AWS HPC Blog
Tag: Machine Learning
Advancing research in the cloud: AWS announces expanded training resources
AWS is investing in researcher training with new learning plans for HPC, quantum, stats, AI/ML & generative AI. Check out the details!
Simulating complex systems with LLM-driven agents: leveraging AWS ParallelCluster for scalable AI experiments
How might AI change the rules of the energy game? A new post explores using large language models to power smarter, more adaptive agents in an energy supply chain simulation. Learn how LLMs could enable more nuanced decision-making behaviors.
Automotive component design at Nifco using generative AI and diffusion models
Combining generative AI with AWS services, Nifco USA is exploring new frontiers in structural design. See how they’re using diffusion models, SageMaker, and Batch to create game-changing lightweight auto parts.
Use Terraform to deploy a complete AWS Batch environment on Amazon EKS
Harness the power of AWS Batch on Amazon EKS with this new Terraform blueprint. It provides a complete template to create robust batch processing in the cloud. An easy button you shouldn’t miss.
A guide to identity management in Research and Engineering Studio on AWS
Check out this new post to learn about identity options for Research and Engineering Studio on AWS. Understanding choices for SAML IdPs and Active Directory will help you plan secure VDI access.
LLMs: the new frontier in generative agent-based simulation
How can LLMs take agent-based simulation to the next level? Check out our new post on leveraging large language models’ capabilities for more realistic modeling.
Harnessing the power of agent-based modeling for equity market simulation and strategy testing
Financial professionals: Simulate realistic market conditions with Simudyne’s agent-based modeling on AWS and Red Hat OpenShift. Learn how HKEX leverages these insights.
Recent improvement to Open MPI AllReduce and the impact to application performance
Our team engineered some Open MPI optimizations for EFA to enhance performance of HPC codes running in the cloud. By improving MPI_AllReduce they improved scaling – matching commercial MPIs. Tests show gains for apps including Code Saturne and OpenFOAM on both Arm64 and x86 instances. Check out how these tweaks can speed up your HPC workloads in the cloud.
Near-real-time energy production forecasts with NVIDIA Earth-2 and AWS Batch
Using AWS Batch and NVIDIA Earth-2, we built a scalable workflow that explores millions of scenarios at a fraction of the cost of traditional methods. This innovative approach not only provides rapid energy calculations, but also shows the potential of AI-driven meteorology.
Whisper audio transcription powered by AWS Batch and AWS Inferentia
Transcribe audio files at scale for really low cost using Whisper and AWS Batch with Inferentia. Check out this post to deploy a cost-effective solution in minutes!