman are computer scientists at the University of British Columbia (UBC) working at the intersection of artificial intelligence (AI) and microeconomic theory. Their research demands large-scale, high-performance computing, in episodic bursts, to run parallel simulations of complex auctions. When Leyton-Brown and Newman began research into the computationally complex auction theory behind the 2016 United States wireless spectrum auction, their ML models required significantly more computing power than their on-premises infrastructure could provide. The UBC team turned to RONIN, an AWS Partner, and the virtually unlimited infrastructure of the AWS Cloud, to accelerate their time to answers and new discoveries.

Amazon Lightsail for Research is a new service that makes it simple to incorporate cloud computing resources into your work without cloud experience. With Lightsail for Research, you can shift large and/or time-consuming analysis from your laptop onto powerful cloud resources, run multiple analyses simultaneously, and continue computations even when your laptop is off or being used for other activities. In this blog post, learn how to use Lightsail for Research with a simple but common use case.

How do we avoid the next global pandemic? For researchers collaborating with the University of British Columbia Cloud Innovation Center (UBC CIC), the answer to that question lies in a massive library of genetic sequencing data. But there is a problem: the data library is so massive that traditional computing can’t comprehensively analyze or process it. So the UBC CIC team collaborated with computational virologists to create Serratus, an open-science viral discovery platform to transform the field of genomics—built on the massive computational power of the Amazon Web Services (AWS) Cloud.

Galaxy is a scientific workflow, data integration, and digital preservation platform that aims to make computational biology accessible to research scientists that do not have computer programming or systems administration experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system, running on everything from academic mainframes to personal computers. But researchers and organizations may worry about capacity and the accessibility of compute power for those with limited or restrictive budgets. In this blog post, we explain how to implement Galaxy on the cloud at a predictable cost within your research or grant budget with Amazon Lightsail.

According to a new IDC report, the cloud is helping researchers conduct research faster than ever before by reducing data analysis and processing times, and is allowing researchers around the world to collaborate on solving universal problems. In addition to the positive impact on research, IDC also forecasts that continued adoption of cloud computing globally could prevent environmental emission of more than 1 billion metric tons of CO2 from 2021 through 2024, almost equivalent to removing the 2020 CO2 emissions of Germany and the U.K. combined.

To allow more visibility into and management of AWS resources and expenses and minimize the cloud skills training required to operate these resources, AWS Partner RONIN created the RONIN research computing platform. RONIN gives researchers the ability to create exactly the computers or storage that they need in minutes. With access to the flexibility and scalability of the cloud, researchers are able to store and process larger datasets, collaborate globally, and adapt to changing technologies and research methods instantly.