AWS HPC Blog
Tag: AI
What’s the difference between AWS ParallelCluster and AWS Parallel Computing Service?
It’s been a year since we announced AWS Parallel Computing Service (PCS). In a way this is the third generation of Slurm-based HPC orchestrators that we’ve brought to you. We’ve learned much from helping customers deploy serious production workloads on AWS ParallelCluster, which itself grew from the foundations layed by CfnCluster – the open-source project […]
Announcing expanded support for Custom Slurm Settings in AWS Parallel Computing Service
Today we’re excited to announce expanded support for custom Slurm settings in AWS Parallel Computing Service (PCS). With this launch, PCS now enables you to configure over 65 Slurm parameters. And for the first time, you can also apply custom settings to queue resources, giving you partition-specific control over scheduling behavior. This release responds directly […]
Announcing Capacity Blocks support for AWS Parallel Computing Service
This post was contributed by by Kareem Abdol-Hamid, Kyle Bush Today we’re happy to announce that support for Amazon EC2 Capacity Blocks for Machine Learning are now supported in AWS Parallel Computing Service (AWS PCS). This allows you to reserve and schedule GPU-accelerated Amazon EC2 instances for future use. That includes the NVIDIA Hopper GPU […]
Scaling your LLM inference workloads: multi-node deployment with TensorRT-LLM and Triton on Amazon EKS
LLMs are scaling exponentially. Learn how advanced technologies like Triton, TRT-LLM and EKS enable seamless deployment of models like the 405B parameter Llama 3.1. Let’s go large.
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.
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!
Using machine learning to drive faster automotive design cycles
Aerospace and automotive companies are speeding up their product design using AI. In this post we’ll discuss how they’re using machine learning to shift design cycles from hours to seconds using surrogate models.
Protein language model training with NVIDIA BioNeMo framework on AWS ParallelCluster
In this new post, we discuss pre-training ESM-1nv for protein language modeling with NVIDIA BioNeMo on AWS. Learn how you can efficiently deploy and customize generative models like ESM-1nv on GPU clusters with ParallelCluster. Whether you’re studying protein sequences, predicting properties, or discovering new therapeutics, this post has tips to accelerate your protein AI workloads on the cloud.
Using large-language models for ESG sentiment analysis using Databricks on AWS
ESG is now a boardroom issue. See how Databricks’ AI solution helps understand emissions data and meet new regulations.
Launch self-supervised training jobs in the cloud with AWS ParallelCluster
In this post we describe the process to launch large, self-supervised training jobs using AWS ParallelCluster and Facebook’s Vision Self-Supervised Learning (VISSL) library.