In this blog post, we catch a glimpse into drug discovery to see how Evolvere Biosciences has deployed a customized architecture w/ AWS Batch and Nextflow to quickly and easily run its macromolecule design pipeline. Read the Post on the AWS …
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Batch inference is a common pattern where prediction requests are batched together on input, a job runs to process those requests against a trained model, and the output includes batch prediction responses that can then be consumed by other …
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Today we show you how to get insights into the costs of running AWS Batch workloads on Amazon EKS using Kubernetes pod labels with Kubecost. Read the Post on the AWS Blog Channel
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In this post, AWS Professional Services highlights how they helped data scientists from Amazon Logistics rearchitect their algorithm for improving the efficiency of their supply-chain by making better planning decisions. Leveraging best …
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AWS Batch customers often ask for guidance to optimize their architectures and make their workload to scale rapidly. Here we describe an observability solution that provides insights into your AWS Batch architectures and allows you to …
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To build machine learning models, machine learning engineers need to develop a data transformation pipeline to prepare the data. The process of designing this pipeline is time-consuming and requires a cross-team collaboration between …
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Since launch, EFA has seen continuous improvements in performance. In this post, we talk about our 2nd generation of EFA, which takes another step in improving Machine Learning and High Performance Computing in the Cloud. Read the Post on …
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AWS Batch is a fully-managed AWS service that orchestrates vast numbers of jobs using containers. It leverages some of your favorite container systems - Amazon ECS and Kubernetes, and - above all: makes your life easier because it handles …
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