AWS HPC Blog
Tag: Scientific Computing
Renewable energy transition: examining the impacts of wind energy through simulation
As we move towards a greener future, understanding wind energy’s climate impacts is key. Check out this blog post by our friends at Whiffle, to learn how large-scale simulations reveal wind power’s effect on our atmosphere.
Choosing the right compute orchestration tool for your research workload
Running big research jobs on AWS but not sure where to start? We break down options like Batch, ECS, EKS, and others to pick the right tool for your needs. Lots of examples for genomics, ML, engineering, and more!
Introducing new alerts to help users detect and react to blocked job queues in AWS Batch
Heads up AWS Batch users! Learn how to get notifications when your job queue gets blocked so you can quickly troubleshoot and keep your workflows moving. Details in our blog.
How agent-based models powered by HPC are enabling large scale economic simulations
See how agent-based models, driven to scale by HPC in the cloud, are shedding new light on macroprudential policies with this post from Oxford’s Institute for New Economic Thinking.
Amazon’s renewable energy forecasting: continuous delivery with Jupyter Notebooks
Interested in eliminating friction between data science and engineering teams? Read this post to learn how Amazon successfully transitioned Jupyter Notebooks from the lab to production.
Dynamic HPC budget control using a core-limit approach with AWS ParallelCluster
Balancing fixed budgets with fluctuating HPC needs is challenging. Discover a customizable solution for automatically setting weekly resource limits based on previous spending.
Accelerating molecule discovery with computational chemistry and Promethium on AWS
Interested in performing high-accuracy computational chemistry simulations faster? Check out this new post about Promethium, a solution from QC Ware that leverages AWS to accelerate simulations by up to 100x.
Leveraging Seqera Platform on AWS Batch for machine learning workflows – Part 2 of 2
In this second part of using Nextflow for machine learning for life science workloads, we provide a step-by-step guide, explaining how you can easily deploy a Seqera environment on AWS to run ML and other pipelines.
Save up to 90% using EC2 Spot, even for long-running HPC jobs
New OS-level checkpointing tools can let you run existing HPC codes on EC2 Spot instances with minimal impact from interruptions. Read on for the details.
Slurm REST API in AWS ParallelCluster
Looking to integrate AWS ParallelCluster into an automated workflow? This post shows how to submit and monitor jobs programmatically with Slurm REST API (code examples included).