AWS Open Source Blog

Category: Amazon EC2

User uploads data in BIDS format to S3 and starts the Lambda function → Lambda parses the uploaded data and launches a cluster of EC2 instances → EC2 instances run fMRIprep which preprocesses the data → preprocessed data are saved to S3.

fMRI data preprocessing on AWS using fMRIprep

A typical fMRI study often produces imaging data of terabytes or more. Storing and preprocessing this data can be challenging on a single computer because it often has neither enough disk space to store the data nor enough computing power to preprocess it. Traditionally, researchers use a combination of cloud-based storage and on-premises high-performance clusters […]

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Deploying an HPC cluster and remote visualization in a single step using AWS ParallelCluster

Since its initial release in November 2018, AWS ParallelCluster (an AWS-supported open source tool) has made it easier and more cost effective for users to manage and deploy HPC clusters in the cloud. Since then, the team has continued to enhance the product with more configuration flexibility and enhancements like built-in support for the Elastic […]

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AWS Fargate container logs collection and analysis with AWS FireLens and Sumo Logic

AWS Fargate is a compute engine for Amazon ECS that allows you to run containers without having to manage servers or clusters. Fargate manages provisioning, configuration, and scaling of the clusters. With Fargate, you can focus on your application design and implementation instead of worrying about the infrastructure. In this post, we’ll provide an overview […]

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Best Practices for Running Ansys Fluent Using AWS ParallelCluster

Using HPC (high performance computing) to solve Computational Fluid Dynamics (CFD) challenges has become common practice. As the growth from HPC workstation to supercomputer has slowed over the last decade or two, compute clusters have increasingly taken the place of single, big SMP (shared memory processing) supercomputers, and have become the ‘new normal’. Another, more […]

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