Compare AWS Parallel Computing Service vs. Amazon EC2 Trn2 Instances in 2025

AWS Parallel Computing Service

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Description

AWS Parallel Computing Service (AWS PCS) is a fully managed service designed to facilitate the execution and scaling of high-performance computing tasks while also aiding in the development of scientific and engineering models using Slurm on AWS. This service allows users to create comprehensive and adaptable environments that seamlessly combine computing, storage, networking, and visualization tools, enabling them to concentrate on their research and innovative projects without the hassle of managing the underlying infrastructure. With features like automated updates and integrated observability, AWS PCS significantly improves the operations and upkeep of computing clusters. Users can easily construct and launch scalable, dependable, and secure HPC clusters via the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. The versatility of the service supports a wide range of applications, including tightly coupled workloads such as computer-aided engineering, high-throughput computing for tasks like genomics analysis, GPU-accelerated computing, and specialized silicon solutions like AWS Trainium and AWS Inferentia. Overall, AWS PCS empowers researchers and engineers to harness advanced computing capabilities without needing to worry about the complexities of infrastructure setup and maintenance.

Description

Amazon EC2 Trn2 instances, equipped with AWS Trainium2 chips, are specifically designed to deliver exceptional performance in the training of generative AI models, such as large language and diffusion models. Users can experience cost savings of up to 50% in training expenses compared to other Amazon EC2 instances. These Trn2 instances can accommodate as many as 16 Trainium2 accelerators, boasting an impressive compute power of up to 3 petaflops using FP16/BF16 and 512 GB of high-bandwidth memory. For enhanced data and model parallelism, they are built with NeuronLink, a high-speed, nonblocking interconnect, and offer a substantial network bandwidth of up to 1600 Gbps via the second-generation Elastic Fabric Adapter (EFAv2). Trn2 instances are part of EC2 UltraClusters, which allow for scaling up to 30,000 interconnected Trainium2 chips within a nonblocking petabit-scale network, achieving a remarkable 6 exaflops of compute capability. Additionally, the AWS Neuron SDK provides seamless integration with widely used machine learning frameworks, including PyTorch and TensorFlow, making these instances a powerful choice for developers and researchers alike. This combination of cutting-edge technology and cost efficiency positions Trn2 instances as a leading option in the realm of high-performance deep learning.