Enhancing High Performance Computing Workloads on AWS to Promote Environmental Sustainability | Amazon Web Services

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High-performance computing (HPC) workloads are essential across various industries, but they can have a significant impact on energy consumption and carbon emissions. Companies are increasingly looking to reduce their carbon footprint, with on-premises HPC clusters being a major contributor to data center emissions. By migrating their HPC workloads to AWS, Baker Hughes managed to reduce their carbon footprint by 99%, setting an example for the industry.

To optimize HPC workloads for resource efficiency and environmental impact, focusing on the pillars of compute, storage, networking, visualization, and orchestration is crucial. Choosing the right instance type, such as the Amazon EC2 Hpc7a instance, and utilizing AWS Graviton instances for energy efficiency are key considerations. Additionally, selecting the right AWS Region based on business requirements and sustainability goals can further enhance environmental impact reduction.

Storage choices play a significant role in optimizing HPC workloads. Utilizing managed file system offerings like Amazon FSx for Lustre for shared storage and leveraging lifecycle policies for data management can contribute to efficiency. Networking considerations, such as using Cluster Placement Groups and Elastic Fabric Adapter for tightly coupled workloads, can help ensure optimal resource utilization.

Orchestration tools like AWS Batch and AWS ParallelCluster enable efficient management of compute resources based on workload needs, reducing unnecessary resource consumption and energy usage. Remote visualization technologies like NICE DCV can enhance interactive model setup and visualization without the need for large data transfers.

Evaluating sustainability improvements for HPC workloads involves analyzing proxy measures like computational resource cost and unit of work KPIs. By optimizing resource utilization and selecting cost-effective EC2 instances, companies can work towards reducing their average cost per job and enhancing efficiency.

In conclusion, transitioning HPC workloads to AWS and following best practices for resource optimization and sustainability can significantly reduce carbon emissions and environmental impact, while maintaining business objectives. By leveraging AWS services and tools, companies can achieve environmental sustainability goals while continuing to innovate and grow.

Article Source
https://aws.amazon.com/blogs/hpc/improve-hpc-workloads-on-aws-for-environmental-sustainability/