Best HPC Software for AWS Trainium

Compare the Top HPC Software that integrates with AWS Trainium as of November 2025

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This a list of HPC software that integrates with AWS Trainium. Use the filters on the left to add additional filters for products that have integrations with AWS Trainium. View the products that work with AWS Trainium in the table below.

What is HPC Software for AWS Trainium?

High-Performance Computing (HPC) software are applications designed to maximize computational power, enabling complex and resource-intensive tasks to be executed efficiently. These programs optimize parallel processing, often leveraging supercomputers or distributed computing clusters to solve problems in fields like scientific research, engineering, and data analytics. HPC software includes components for workload management, data communication, and performance tuning, ensuring scalability and efficient resource utilization. Examples include simulation software, machine learning frameworks, and tools for weather modeling or molecular dynamics. By harnessing advanced algorithms and hardware, HPC software accelerates computation, reducing the time required for tasks that would otherwise take weeks or months on conventional systems. Compare and read user reviews of the best HPC software for AWS Trainium currently available using the table below. This list is updated regularly.

1

Amazon EC2 P4 Instances

Amazon

Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.

Starting Price: $11.57 per hour

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2

AWS Parallel Computing Service

Amazon

AWS Parallel Computing Service (AWS PCS) is a managed service that simplifies running and scaling high-performance computing workloads and building scientific and engineering models on AWS using Slurm. It enables the creation of complete, elastic environments that integrate computing, storage, networking, and visualization tools, allowing users to focus on research and innovation without the burden of infrastructure management. AWS PCS offers managed updates and built-in observability features, enhancing cluster operations and maintenance. Users can build and deploy scalable, reliable, and secure HPC clusters through the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. The service supports various use cases, including tightly coupled workloads like computer-aided engineering, high-throughput computing such as genomics analysis, accelerated computing with GPUs, and custom silicon like AWS Trainium and AWS Inferentia.

Starting Price: $0.5977 per hour

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3

Amazon EC2 P5 Instances

Amazon

Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery.

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4

Amazon EC2 UltraClusters

Amazon

Amazon EC2 UltraClusters enable you to scale to thousands of GPUs or purpose-built machine learning accelerators, such as AWS Trainium, providing on-demand access to supercomputing-class performance. They democratize supercomputing for ML, generative AI, and high-performance computing developers through a simple pay-as-you-go model without setup or maintenance costs. UltraClusters consist of thousands of accelerated EC2 instances co-located in a given AWS Availability Zone, interconnected using Elastic Fabric Adapter (EFA) networking in a petabit-scale nonblocking network. This architecture offers high-performance networking and access to Amazon FSx for Lustre, a fully managed shared storage built on a high-performance parallel file system, enabling rapid processing of massive datasets with sub-millisecond latencies. EC2 UltraClusters provide scale-out capabilities for distributed ML training and tightly coupled HPC workloads, reducing training times.

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