Category: AWS Batch

In this post, I show how the new shared memory support in AWS Batch is able to improve performance while decreasing the latency of the intra-node communication. This performance gain can also lower the cost of running jobs overall.

This post is authored by Deepthi Chelupati, Senior Product Manager for Amazon EC2 Spot Instances, and Chad Schmutzer, Principal Developer Advocate for Amazon EC2 Customers have been using EC2 Spot Instances to save money and scale workloads to new levels for over a decade. Launched in late 2009, Spot Instances are spare Amazon EC2 compute […]

This post is contributed by Christian Kniep, Sr. Developer Advocate, HPC and AWS Batch. Scientists, researchers, and engineers are using AWS Batch to run workloads reliably at scale, and to offload the undifferentiated heavy lifting in their day-to-day work. But even with a slight chance of failure in the stack, the act of mitigating these […]

This post is contributed by Alberto Falzone, Consultant, HPC and Roberto Meda, Senior Consultant, HPC. High Performance Computing (HPC) workflows across industry verticals such as Design and Engineering, Oil and Gas, and Life Sciences often require GPU-based 3D/OpenGL rendering. Setting up drivers and applications for these types of workflows can require significant effort. Similar GPU […]

This post was written by Christian Kniep, Senior Developer Advocate for HPC and AWS Batch.  For HPC workloads, visibility into the logs of jobs is important to debug a job which failed, but also to have insights into a running job and track its trajectory to influence the configuration of the next job or terminate […]

In this post, I show how to integrate the AWS Batch CLI by AWS ParallelCluster with API Gateway.

This post is written by Sivasubramanian Ramani In many real work applications, you can use custom Docker images with AWS Batch and AWS CloudFormation to execute complex jobs efficiently.   This post provides a file processing implementation using Docker images and Amazon S3, AWS Lambda, Amazon DynamoDB, and AWS Batch. In this scenario, the user […]

This post is contributed by Steve Kendrex, Senior Technical Product Manager, AWS Batch   Introduction   AWS offers a broad range of instances that are advantageous for batch workloads. The scale and provisioning speed of AWS’ compute instances allow you to get up and running at peak capacity in minutes without paying for downtime. Today, I’m […]

Leveraging Elastic Fabric Adapter to run HPC and ML Workloads on AWS Batch  This post is contributed by  Sean Smith, Software Development Engineer II, AWS ParallelCluster & Arya Hezarkhani, Software Development Engineer II, AWS Batch and HPC   On August 2, 2019, AWS Batch announced support for Elastic Fabric Adapter (EFA). This enables you to run highly […]

This post is courtesy of Lee Pang – AWS Technical Business Development  I recently worked with a customer who needed to process a bunch of raw sequence files (FastQs) into Hi-C format (*.hic), which is used for the structural analysis of DNA/chromatin loops and sequence accessibility. The tooling they were interested in using was the Juicer […]