In this blog post, we demonstrate how to leverage the AWS Genomics Command line and Amazon SageMaker to analyze large-scale exome sequences and derive meaningful insights. We use the bioinformatics workflow manager Nextflow, it’s open …
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Today is the first part of a 2-part series and we’re covering all the aspects of designing and creating ParallelClusters using PCluster Manager, which is a graphical user interface tool for making all the hard bits of cluster …
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In this blog post, we’ll walk you through the process of building a successful Cryo-EM benchmarking pilot using AWS ParallelCluster, Amazon FSx for Lustre, and cryoSPARC (from Structura Biotechnology) and explain some of our design …
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This blog post explains how to run parallel rendering workloads and produce an animation in a cost and time effective way using AWS Batch and AWS Step Functions. AWS Batch manages the rendering jobs on Amazon Elastic Compute Cloud (Amazon …
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Machine Learning is a huge workload, and one of the most demanding when it comes to scaling to thousands (and thousands) of CPUs. Some of the largest workloads customers run in the cloud are deep learning models, which require huge numbers …
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In this blog post, we’ll show how you can run NVIDIA Parabricks on AWS Batch leveraging AWS CloudFormation templates. Parabricks is a GPU-accelerated tool for secondary genomic analysis. It reduces the runtime of variant calling on a 30x …
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As companies shift high-performance workloads toward cloud solutions, data storage and data protection go side-by-side. Many companies have both internal and external security rules and regulations they must adhere to when storing their …
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The Ampersand Data Science team had a challenge: their Bayesian statistical models needed more than half a million core-hours of runtime, regularly, if they were to get an answer fast enough for it to be useful to their customers.
Scaling …
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