AWS HPC Blog

Category: High Performance Computing

Rearchitecting AWS Batch managed services to leverage AWS Fargate

AWS service teams continuously improve the underlying infrastructure and operations of managed services, and AWS Batch is no exception. The AWS Batch team recently moved most of their job scheduler fleet to a serverless infrastructure model leveraging AWS Fargate. I had a chance to sit with Devendra Chavan, Senior Software Development Engineer on the AWS Batch team, to discuss the move to AWS Fargate and its impact on the Batch managed scheduler service component.

44-Qubit quantum circuits simulated using AWS ParallelCluster 

Simulating 44-Qubit quantum circuits using AWS ParallelCluster

A key part of the development of quantum hardware and quantum algorithms is simulation using existing classical architectures and HPC techniques. In this blog post, we describe how to perform large-scale quantum circuits simulations using AWS ParallelCluster with QuEST, the Quantum Exact Simulation Toolkit. We demonstrate a simple and rapid deployment of computational resources up to 4,096 compute instances to simulate random quantum circuits with up to 44 qubits. We were able to allocate as many as 4096 EC2 instances of c5.18xlarge to simulate a non-trivial 44 qubit quantum circuit in fewer than 3.5 hours.

Accelerating Genomics Pipelines Using Intel’s Open Omics Acceleration Framework on AWS

In this blog, we showcase the first version of Open Omics and benchmark three applications that are used in processing NGS data – sequence alignment tools BWA-MEM, minimap2, and single cell ATAC-Seq on Xeon-based Amazon Elastic Compute Cloud (Amazon EC2) Instances.

Building a Scalable Predictive Modeling Framework in AWS – Part 3

In this final part of this three-part blog series on building predictive models at scale in AWS, we will use the synthetic dataset and the models generated in the previous post to showcase the model updating and sensitivity analysis capabilities of the aws-do-pm framework.

Building a Scalable Predictive Modeling Framework in AWS – Part 2

In the first part of this three-part blog series, we introduced the aws-do-pm framework for building predictive models at scale in AWS. In this blog, we showcase a sample application for predicting the life of batteries in a fleet of electric vehicles, using the aws-do-pm framework.

Building a Scalable Predictive Modeling Framework in AWS – Part 1

Predictive models have powered the design and analysis of real-world systems such as jet engines, automobiles, and powerplants for decades. These models are used to provide insights on system performance and to run simulations, at a fraction of the cost compared to experiments with physical hardware. In this first post of three, we described the motivation and general architecture of the open-source aws-do-pm framework project for building predictive models at scale in AWS.