AWS HPC Blog
Category: AWS Batch
Scale Reinforcement Learning with AWS Batch Multi-Node Parallel Jobs
Autonomous robots are increasingly used across industries, from warehouses to space exploration. While developing these robots requires complex simulation and reinforcement learning (RL), setting up training environments can be challenging and time-consuming. AWS Batch multi-node parallel (MNP) infrastructure, combined with NVIDIA Isaac Lab, offers a solution by providing scalable, cost-effective robot training capabilities for sophisticated behaviors and complex tasks.
Adding functionality to your applications using multiple containers in AWS Batch
Discover how to coordinate multiple applications in separate containers within a single AWS Batch job definition. Learn the benefits of this approach and how to share resources between containers for more efficient, scalable deployments.
Enhancing Equity Strategy Backtesting with Synthetic Data: An Agent-Based Model Approach – part 2
Developing robust investment strategies requires thorough testing, but relying solely on historical data can introduce biases and limit your insights. Learn how synthetic data from agent-based models can provide an unbiased testbed to systematically evaluate your strategies and prepare for future market scenarios. Part 2 covers implementation details and results.
How to use rate-limited resources in AWS Batch jobs with resource aware scheduling
Struggling with bottlenecks in your batch processing? AWS Batch’s new resource aware scheduling capability could be the solution your business needs. This feature allows you to define and manage consumable resources, helping maximize the use of your compute power. Check out our blog to learn more.
Using the Terraform AWS Cloud Control provider for managing AWS Batch resources
The Terraform AWS Cloud Control (AWSCC) provider now supports AWS Batch job definitions, enabling you to leverage recent and future enhancements to AWS Batch. Learn more in our latest blog post.
Adding configurable namespaces, persistent volume claims, and other features for AWS Batch on Amazon EKS
Exciting updates to AWS Batch on Amazon EKS! Configurable namespaces, persistent volume claims, and more. Check out our blog post to see how these features can help manage your complex containerized workloads.
How Caris Life Sciences processed 400,000 RNAseq samples in 2.5 days with AWS Batch
In the race to deliver precision medicine, time is of the essence. Caris Life Sciences, a pioneer in this field, leveraged AWS Batch to build a highly scalable solution that processed hundreds of thousands of genomic samples in record time. Discover how they achieved this remarkable feat and the key services that powered their breakthrough.
Smashing computational barriers: data-driven ball-impact modeling on AWS
Elevate your engineering capabilities with lightning-fast impact prediction. Our new blog post delves into how advanced ML models, like U-Nets and Fourier Neural Operators, are revolutionizing transient response forecasting for critical industries like consumer electronics, automotive, and aerospace. Gain a competitive edge by integrating these cutting-edge techniques.
Run protein folding on AWS with Quantori
Curious about running AI-powered protein folding analyses on AWS? Quantori’s new solution makes it easy to test generative models and visualize results in your own cloud environment.
Unlock large-scale autonomous driving simulations on AWS with IPG
Discover how AWS Batch’s multi-container features enable large-scale AV/ADAS simulations with the IPG CarMaker simulator. Learn about the challenges of integrating complex, interdependent vehicle systems.