Showing items from AWS Batch

Protein Structure Prediction at Scale using AWS Batch

In this post, we discuss how Novo Nordisk approached the deployment of a scale-out HPC platform for running AlphaFold, while meeting their enterprise IT requirements and keeping the user experience simple. Read the Post on the AWS Blog …

Streamlining distributed ML workflow orchestration using Covalent with AWS Batch

Complicated multi-step workflows can be challenging to deploy, especially when using a variety of high-compute resources. Covalent is an open-source orchestration tool that streamlines the deployment of distributed workloads on AWS …

Perform batch transforms with Amazon SageMaker Jumpstart Text2Text Generation large language models

Today we are excited to announce that you can now perform batch transforms with Amazon SageMaker JumpStart large language models (LLMs) for Text2Text Generation. Batch transforms are useful in situations where the responses don’t need to be …

Benchmarking the Oxford Nanopore Technologies basecallers on AWS

Oxford Nanopore sequencers enables direct, real-time analysis of long DNA or RNA fragments. They work by monitoring changes to an electrical current as nucleic acids are passed through a protein nanopore. The resulting signal is decoded to …

Run Celery workers for compute-intensive tasks with AWS Batch

Many applications leverage distributed task systems like Celery to handle asynchronous work. In this post, we describe how to handle compute-intensive Celery tasks using AWS Batch to scale the compute resources and run worker agents. Read …

How Evolvere Biosciences performs macromolecule design on AWS

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 …

Create SageMaker Pipelines for training, consuming and monitoring your batch use cases

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 …

Explore costs of AWS Batch jobs run on Amazon EKS using pod labels and Kubecost

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